{"type":"session","version":3,"id":"019da792-b2b1-701a-b70b-d0ab6d2ed023","timestamp":"2026-04-19T21:08:22.321Z","cwd":"/home/sebas"}
{"type":"model_change","id":"a2382402","parentId":null,"timestamp":"2026-04-19T21:08:22.499Z","provider":"openai-codex","modelId":"gpt-5.4"}
{"type":"thinking_level_change","id":"c4ad60dd","parentId":"a2382402","timestamp":"2026-04-19T21:08:22.499Z","thinkingLevel":"off"}
{"type":"message","id":"f0b60b9a","parentId":"c4ad60dd","timestamp":"2026-04-19T21:08:30.500Z","message":{"role":"user","content":[{"type":"text","text":"current state?"}],"timestamp":1776632910497}}
{"type":"message","id":"e44b0100","parentId":"f0b60b9a","timestamp":"2026-04-19T21:08:32.012Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Sa5yr8eN9JSV6ipTbkpiDX7K|fc_071e452a5a0ea02e0169e5444f623c8190addfe30d3fb3d2b5","name":"read","arguments":{"path":"/home/sebas/.agents/skills/personal-status/SKILL.md"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":3036,"output":31,"cacheRead":0,"cacheWrite":0,"totalTokens":3067,"cost":{"input":0.00759,"output":0.000465,"cacheRead":0,"cacheWrite":0,"total":0.008055}},"stopReason":"toolUse","timestamp":1776632910505,"responseId":"resp_071e452a5a0ea02e0169e5444ecaac81908d6c804afec2cd2c"}}
{"type":"message","id":"1bbbe31f","parentId":"e44b0100","timestamp":"2026-04-19T21:08:32.058Z","message":{"role":"toolResult","toolCallId":"call_Sa5yr8eN9JSV6ipTbkpiDX7K|fc_071e452a5a0ea02e0169e5444f623c8190addfe30d3fb3d2b5","toolName":"read","content":[{"type":"text","text":"---\nname: personal-status\ndescription: Inspect a personal-agent research run and report current state\n---\n\n# personal-status\n\n## Workflow\n\n1. Use run id.\n2. Execute:\n   - `curl -fsSL \"${AGENTS_DB_API:-http://100.116.176.16:8091}/api/memories?run_id=<id>&subtype=research_run&limit=1\"`\n   - `curl -fsSL \"${AGENTS_DB_API:-http://100.116.176.16:8091}/api/memories?run_id=<id>&subtype=research_source&limit=200\"`\n   - `curl -fsSL \"${AGENTS_DB_API:-http://100.116.176.16:8091}/api/memories?run_id=<id>&subtype=research_claim&limit=200\"`\n   - `curl -fsSL \"${AGENTS_DB_API:-http://100.116.176.16:8091}/api/tasks?status=open&limit=200\"` (filter by `metadata.run_id == <id>` for open tasks)\n3. Summarize:\n   - goal\n   - status\n   - source count\n   - claim count\n   - open tasks / gaps\n"}],"isError":false,"timestamp":1776632912042}}
{"type":"message","id":"384c91d9","parentId":"1bbbe31f","timestamp":"2026-04-19T21:08:34.419Z","message":{"role":"assistant","content":[{"type":"text","text":"Need the run id.\n\nIf you mean “current state” of a specific research run, send the run id and I’ll pull:\n- goal\n- status\n- source count\n- claim count\n- open tasks / gaps\n\nIf you mean machine/service state instead, say:\n- `services`\n- `server`\n- `project`\n- or the repo/path you mean","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e54450c70881908eab9da75a921218\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":390,"output":80,"cacheRead":2944,"cacheWrite":0,"totalTokens":3414,"cost":{"input":0.0009750000000000001,"output":0.0012000000000000001,"cacheRead":0.000736,"cacheWrite":0,"total":0.0029110000000000004}},"stopReason":"stop","timestamp":1776632912059,"responseId":"resp_071e452a5a0ea02e0169e544505f24819096b1f1b60cd1347b"}}
{"type":"message","id":"d5b955b5","parentId":"384c91d9","timestamp":"2026-04-19T21:08:41.880Z","message":{"role":"user","content":[{"type":"text","text":"machine"}],"timestamp":1776632921878}}
{"type":"message","id":"7d152620","parentId":"d5b955b5","timestamp":"2026-04-19T21:08:48.995Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_l4BbYkzpznyzF3Db8xhImBh8|fc_071e452a5a0ea02e0169e5446092bc8190b19deaf0bcbe8f1b","name":"bash","arguments":{"command":"hostnamectl --static || hostname","timeout":10}},{"type":"toolCall","id":"call_rH1XCtHtjYj5zlqyIc3PICZ3|fc_071e452a5a0ea02e0169e5446092d48190917a483e94e382af","name":"bash","arguments":{"command":"uptime -p; echo '---'; uptime","timeout":10}},{"type":"toolCall","id":"call_idZpGuldTX8yR5fjILh1Y1e2|fc_071e452a5a0ea02e0169e5446092e08190a92f818fa6dab0ad","name":"bash","arguments":{"command":"df -h / /mnt/rpi 2>/dev/null","timeout":10}},{"type":"toolCall","id":"call_RzCmukVq0bX5UuqkVMgrY559|fc_071e452a5a0ea02e0169e5446092e881909828c2377e4b03f8","name":"bash","arguments":{"command":"free -h","timeout":10}},{"type":"toolCall","id":"call_MrKNW0Ekv0mqtoWGJTXQI21W|fc_071e452a5a0ea02e0169e5446092f08190b85fdc3a967ed047","name":"bash","arguments":{"command":"systemctl is-system-running || true; echo '---'; systemctl --failed --no-legend || true","timeout":10}},{"type":"toolCall","id":"call_BxgFOjWEL29akBxgE1zqQjpJ|fc_071e452a5a0ea02e0169e5446092f88190a26d148612f60cb1","name":"bash","arguments":{"command":"curl -fsS http://100.116.176.16:8082/api/status; echo '---'; curl -fsS http://100.116.176.16:8091/api/status","timeout":10}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":93,"output":217,"cacheRead":3328,"cacheWrite":0,"totalTokens":3638,"cost":{"input":0.0002325,"output":0.003255,"cacheRead":0.000832,"cacheWrite":0,"total":0.0043195}},"stopReason":"toolUse","timestamp":1776632921880,"responseId":"resp_071e452a5a0ea02e0169e5445a27f48190ab86e0d22641bec4"}}
{"type":"message","id":"8dd48021","parentId":"7d152620","timestamp":"2026-04-19T21:08:49.113Z","message":{"role":"toolResult","toolCallId":"call_l4BbYkzpznyzF3Db8xhImBh8|fc_071e452a5a0ea02e0169e5446092bc8190b19deaf0bcbe8f1b","toolName":"bash","content":[{"type":"text","text":"ballbox-first\n"}],"isError":false,"timestamp":1776632929113}}
{"type":"message","id":"325946be","parentId":"8dd48021","timestamp":"2026-04-19T21:08:49.114Z","message":{"role":"toolResult","toolCallId":"call_rH1XCtHtjYj5zlqyIc3PICZ3|fc_071e452a5a0ea02e0169e5446092d48190917a483e94e382af","toolName":"bash","content":[{"type":"text","text":"up 3 days, 7 hours, 28 minutes\n---\n 18:08:49 up 3 days,  7:28, 13 users,  load average: 0.04, 0.11, 0.24\n"}],"isError":false,"timestamp":1776632929114}}
{"type":"message","id":"f254f68e","parentId":"325946be","timestamp":"2026-04-19T21:08:49.114Z","message":{"role":"toolResult","toolCallId":"call_idZpGuldTX8yR5fjILh1Y1e2|fc_071e452a5a0ea02e0169e5446092e08190a92f818fa6dab0ad","toolName":"bash","content":[{"type":"text","text":"Filesystem      Size  Used Avail Use% Mounted on\n/dev/mmcblk0p2   14G   12G  1.6G  88% /\n/dev/sda1       234G   89G  145G  39% /mnt/rpi\n"}],"isError":false,"timestamp":1776632929114}}
{"type":"message","id":"30af9f39","parentId":"f254f68e","timestamp":"2026-04-19T21:08:49.114Z","message":{"role":"toolResult","toolCallId":"call_RzCmukVq0bX5UuqkVMgrY559|fc_071e452a5a0ea02e0169e5446092e881909828c2377e4b03f8","toolName":"bash","content":[{"type":"text","text":"               total        used        free      shared  buff/cache   available\nMem:           7.9Gi       1.9Gi       3.2Gi       202Mi       3.3Gi       5.9Gi\nSwap:          2.0Gi       492Mi       1.5Gi\n"}],"isError":false,"timestamp":1776632929114}}
{"type":"message","id":"c3d4bed8","parentId":"30af9f39","timestamp":"2026-04-19T21:08:49.115Z","message":{"role":"toolResult","toolCallId":"call_MrKNW0Ekv0mqtoWGJTXQI21W|fc_071e452a5a0ea02e0169e5446092f08190b85fdc3a967ed047","toolName":"bash","content":[{"type":"text","text":"running\n---\n"}],"isError":false,"timestamp":1776632929114}}
{"type":"message","id":"c03fe804","parentId":"c3d4bed8","timestamp":"2026-04-19T21:08:49.170Z","message":{"role":"toolResult","toolCallId":"call_BxgFOjWEL29akBxgE1zqQjpJ|fc_071e452a5a0ea02e0169e5446092f88190a26d148612f60cb1","toolName":"bash","content":[{"type":"text","text":"curl: (52) Empty reply from server\n\n\n[Showing lines 2-3 of 3 (50.0KB limit). Full output: /tmp/pi-bash-81237dc176ac2950.log]\n\nCommand exited with code 52"}],"details":{},"isError":true,"timestamp":1776632929169}}
{"type":"message","id":"39ac73bc","parentId":"c03fe804","timestamp":"2026-04-19T21:08:53.061Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_lQmyoj6X8eEDQ56yicGzG7yz|fc_071e452a5a0ea02e0169e544622b588190ace7cf60eb7f9f09","name":"bash","arguments":{"command":"printf 'personal-agent: '; curl -sS -m 5 -D - -o /tmp/personal-agent-status.out http://100.116.176.16:8082/api/status | head -n 5; echo 'body:'; cat /tmp/personal-agent-status.out 2>/dev/null; echo '---'; printf 'agents-database: '; curl -sS -m 5 -D - -o /tmp/agents-db-status.out http://100.116.176.16:8091/api/status | head -n 5; echo 'body:'; cat /tmp/agents-db-status.out 2>/dev/null","timeout":10}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":484,"output":157,"cacheRead":3456,"cacheWrite":0,"totalTokens":4097,"cost":{"input":0.0012100000000000001,"output":0.002355,"cacheRead":0.000864,"cacheWrite":0,"total":0.004429}},"stopReason":"toolUse","timestamp":1776632929170,"responseId":"resp_071e452a5a0ea02e0169e544616b4481909b2c2c5a3cf3b63d"}}
{"type":"message","id":"d016e960","parentId":"39ac73bc","timestamp":"2026-04-19T21:08:53.135Z","message":{"role":"toolResult","toolCallId":"call_lQmyoj6X8eEDQ56yicGzG7yz|fc_071e452a5a0ea02e0169e544622b588190ace7cf60eb7f9f09","toolName":"bash","content":[{"type":"text","text":"agents-database: curl: (52) Empty reply from server\nbody:\n\n\n[Showing lines 8-10 of 10 (50.0KB limit). Full output: /tmp/pi-bash-44b82cd557fbac62.log]\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776632933134}}
{"type":"message","id":"829c784f","parentId":"d016e960","timestamp":"2026-04-19T21:09:00.999Z","message":{"role":"assistant","content":[{"type":"text","text":"Machine state:\n\n- Host: `ballbox-first`\n- Uptime: `3d 7h`\n- Load: `0.04 0.11 0.24`\n- Systemd: `running`\n- Failed units: none shown\n\nResources:\n- RAM: `7.9Gi total`, `1.9Gi used`, `5.9Gi available`\n- Swap: `492Mi / 2.0Gi`\n- Root `/`: `12G / 14G used` -> `88%`, only `1.6G` free\n- `/mnt/rpi`: `89G / 234G used` -> `39%`\n\nNotable issue:\n- Root disk is tight. Main machine risk right now is `/` at `88%`.\n- `agents-database` status endpoint on `:8091` gave `Empty reply from server`, so that service or its HTTP handling looks unhealthy.\n- The combined status check also failed on the service curl pass, so I’d treat service health as needing a direct check, not green.\n\nIf you want, I can do the next pass:\n1. identify what is filling `/`\n2. check `personal-agent` and `agents-database` services via `systemctl` and logs\n3. give you a short fix plan","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e544682ce0819099acb9f59fb4eaff\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":198,"output":273,"cacheRead":3968,"cacheWrite":0,"totalTokens":4439,"cost":{"input":0.000495,"output":0.004095,"cacheRead":0.000992,"cacheWrite":0,"total":0.005581999999999999}},"stopReason":"stop","timestamp":1776632933135,"responseId":"resp_071e452a5a0ea02e0169e5446579348190bd21df7df293f79e"}}
{"type":"message","id":"8373178a","parentId":"829c784f","timestamp":"2026-04-19T21:09:51.610Z","message":{"role":"user","content":[{"type":"text","text":"do 1 and 2 in subagents"}],"timestamp":1776632991608}}
{"type":"message","id":"9015ecc2","parentId":"8373178a","timestamp":"2026-04-19T21:09:57.794Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_rTOJUdFvSnuXPhm6gx8r4E1S|fc_071e452a5a0ea02e0169e544a0a40881908bd4e3582d24e663","name":"subagent","arguments":{"mode":"parallel","agentScope":"both","confirmProjectAgents":false,"tasks":[{"description":"Disk usage investigator","tools":["bash","read"],"systemPrompt":"You are a focused infra investigator. Keep output terse. Inspect what is filling root filesystem /. Do not modify anything. Return: top space consumers on /, likely safe cleanup targets, and any risks. Use cwd /home/sebas.","task":"Investigate root filesystem usage on this machine. Find the biggest directories/files on /. Stay on the root filesystem only. Do not cross into other mounts. No changes. Return a concise report with exact paths and sizes, likely cleanup candidates, and warnings.","cwd":"/home/sebas"},{"description":"Service health investigator","tools":["bash","read"],"systemPrompt":"You are a focused infra investigator. Keep output terse. Check service health for personal-agent and agents-database. Do not modify anything. Return status, recent errors, listening ports/processes, and likely cause if unhealthy. Use cwd /home/sebas.","task":"Investigate health of personal-agent and agents-database on this machine. Check systemd units, recent logs, process/listen state, and local HTTP behavior for ports 8082 and 8091. No changes. Return a concise report with findings and likely cause.","cwd":"/home/sebas"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":4454,"output":285,"cacheRead":0,"cacheWrite":0,"totalTokens":4739,"cost":{"input":0.011135,"output":0.004275,"cacheRead":0,"cacheWrite":0,"total":0.01541}},"stopReason":"toolUse","timestamp":1776632991610,"responseId":"resp_071e452a5a0ea02e0169e5449fff1081908cc2b83dc7ae13c7"}}
{"type":"message","id":"80cb92b7","parentId":"9015ecc2","timestamp":"2026-04-19T21:10:44.733Z","message":{"role":"toolResult","toolCallId":"call_rTOJUdFvSnuXPhm6gx8r4E1S|fc_071e452a5a0ea02e0169e544a0a40881908bd4e3582d24e663","toolName":"subagent","content":[{"type":"text","text":"Parallel: 2/2 succeeded\n\n[dynamic] completed: Root fs `/` is 88% full: `12G / 14G used`, `1.6G free`.\n\nTop space on root fs only\n- `/usr` — `6.6G`...\n\n[dynamic] completed: Concise health report.\n\n## Summary\n\n- `personal-agent` on `:8082`: partially up from a live orphan/m..."}],"details":{"mode":"parallel","agentScope":"both","projectAgentsDir":null,"results":[{"agent":"dynamic","agentSource":"user","task":"Investigate root filesystem usage on this machine. Find the biggest directories/files on /. Stay on the root filesystem only. Do not cross into other mounts. No changes. Return a concise report with exact paths and sizes, likely cleanup candidates, and warnings.","exitCode":0,"messages":[{"role":"user","content":[{"type":"text","text":"Task: Investigate root filesystem usage on this machine. Find the biggest directories/files on /. Stay on the root filesystem only. Do not cross into other mounts. No changes. Return a concise report with exact paths and sizes, likely cleanup candidates, and warnings."}],"timestamp":1776632999301},{"role":"assistant","content":[{"type":"toolCall","id":"call_Ec39sIKSTuf5Swbe3vOMlzMw|fc_075c1c25b64647680169e544b1a748819380d8e6a27d11ca05","name":"bash","arguments":{"command":"set -o pipefail\nprintf '=== df ===\\n'\ndf -h /\nprintf '\\n=== top_dirs_rootfs ===\\n'\nsudo du -xhd1 / 2>/dev/null | sort -hr | head -n 30\nprintf '\\n=== top_dirs_var ===\\n'\nsudo du -xhd2 /var 2>/dev/null | sort -hr | head -n 40\nprintf '\\n=== top_dirs_usr ===\\n'\nsudo du -xhd2 /usr 2>/dev/null | sort -hr | head -n 40\nprintf '\\n=== top_dirs_home ===\\n'\nsudo du -xhd2 /home 2>/dev/null | sort -hr | head -n 40\nprintf '\\n=== top_files_rootfs ===\\n'\nsudo find / -xdev -type f -printf '%s\\t%p\\n' 2>/dev/null | sort -nr | head -n 60 | awk 'BEGIN{OFS=\"\\t\"} {cmd=\"numfmt --to=iec --suffix=B \" $1; cmd | getline h; close(cmd); print h,$2}'","timeout":120}},{"type":"toolCall","id":"call_5PbaGPpkmS5PCCrxxLJT7C4j|fc_075c1c25b64647680169e544b1a7588193a411e56d66dafd99","name":"bash","arguments":{"command":"set -o pipefail\nprintf '=== apt ===\\n'\n(apt-get -s autoremove 2>/dev/null | sed -n '1,120p') || true\nprintf '\\n=== journal ===\\n'\njournalctl --disk-usage 2>/dev/null || true\nprintf '\\n=== docker ===\\n'\n(docker system df 2>/dev/null || true)\nprintf '\\n=== snap ===\\n'\n(snap list --all 2>/dev/null || true)\nprintf '\\n=== logs_varlog ===\\n'\nsudo du -xhd2 /var/log 2>/dev/null | sort -hr | head -n 40\nprintf '\\n=== cache_varcache ===\\n'\nsudo du -xhd2 /var/cache 2>/dev/null | sort -hr | head -n 40","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2883,"output":488,"cacheRead":0,"cacheWrite":0,"totalTokens":3371,"cost":{"input":0.0072075,"output":0.00732,"cacheRead":0,"cacheWrite":0,"total":0.0145275}},"stopReason":"toolUse","timestamp":1776632999311,"responseId":"resp_075c1c25b64647680169e544a797e481939671f0dcf180b488"},{"role":"toolResult","toolCallId":"call_Ec39sIKSTuf5Swbe3vOMlzMw|fc_075c1c25b64647680169e544b1a748819380d8e6a27d11ca05","toolName":"bash","content":[{"type":"text","text":"=== df ===\nFilesystem      Size  Used Avail Use% Mounted on\n/dev/mmcblk0p2   14G   12G  1.6G  88% /\n\n=== top_dirs_rootfs ===\n12G\t/\n6.6G\t/usr\n2.4G\t/var\n2.2G\t/home\n62M\t/boot\n51M\t/opt\n8.0M\t/etc\n80K\t/root\n16K\t/lost+found\n8.0K\t/mnt\n4.0K\t/srv\n4.0K\t/media\n\n=== top_dirs_var ===\n2.4G\t/var\n230M\t/var/lib\n148M\t/var/lib/apt\n147M\t/var/cache\n140M\t/var/cache/apt\n75M\t/var/lib/dpkg\n4.4M\t/var/cache/debconf\n4.4M\t/var/backups\n4.2M\t/var/lib/aspell\n1.9M\t/var/lib/lightdm\n1.9M\t/var/cache/man\n1.5M\t/var/log\n716K\t/var/lib/systemd\n508K\t/var/cache/fontconfig\n224K\t/var/lib/cloud\n156K\t/var/log/apt\n128K\t/var/log/nginx\n84K\t/var/www\n84K\t/var/cache/ldconfig\n72K\t/var/www/portal\n52K\t/var/lib/tailscale\n44K\t/var/lib/ucf\n44K\t/var/cache/dictionaries-common\n40K\t/var/log/cups\n40K\t/var/lib/ghostscript\n36K\t/var/tmp\n36K\t/var/lib/PackageKit\n36K\t/var/lib/NetworkManager\n32K\t/var/lib/nginx\n32K\t/var/lib/dictionaries-common\n28K\t/var/lib/pam\n28K\t/var/lib/emacsen-common\n24K\t/var/spool\n20K\t/var/lib/xml-core\n20K\t/var/cache/cups\n16K\t/var/log/lightdm\n12K\t/var/spool/cron\n12K\t/var/lib/sgml-base\n12K\t/var/lib/raspberrypi\n12K\t/var/lib/nfs\n\n=== top_dirs_usr ===\n6.6G\t/usr\n4.1G\t/usr/lib\n1.9G\t/usr/lib/aarch64-linux-gnu\n1.5G\t/usr/share\n1.1G\t/usr/lib/python3\n633M\t/usr/bin\n346M\t/usr/share/locale\n250M\t/usr/lib/firefox\n242M\t/usr/lib/firefox-esr\n230M\t/usr/share/doc\n209M\t/usr/lib/firmware\n170M\t/usr/share/go-1.24\n163M\t/usr/include\n109M\t/usr/lib/go-1.24\n106M\t/usr/libexec\n90M\t/usr/libexec/gcc\n80M\t/usr/sbin\n73M\t/usr/share/rpd-wallpaper\n67M\t/usr/include/node\n66M\t/usr/src\n64M\t/usr/share/userguide\n63M\t/usr/lib/libtorch-test\n60M\t/usr/src/linux-headers-6.12.47+rpt-common-rpi\n58M\t/usr/lib/modules\n53M\t/usr/lib/python3.13\n52M\t/usr/share/fonts\n41M\t/usr/include/ATen\n39M\t/usr/share/unicode\n37M\t/usr/share/pocketsphinx\n37M\t/usr/share/man\n35M\t/usr/share/icons\n32M\t/usr/share/python-babel-localedata\n30M\t/usr/share/help\n28M\t/usr/local/bin\n28M\t/usr/local\n25M\t/usr/lib/udev\n25M\t/usr/lib/git-core\n24M\t/usr/share/proj\n24M\t/usr/lib/gcc\n23M\t/usr/share/perl\n\n=== top_dirs_home ===\n2.2G\t/home\n2.0G\t/home/sebas\n990M\t/home/sebas/.cache\n284M\t/home/sebas/.local\n194M\t/home/sebas/.opencode\n188M\t/home/linuxbrew/.linuxbrew\n188M\t/home/linuxbrew\n176M\t/home/sebas/.npm-global\n85M\t/home/sebas/.bun\n59M\t/home/sebas/downloads\n58M\t/home/sebas/.config\n55M\t/home/sebas/venvs\n40M\t/home/sebas/telegram-bot-listener-backup-20260118\n17M\t/home/sebas/.pnpm-store\n7.5M\t/home/sebas/.claude\n4.8M\t/home/sebas/.pi\n4.2M\t/home/sebas/eiffel-monitor\n4.2M\t/home/sebas/.codex\n1.3M\t/home/sebas/bug-bounty\n836K\t/home/sebas/health-system\n76K\t/home/sebas/.pki\n72K\t/home/sebas/.agents\n20K\t/home/sebas/ops-notes\n16K\t/home/sebas/.ssh\n8.0K\t/home/sebas/scripts\n8.0K\t/home/sebas/.mozilla\n8.0K\t/home/sebas/logs\n8.0K\t/home/sebas/.ansible\n4.0K\t/home/sebas/Videos\n4.0K\t/home/sebas/Templates\n4.0K\t/home/sebas/Public\n4.0K\t/home/sebas/Pictures\n4.0K\t/home/sebas/Music\n4.0K\t/home/sebas/go\n4.0K\t/home/sebas/Downloads\n4.0K\t/home/sebas/Documents\n4.0K\t/home/sebas/Desktop\n\n=== top_files_rootfs ===\n2.0GB\t/var/swap\n428MB\t/home/sebas/.cache/ms-playwright/chromium-1208/chrome-linux/chrome\n275MB\t/home/sebas/.cache/ms-playwright/chromium_headless_shell-1208/chrome-linux/headless_shell\n205MB\t/usr/lib/aarch64-linux-gnu/libtorch_cpu.so.2.6.0\n204MB\t/home/sebas/.local/share/claude/versions/2.1.7\n151MB\t/usr/lib/firefox/libxul.so\n146MB\t/usr/lib/firefox-esr/libxul.so\n136MB\t/home/sebas/.opencode/bin/opencode\n118MB\t/usr/lib/aarch64-linux-gnu/libLLVM.so.19.1\n116MB\t/usr/bin/node\n114MB\t/usr/lib/aarch64-linux-gnu/libLLVM-17.so.1\n111MB\t/usr/lib/aarch64-linux-gnu/libWPEWebKit-2.0.so.1.5.8\n106MB\t/home/linuxbrew/.linuxbrew/Homebrew/.git/objects/pack/pack-1540c407979cc71a1aa54635c125960c5bf99a62.pack\n66MB\t/var/cache/apt/pkgcache.bin\n66MB\t/var/cache/apt/srcpkgcache.bin\n64MB\t/usr/share/userguide/The_Official_Raspberry_Pi_Beginners_Guide_5th_Edition.pdf\n60MB\t/usr/lib/aarch64-linux-gnu/libamd_comgr.so.2.6.0\n54MB\t/var/lib/apt/lists/deb.debian.org_debian_dists_trixie_main_binary-arm64_Packages\n54MB\t/usr/bin/rclone\n51MB\t/var/lib/apt/lists/deb.debian.org_debian_dists_trixie_main_binary-armhf_Packages\n50MB\t/home/sebas/.local/share/opencode/opencode.db\n44MB\t/usr/lib/firefox-esr/browser/omni.ja\n43MB\t/usr/lib/firefox/browser/omni.ja\n39MB\t/usr/lib/firefox/omni.ja\n37MB\t/usr/bin/rpi-imager\n36MB\t/usr/lib/firefox-esr/omni.ja\n35MB\t/usr/sbin/tailscaled\n34MB\t/usr/bin/gh\n34MB\t/usr/lib/aarch64-linux-gnu/libgallium-25.0.7-2+rpt3.so\n34MB\t/var/lib/apt/lists/deb.debian.org_debian_dists_trixie_main_i18n_Translation-en\n32MB\t/usr/libexec/gcc/aarch64-linux-gnu/14/cc1plus\n31MB\t/usr/lib/aarch64-linux-gnu/libicudata.so.76.1\n31MB\t/opt/player/videos/channel-1/jellyfish.mp4\n30MB\t/usr/libexec/gcc/aarch64-linux-gnu/14/cc1\n29MB\t/usr/lib/python3/dist-packages/3204bda914b7f2c6f497__mypyc.cpython-313-aarch64-linux-gnu.so\n29MB\t/usr/bin/aarch64-linux-gnu-lto-dump-14\n28MB\t/usr/libexec/gcc/aarch64-linux-gnu/14/lto1\n28MB\t/usr/local/bin/gog\n26MB\t/usr/lib/aarch64-linux-gnu/libgdal.so.36.3.10.3\n26MB\t/usr/share/pocketsphinx/model/en-us/en-us.lm.bin\n26MB\t/usr/lib/aarch64-linux-gnu/libz3.so.4\n24MB\t/usr/lib/aarch64-linux-gnu/libamdhip64.so.5.7.31921\n24MB\t/usr/lib/aarch64-linux-gnu/libdnnl.so.3.7\n24MB\t/usr/bin/tailscale\n23MB\t/home/sebas/.cache/ms-playwright/chromium_headless_shell-1208/chrome-linux/libvk_swiftshader.so\n23MB\t/home/sebas/.cache/ms-playwright/chromium-1208/chrome-linux/libvk_swiftshader.so\n22MB\t/boot/initrd.img-6.12.47+rpt-rpi-v8\n22MB\t/boot/initrd.img-6.12.47+rpt-rpi-2712\n22MB\t/usr/lib/aarch64-linux-gnu/libgs.so.10.05\n19MB\t/usr/bin/sq\n18MB\t/usr/lib/aarch64-linux-gnu/libtorch_python.so.2.6.0\n18MB\t/usr/lib/go-1.24/pkg/tool/linux_arm64/compile\n17MB\t/home/linuxbrew/.linuxbrew/Homebrew/Library/Homebrew/vendor/portable-ruby/3.4.8/bin/ruby\n17MB\t/usr/bin/squeekboard\n17MB\t/usr/lib/aarch64-linux-gnu/libcodec2.so.1.2\n17MB\t/usr/lib/python3/dist-packages/awscli/data/ac.index\n15MB\t/usr/share/rpd-wallpaper/mist.jpg\n15MB\t/usr/lib/aarch64-linux-gnu/libvulkan_nouveau.so\n14MB\t/usr/lib/aarch64-linux-gnu/libonnxruntime.so.1.21.0\n14MB\t/usr/lib/aarch64-linux-gnu/libavcodec.so.61.19.101\n\n\nCommand exited with code 141"}],"details":{},"isError":true,"timestamp":1776633022472},{"role":"toolResult","toolCallId":"call_5PbaGPpkmS5PCCrxxLJT7C4j|fc_075c1c25b64647680169e544b1a7588193a411e56d66dafd99","toolName":"bash","content":[{"type":"text","text":"=== apt ===\nNOTE: This is only a simulation!\n      apt-get needs root privileges for real execution.\n      Keep also in mind that locking is deactivated,\n      so don't depend on the relevance to the real current situation!\nReading package lists...\nBuilding dependency tree...\nReading state information...\n0 upgraded, 0 newly installed, 0 to remove and 279 not upgraded.\n\n=== journal ===\nArchived and active journals take up 151.6M in the file system.\n\n=== docker ===\n\n=== snap ===\n\n=== logs_varlog ===\n1.5M\t/var/log\n156K\t/var/log/apt\n128K\t/var/log/nginx\n40K\t/var/log/cups\n16K\t/var/log/lightdm\n8.0K\t/var/log/runit\n8.0K\t/var/log/hp\n4.0K\t/var/log/runit/ssh\n4.0K\t/var/log/private\n4.0K\t/var/log/journal\n4.0K\t/var/log/hp/tmp\n\n=== cache_varcache ===\n147M\t/var/cache\n140M\t/var/cache/apt\n9.0M\t/var/cache/apt/archives\n4.4M\t/var/cache/debconf\n1.9M\t/var/cache/man\n508K\t/var/cache/fontconfig\n84K\t/var/cache/ldconfig\n52K\t/var/cache/man/fr\n52K\t/var/cache/man/de\n48K\t/var/cache/man/pt\n44K\t/var/cache/dictionaries-common\n32K\t/var/cache/man/sv\n32K\t/var/cache/man/nl\n28K\t/var/cache/man/uk\n28K\t/var/cache/man/ru\n28K\t/var/cache/man/ro\n28K\t/var/cache/man/pt_BR\n28K\t/var/cache/man/pl\n28K\t/var/cache/man/ja\n28K\t/var/cache/man/it\n28K\t/var/cache/man/es\n24K\t/var/cache/man/zh_TW\n24K\t/var/cache/man/zh_CN\n24K\t/var/cache/man/tr\n24K\t/var/cache/man/sr\n24K\t/var/cache/man/sl\n24K\t/var/cache/man/nb\n24K\t/var/cache/man/ko\n24K\t/var/cache/man/id\n24K\t/var/cache/man/hu\n24K\t/var/cache/man/hr\n24K\t/var/cache/man/fr.UTF-8\n24K\t/var/cache/man/fr.ISO8859-1\n24K\t/var/cache/man/fi\n24K\t/var/cache/man/da\n24K\t/var/cache/man/cs\n24K\t/var/cache/man/ca\n24K\t/var/cache/man/bg\n24K\t/var/cache/man/be\n20K\t/var/cache/cups\n"}],"isError":false,"timestamp":1776633022472},{"role":"assistant","content":[{"type":"text","text":"Root fs `/` is 88% full: `12G / 14G used`, `1.6G free`.\n\nTop space on root fs only\n- `/usr` — `6.6G`\n- `/var` — `2.4G`\n- `/home` — `2.2G`\n- `/boot` — `62M`\n- `/opt` — `51M`\n\nBiggest dirs/files found on `/` without crossing mounts\n\nTop dirs\n- `/usr/lib` — `4.1G`\n- `/usr/share` — `1.5G`\n- `/usr/lib/aarch64-linux-gnu` — `1.9G`\n- `/usr/lib/python3` — `1.1G`\n- `/home/sebas` — `2.0G`\n- `/home/sebas/.cache` — `990M`\n- `/home/sebas/.local` — `284M`\n- `/home/sebas/.opencode` — `194M`\n- `/home/linuxbrew/.linuxbrew` — `188M`\n- `/home/sebas/.npm-global` — `176M`\n- `/var/lib` — `230M`\n- `/var/lib/apt` — `148M`\n- `/var/cache` — `147M`\n- `/var/cache/apt` — `140M`\n- `/var/log` — `1.5M`\n\nTop files\n- `/var/swap` — `2.0G`\n- `/home/sebas/.cache/ms-playwright/chromium-1208/chrome-linux/chrome` — `428M`\n- `/home/sebas/.cache/ms-playwright/chromium_headless_shell-1208/chrome-linux/headless_shell` — `275M`\n- `/usr/lib/aarch64-linux-gnu/libtorch_cpu.so.2.6.0` — `205M`\n- `/home/sebas/.local/share/claude/versions/2.1.7` — `204M`\n- `/usr/lib/firefox/libxul.so` — `151M`\n- `/usr/lib/firefox-esr/libxul.so` — `146M`\n- `/home/sebas/.opencode/bin/opencode` — `136M`\n- `/usr/bin/node` — `116M`\n- `/home/linuxbrew/.linuxbrew/Homebrew/.git/objects/pack/pack-1540c407979cc71a1aa54635c125960c5bf99a62.pack` — `106M`\n- `/var/cache/apt/pkgcache.bin` — `66M`\n- `/var/cache/apt/srcpkgcache.bin` — `66M`\n- `/var/lib/apt/lists/deb.debian.org_debian_dists_trixie_main_binary-arm64_Packages` — `54M`\n- `/var/lib/apt/lists/deb.debian.org_debian_dists_trixie_main_binary-armhf_Packages` — `51M`\n- `/home/sebas/.local/share/opencode/opencode.db` — `50M`\n\nLikely cleanup targets\n- Playwright browser cache:\n  - `/home/sebas/.cache/ms-playwright` — at least `~726M` from the two big binaries alone\n- User cache in general:\n  - `/home/sebas/.cache` — `990M`\n- APT metadata/cache:\n  - `/var/cache/apt` — `140M`\n  - `/var/lib/apt/lists` contents include `54M`, `51M`, `34M` files\n- Old tool/runtime payloads if unused:\n  - `/home/sebas/.local/share/claude/versions/2.1.7` — `204M`\n  - `/home/linuxbrew/.linuxbrew` — `188M`\n  - `/home/sebas/.npm-global` — `176M`\n  - `/home/sebas/.opencode` — `194M`\n\nWarnings / risks\n- Biggest single item is `/var/swap` at `2.0G`. Do not remove casually. Risk: memory pressure, instability, crashes.\n- `/usr` is the main consumer. Most of that is installed system packages/libs, not safe manual-delete territory.\n- Both `/usr/lib/firefox` and `/usr/lib/firefox-esr` exist. If both browsers are installed intentionally, leave them. If one is obsolete, reclaim could be meaningful, but only via package manager.\n- `journalctl --disk-usage`: journals use `151.6M`. Not huge, but nontrivial.\n- `/opt` is small overall, but contains `/opt/player/videos/channel-1/jellyfish.mp4` — `31M`.\n- No sign of Docker or Snap bloat here.\n- Logs are not the problem: `/var/log` is only `1.5M`.\n\nBest reclaim first, low risk\n1. `/home/sebas/.cache`\n2. `/home/sebas/.cache/ms-playwright`\n3. `/var/cache/apt` and stale APT lists\n4. Unused user-space tool installs under `/home/sebas/.local`, `/home/sebas/.opencode`, `/home/linuxbrew/.linuxbrew`\n\nIf you want, I can do a second pass that ranks cleanup actions by expected freed space vs risk, still without changing anything.","textSignature":"{\"v\":1,\"id\":\"msg_075c1c25b64647680169e544c00d5881938f04f60046df9c2f\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":3240,"output":1116,"cacheRead":3200,"cacheWrite":0,"totalTokens":7556,"cost":{"input":0.008100000000000001,"output":0.01674,"cacheRead":0.0007999999999999999,"cacheWrite":0,"total":0.02564}},"stopReason":"stop","timestamp":1776633022473,"responseId":"resp_075c1c25b64647680169e544bf40588193ad22e93d1e321db5"}],"stderr":"","usage":{"input":6123,"output":1604,"cacheRead":3200,"cacheWrite":0,"cost":0.0401675,"contextTokens":7556,"turns":2},"model":"gpt-5.4","stopReason":"stop"},{"agent":"dynamic","agentSource":"user","task":"Investigate health of personal-agent and agents-database on this machine. Check systemd units, recent logs, process/listen state, and local HTTP behavior for ports 8082 and 8091. No changes. Return a concise report with findings and likely cause.","exitCode":0,"messages":[{"role":"user","content":[{"type":"text","text":"Task: Investigate health of personal-agent and agents-database on this machine. Check systemd units, recent logs, process/listen state, and local HTTP behavior for ports 8082 and 8091. No changes. Return a concise report with findings and likely cause."}],"timestamp":1776632999260},{"role":"assistant","content":[{"type":"toolCall","id":"call_6JKt5WP8uUVfbMBBaVJJ9cVw|fc_037559ed605dbf880169e544b079d08196a7d26db5d6e98ae2","name":"bash","arguments":{"command":"set -o pipefail\nprintf '== status endpoints ==\\n'\nfor u in http://127.0.0.1:8082/api/status http://127.0.0.1:8091/api/status; do echo \"-- $u\"; curl -sS -D - --max-time 5 \"$u\" -o /tmp/resp.$$ || true; echo; [ -f /tmp/resp.$$ ] && cat /tmp/resp.$$; echo; rm -f /tmp/resp.$$; done\nprintf '\\n== systemd units ==\\n'\nsystemctl --no-pager --full status personal-agent.service agents-database.service || true\nprintf '\\n== recent journal personal-agent ==\\n'\njournalctl -u personal-agent.service -n 120 --no-pager || true\nprintf '\\n== recent journal agents-database ==\\n'\njournalctl -u agents-database.service -n 120 --no-pager || true","timeout":25}},{"type":"toolCall","id":"call_bzaBk4FvQAwAtP7Nc5tsPjpZ|fc_037559ed605dbf880169e544b079e0819692f94f85791fe865","name":"bash","arguments":{"command":"set -o pipefail\nprintf '== listening sockets 8082/8091 ==\\n'\nss -ltnp '( sport = :8082 or sport = :8091 )' || true\nprintf '\\n== processes matching services ==\\n'\nps -ef | rg -i 'personal-agent|agents-database|uvicorn|gunicorn|node|python' || true\nprintf '\\n== local http probes verbose ==\\n'\nfor p in 8082 8091; do echo \"-- port $p /\"; curl -sv --max-time 5 \"http://127.0.0.1:$p/\" -o /dev/null 2>&1 || true; echo; echo \"-- port $p /api/status\"; curl -sv --max-time 5 \"http://127.0.0.1:$p/api/status\" -o /dev/null 2>&1 || true; echo; done","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2891,"output":463,"cacheRead":0,"cacheWrite":0,"totalTokens":3354,"cost":{"input":0.0072275,"output":0.006945,"cacheRead":0,"cacheWrite":0,"total":0.014172500000000001}},"stopReason":"toolUse","timestamp":1776632999268,"responseId":"resp_037559ed605dbf880169e544a7938c8196acc1321d4adad812"},{"role":"toolResult","toolCallId":"call_6JKt5WP8uUVfbMBBaVJJ9cVw|fc_037559ed605dbf880169e544b079d08196a7d26db5d6e98ae2","toolName":"bash","content":[{"type":"text","text":"5)[S16](#ref-s16)\\n3. La company esta empujando una evolucion desde \\\"trainer booking\\\" a \\\"sport commerce OS ligero\\\": storefront, widget, apps, credits, courses, integrations, manager. [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)[S17](#ref-s17)[S18](#ref-s18)\\n4. El posicionamiento geografico/publico es multi-country, pero la fuerza de las integraciones y ejemplos visibles sesga hacia Europa y racquet/federation ecosystems. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n## Riesgos, limites y lectura critica\\n\\n- Parte del marketplace publico devuelve `0 results` sin contexto o depende de query/location; por tanto el mapeo se centra en capacidades de producto confirmadas, no en catalogo disponible en cada region. [S20](#ref-s20)[S21](#ref-s21)\\n- Hay copy inconsistente entre pricing y help center/app release notes sobre courses, credits e insights. No conviene asumir rollout uniforme por cliente/mercado. [S3](#ref-s3)[S11](#ref-s11)[S17](#ref-s17)\\n- La profundidad del BI/reporting no es visible publicamente; \\\"insights\\\" aparece, pero sin detalle funcional verificable. [S3](#ref-s3)\\n- La integracion de Google Calendar se describe como two-way en marketing, pero el help publico solo verifica una integracion via URL/ICS; tratar la sincronizacion bidireccional exacta como probable pero no cerrada. [S13](#ref-s13)[S11](#ref-s11)\\n- No pude verificar exhaustivamente todas las venue pages publicas desde muestra puntual; algunas URLs del sitemap no devolvieron contenido util. [S20](#ref-s20)\\n\\n## Fuentes primarias usadas\\n\\n- [S1] Matchable consumer homepage: https://www.matchable.io/\\n- [S2] Matchable business homepage: https://business.matchable.io/\\n- [S3] Matchable pricing: https://matchable.io/business/pricing\\n- [S4] Matchable integrations overview: https://matchable.io/business/integrations\\n- [S5] Matchable help center index: https://help.matchable.io/en/\\n- [S6] How to book a training: https://help.matchable.io/en/articles/10-how-to-book-a-training\\n- [S7] Client app / credits / FAQ / invoices help pages: https://help.matchable.io/en/articles/15-client-app-iosandroid ; https://help.matchable.io/en/articles/23-how-to-use-credits ; https://help.matchable.io/en/articles/12-faq ; https://help.matchable.io/en/articles/39-invoice-for-my-purchases\\n- [S8] Quick-start manager setup pages: https://help.matchable.io/en/articles/1-add-a-payment-method ; https://help.matchable.io/en/articles/2-create-your-first-class-or-event ; https://help.matchable.io/en/articles/3-create-your-first-private-service ; https://help.matchable.io/en/articles/4-how-to-edit-your-trainer-profile ; https://help.matchable.io/en/articles/5-how-to-edit-your-venue-profile ; https://help.matchable.io/en/articles/6-edit-your-availability ; https://help.matchable.io/en/articles/7-add-your-venue-schedule\\n- [S9] Manager operations pages: https://help.matchable.io/en/articles/17-manage-trainings-and-classes ; https://help.matchable.io/en/articles/18-manage-your-trainers-schedules ; https://help.matchable.io/en/articles/19-manage-your-clients ; https://help.matchable.io/en/articles/22-manage-credits\\n- [S10] Storefront guide: https://help.matchable.io/en/articles/38-getting-started-with-your-storefront\\n- [S11] Courses + trainer app help pages: https://help.matchable.io/en/articles/13-getting-started-with-the-matchable-trainer-app ; https://help.matchable.io/en/articles/14-adding-and-managing-your-holidays ; https://help.matchable.io/en/articles/41-getting-started-with-courses ; https://help.matchable.io/en/articles/42-smart-courses-feature ; https://help.matchable.io/en/articles/43-set-up-a-course-page-template ; https://help.matchable.io/en/articles/44-create-and-manage-your-course-schedule ; https://help.matchable.io/en/articles/45-viewing-courses-in-the-calendar ; https://help.matchable.io/en/articles/46-manage-course-participants\\n- [S12] MATCHi integration: https://matchable.io/business/integration/matchi\\n- [S13] Google Calendar integration: https://matchable.io/business/integration/google-calendar\\n- [S14] Google Meet integration: https://matchable.io/business/integration/google-meet\\n- [S15] Matchpoint integration: https://matchable.io/business/integration/matchpoint\\n- [S16] KNLTB Meet & Play integration: https://matchable.io/business/integration/knltb-meet-play\\n- [S17] Client app store pages / release notes: https://apps.apple.com/nl/app/matchable-book-your-training/id6742325816 ; https://play.google.com/store/apps/details?id=com.getmatchable.client\\n- [S18] Trainer app store pages / release notes: https://apps.apple.com/nl/app/matchable-for-trainers/id6468798694 ; https://play.google.com/store/apps/details?id=com.getmatchable.app\\n- [S19] Sample trainer page: https://matchable.io/trainers/alex-hosp\\n- [S20] Matchable sitemap: https://matchable.io/sitemap.xml\\n- [S21] Explore / Activities public pages: https://matchable.io/explore ; https://matchable.io/activities\\n\\n\\n- [S22] Spec Ballbox \\u00d7 ATC: secci\\u00f3n 16 de este documento (Spec de integraci\\u00f3n para copiar patr\\u00f3n MATCHi/Matchpoint/KNLTB en Ballbox)\\n\\n## Ballbox \\u00d7 ATC \\u2014 Spec de Integraci\\u00f3n\\n\\n*Spec de integraci\\u00f3n para copiar el patr\\u00f3n de MATCHi/Matchpoint/KNLTB en Ballbox.*\\n\\n---\\n\\n### 1. Contexto de negocio\\n\\n**Problema que resuelve**\\n\\nUn club de tennis/padel usa ATC como su sistema de gesti\\u00f3n de canchas (reservas, pagos, inventario). Ballbox quiere vender trainings y clases de sus trainers en ese club. El riesgo es vender un entrenamiento cuando la cancha no est\\u00e1 disponible, o duplicar reservas.\\n\\n**Soluci\\u00f3n**\\n\\nCuando alguien reserva un training en Ballbox, el sistema autom\\u00e1ticamente verifica disponibilidad y reserva la cancha en ATC al mismo tiempo. Si el club cancela o modifica la reserva en ATC, Ballbox se entera y act\\u00faa en consecuencia.\\n\\n**Modelo de relaci\\u00f3n**\\n\\n- ATC es el **source of truth** para inventario de canchas\\n- Ballbox es el **canal de venta** de trainings\\n- Ambas plataformas mantienen sync en tiempo real\\n\\n---\\n\\n### 2. Descripci\\u00f3n funcional del flujo\\n\\n#### 2.1. Un cliente busca un entrenamiento\\n\\nEl cliente ve en Ballbox los trainers disponibles de un club. Al seleccionar fecha y horario, Ballbox consulta a ATC qu\\u00e9 canchas est\\u00e1n libres en ese momento. Solo muestra opciones disponibles.\\n\\n#### 2.2. El cliente confirma la reserva\\n\\nCuando el cliente paga o confirma el training en Ballbox:\\n1. Ballbox registra la reserva del training para el trainer\\n2. Simult\\u00e1neamente, Ballbox reserva la cancha en ATC para ese horario\\n3. Ambas reservas quedan linkeadas por un identificador compartido\\n4. Si la cancha no se puede reservar (ya se ocup\\u00f3 entre consulta y confirmaci\\u00f3n), Ballbox informa al cliente y sugiere otro horario\\n\\n#### 2.3. El cliente o el trainer cancela desde Ballbox\\n\\nBallbox cancela la reserva del training y, al mismo tiempo, libera la cancha en ATC.\\n\\n#### 2.4. El club cancela o modifica la reserva desde ATC\\n\\nATC notifica a Ballbox del cambio. Ballbox:\\n- Informa al cliente/trainer\\n- Ofrece reagendar o cancelar sin costo\\n- Marca la reserva como afectada\\n\\n#### 2.5. El club tiene la cancha indisponible (mantenimiento, evento)\\n\\nATC informa a Ballbox. Ballbox marca esas horas como no disponibles para nuevos bookings de trainings.\\n\\n---\\n\\n### 3. Escenarios soportados\\n\\n| Escenario | Comportamiento |\\n|-----------|----------------|\\n| Training reservado en Ballbox, club cierra la cancha | Ballbox notifica al cliente, ofrece reagendar |\\n| Trainer cancela training en Ballbox | La cancha se libera en ATC autom\\u00e1ticamente |\\n| Cliente reserva training, la cancha se ocupa antes de confirmar | Ballbox muestra horarios alternativos |\\n| Ballbox cae durante la reserva | La transacci\\u00f3n se deshace; la cancha en ATC no queda reservada |\\n| ATC tiene mantenimiento | Ballbox lo detecta y muestra \\\"canchas temporalmente no disponibles\\\" |\\n\\n---\\n\\n### 4. Definici\\u00f3n de responsabilidades\\n\\n**Ballbox se encarga de:**\\n- Mostrar la oferta de trainings y trainers\\n- Gestionar el checkout, pago y comunicaci\\u00f3n con el cliente\\n- Mantener el estado del training (confirmado, cancelado, reagendado)\\n- Notificar al cliente ante cambios en disponibilidad de cancha\\n- Persistir la referencia cruzada entre booking de training y booking de cancha\\n\\n**ATC se encarga de:**\\n- Mantener el inventario actualizado de canchas por club\\n- Gestionar reservas de cancha (crear, cancelar, consultar disponibilidad)\\n- Procesar pagos de alquiler de canasta si aplica\\n- Notificar a Ballbox ante cambios en reservas de cancha realizados fuera de Ballbox\\n- Proveer soporte t\\u00e9cnico para la integraci\\u00f3n\\n\\n---\\n\\n### 5. Especificaci\\u00f3n t\\u00e9cnica\\n\\n*Requiere que ATC expose los siguientes endpoints (si no existen, se arman en coordinaci\\u00f3n con ATC).*\\n\\n#### 5.1. Consultar disponibilidad\\n\\n```\\nGET /api/v1/clubs/{club_id}/availability?sport={sport}&date={YYYY-MM-DD}\\n\\nRespuesta:\\n{\\n  \\\"date\\\": \\\"2026-03-25\\\",\\n  \\\"slots\\\": [\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"court_name\\\": \\\"Cancha 1\\\",\\n      \\\"time\\\": \\\"14:00\\\",\\n      \\\"duration_minutes\\\": 60,\\n      \\\"available\\\": true\\n    },\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"time\\\": \\\"15:00\\\",\\n      \\\"available\\\": false,\\n      \\\"reason\\\": \\\"booked\\\"\\n    }\\n  ]\\n}\\n```\\n\\n#### 5.2. Reservar cancha\\n\\n```\\nPOST /api/v1/bookings\\n{\\n  \\\"club_id\\\": \\\"club-123\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\",\\n  \\\"duration_minutes\\\": 60,\\n  \\\"client_name\\\": \\\"Juan P\\u00e9rez\\\",\\n  \\\"client_phone\\\": \\\"+5491112345678\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"notes\\\": \\\"Training Ballbox\\\"\\n}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\",\\n  \\\"court\\\": \\\"Cancha 1\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.3. Cancelar reserva de cancha\\n\\n```\\nDELETE /api/v1/bookings/{atc_booking_id}?reason={reason}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"cancelled\\\"\\n}\\n```\\n\\n#### 5.4. Consultar estado de una reserva\\n\\n```\\nGET /api/v1/bookings/{atc_booking_id}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\" | \\\"cancelled\\\" | \\\"completed\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.5. Webhook \\u2014 Notificaciones desde ATC\\n\\nBallbox expone un endpoint que ATC llama ante cambios:\\n\\n```\\nPOST /ballbox/webhooks/atc\\n\\nPayload:\\n{\\n  \\\"event\\\": \\\"booking_cancelled\\\" | \\\"court_unavailable\\\" | \\\"maintenance\\\",\\n  \\\"atc_booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"reason\\\": \\\"club_cancelled\\\" | \\\"court_blocked\\\",\\n  \\\"affected_slots\\\": [\\\"2026-03-25T14:00:00\\\"]\\n}\\n```\\n\\nBallbox responde con `200 OK` y procesa el evento.\\n\\n#### 5.6. Autenticaci\\u00f3n\\n\\n- ATC provee `api_key` por club\\n- Ballbox env\\u00eda `Authorization: Bearer {api_key}` en cada request\\n- Ballbox expone webhook con firma HMAC para verificar origen\\n\\n---\\n\\n### 6. Configuraci\\u00f3n por club\\n\\nPara activar la integraci\\u00f3n, cada club configura en Ballbox:\\n\\n| Campo | Descripci\\u00f3n |\\n|-------|-------------|\\n| `atc_club_id` | Identificador del club en ATC |\\n| `atc_api_key` | Clave de API entregada por ATC |\\n| `sports_enabled` | Lista de deportes habilitados (tennis, padel, etc.) |\\n| `default_duration_minutes` | Duraci\\u00f3n por defecto de un training |\\n\\n---\\n\\n### 7. Roadmap de implementaci\\u00f3n sugerida\\n\\n**Fase 1 \\u2014 MVP (4-6 semanas)**\\n- Disponibilidad consulta\\n- Reserva de cancha\\n- Cancelaci\\u00f3n desde Ballbox\\n- Sincronizaci\\u00f3n unidireccional (Ballbox \\u2192 ATC)\\n\\n**Fase 2 \\u2014 Bidireccional (2-3 semanas)**\\n- Webhooks desde ATC\\n- Notificaciones al cliente\\n- Manejo de cancelaciones externas\\n\\n**Fase 3 \\u2014 Robustez (2 semanas)**\\n- Retry con backoff ante fallos de ATC\\n- Cola de sincronizaci\\u00f3n para fallos\\n- Panel de estado de integraci\\u00f3n por club\\n\\n---\\n\\n*Spec elaborado el 24 de marzo de 2026, basado en el patr\\u00f3n de integraci\\u00f3n de Matchable con MATCHi/Matchpoint/KNLTB.*\\n\\n## Fecha de corte\\n\\nInvestigacion basada en fuentes publicas verificadas disponibles el 24 de marzo de 2026.\\n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"created_at\": \"2026-03-24T14:26:24.158968+00:00\", \"updated_at\": \"2026-03-24T15:39:47.195210+00:00\", \"metadata\": {\"report_type\": \"feature-use-case-map\", \"run_id\": \"a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"topic\": \"matchable\"}, \"task_title\": \"Matchable: mapa exhaustivo de features y use cases\", \"task_status\": \"done\"}, {\"id\": \"art_smoke_markdown_file_links\", \"task_id\": \"task_smoke_markdown_file_links\", \"artifact_type\": \"report\", \"title\": \"smoke markdown file links\", \"content\": \"[tmp](personal-agent-markdown-link-test.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:smoke\", \"created_at\": \"2026-03-17T21:11:26.188844+00:00\", \"updated_at\": \"2026-03-17T21:11:26.188844+00:00\", \"metadata\": {\"cwd\": \"/tmp\"}, \"task_title\": \"smoke markdown file links\", \"task_status\": \"completed\"}, {\"id\": \"art_5e03c108db5345269e77d02e21d07dd9\", \"task_id\": \"task_84da4829fdea45728971df65c57ff33f\", \"artifact_type\": \"report\", \"title\": \"Codex result for Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"content\": \"Hi Sebas. Kept it tight.\\n\\nDocumented current live flow in [docs/raycast-codex-notify.md](/Users/sebas/personal-agent/docs/raycast-codex-notify.md). It captures the actual implementation split between `~/.codex/hooks/notify_macos.sh` and `~/Code/raycast-codex-reply`, including:\\n\\n- notify hook decision path\\n- rollout-message recovery from `~/.codex/state_5.sqlite`\\n- Raycast reply bridge files + deeplinks\\n- approval watcher flow\\n- fallback AppleScript dialog\\n- explicit note that `personal-agent`\\u2019s old blocker/reply path is removed, so this is not handled by the current runtime\\n\\nAdded a README pointer at [README.md](/Users/sebas/personal-agent/README.md).\\n\\nVerification: `./scripts/run-checks.sh` passed.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:12:31.505135+00:00\", \"updated_at\": \"2026-03-17T02:12:31.505135+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"~/.codex/hooks/notify_macos.sh\", \"~/.codex/state_5.sqlite\", \"~/Code/raycast-codex-reply\"]}, \"run_id\": \"run_9f50b4d09e5842498c055923a851c678\"}, \"task_title\": \"Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"task_status\": \"completed\"}, {\"id\": \"art_d69dff710f97429882a05b0ec979ac5b\", \"task_id\": \"task_be1a1e514a7d43d1b59009ccca9fb57c\", \"artifact_type\": \"report\", \"title\": \"Codex result for Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"content\": \"Hi. Legacy seam closed.\\n\\nCanonical shared-memory model now drives personal-agent surfaces from [shared_memory.py](/Users/sebas/personal-agent/personal_agent/shared_memory.py), with `personal-agent-memory-v1` and `personal-agent-task-v1` helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires `approvals resolve` back into the CLI. [migration.py](/Users/sebas/personal-agent/personal_agent/migration.py) now runs real migration work instead of no-op, and [README.md](/Users/sebas/personal-agent/README.md) reflects the new model.\\n\\nCoverage added in [tests/test_personal.py](/Users/sebas/personal-agent/tests/test_personal.py) for canonical research records, native approval lifecycle, and legacy migration behavior. Verified with `./scripts/run-checks.sh` and `git diff --check`; both passed. No daemon/UI smoke run.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:02:06.161088+00:00\", \"updated_at\": \"2026-03-17T02:02:06.161088+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\" helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires \", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_b694a238b532454bb547c056246a31fd\"}, \"task_title\": \"Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"task_status\": \"completed\"}, {\"id\": \"art_b4f5386484794717b0ddc4c42c265319\", \"task_id\": \"task_871c609196b94132aa686188007f6dea\", \"artifact_type\": \"report\", \"title\": \"Codex result for Consolidate all Ballbox payment-system work from demo validation through production readiness and go-live certification.\", \"content\": \"Consolidated into one active workflow.\\n\\nCreated local repo mapping in [.agents/local-config.json](/Users/sebas/Code/ai-dev-workflow/.agents/local-config.json), set current feature in [.agents/current-feature](/Users/sebas/Code/ai-dev-workflow/.agents/current-feature), and wrote the active feature context in [.agents/feature-contexts/ballbox-payment-system-prod-readiness.json](/Users/sebas/Code/ai-dev-workflow/.agents/feature-contexts/ballbox-payment-system-prod-readiness.json). Added the execution brief/checklist in [docs/ballbox-payment-system-consolidation.md](/Users/sebas/Code/ai-dev-workflow/docs/ballbox-payment-system-consolidation.md).\\n\\nKey consolidation outcome: `ballbox` is stable/demo-facing only; `ballbox-payment-integration` is the real workstream. Demo validation exists now. Production hardening is partially drafted but unstaged in backend. Go-live certification is still blocked by two real gaps: missing TCN/Yunshu live adapter contract, and unvalidated MercadoPago real QR flow.\\n\\nVerification: JSON valid. Shared-memory sync failed because `shared_agent_memory` is not installed/importable in this environment. Control repo also remains behind `origin/main` by 1 commit: `111e974 Feat: accept shared memory run-task handoffs (#2)`. I did not pull because this branch is also 3 commits ahead.\\n\\nBest next move: review and commit the backend readiness slice in `~/Code/ballbox-payment-integration`, then `/status --current`.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T01:55:28.432378+00:00\", \"updated_at\": \"2026-03-17T01:55:28.432378+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\" is not installed/importable in this environment. Control repo also remains behind \", \" is stable/demo-facing only; \", \"~/Code/ballbox-payment-integration\"]}, \"run_id\": \"run_80140950f2c04d10bd3941d712ab0b25\"}, \"task_title\": \"Take the Ballbox payment system from demo flow to production readiness\", \"task_status\": \"completed\"}, {\"id\": \"art_a5cbdcb711234fd3b8306f379678523c\", \"task_id\": \"task_746e1a74f77b4cb0b8e3fd950fad90cb\", \"artifact_type\": \"report\", \"title\": \"link smoke\", \"content\": \"[tct](link) [txt](link.com)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:42:13.176072+00:00\", \"updated_at\": \"2026-03-16T20:42:13.176072+00:00\", \"metadata\": {}, \"task_title\": \"link smoke\", \"task_status\": \"completed\"}, {\"id\": \"art_322e6f0e62724030b8d995053a5ec674\", \"task_id\": \"task_2f22e794212641c49d7f8a600ad3a4bd\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"content\": \"## Summary\\nImplementado en `personal-agent`: el restart del daemon ahora pausa runs activas, las deja en estado reiniciable, y al levantar de nuevo el runtime intenta relanzarlas solo. Tambi\\u00e9n blind\\u00e9 el watcher para que un run ya pausado no termine marcado como fallo cuando llega el `SIGTERM`.\\n\\n## Changes\\n- [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - agregado `pause_running_tasks()`\\n  - `stop()` ahora puede pausar antes de terminar procesos\\n  - runs `running` recuperadas tras restart/crash pasan a `paused`, task vuelve a `draft`, metadata marca `auto_restart_on_daemon_start`\\n  - en boot, `_restart_paused_runs()` relanza tasks pausadas con `cwd`/prompt guardados\\n  - `_watch_run()` sale temprano si el run ya no est\\u00e1 `running`, evita falso `failed`\\n- [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - nuevo comando `pause-running --reason ...`\\n- [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - `restart` ahora ejecuta `python3 scripts/personal.py pause-running ...` antes de `stop/start`\\n- [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n  - actualizado recovery test para validar pause + auto-restart\\n  - nuevo test para pause/shutdown race, sin false failure/artifact\\n\\n## Verification\\n- `python3 -m unittest tests.test_personal` \\u2705\\n- `./scripts/run-checks.sh` \\u2705\\n- `./scripts/daemon-8082.sh restart`\\n  - pause step ejecut\\u00f3 bien\\n  - restart completo bloqueado por entorno actual: `\\\"foreign listener on 127.0.0.1:8082 (pid 18283); refusing to stop it\\\"`\\n- `curl -fsS http://127.0.0.1:8082/api/status` \\u2705\\n  - confirm\\u00f3 que la task activa qued\\u00f3 `draft` con latest run `paused`\\n\\n## Outputs\\n- Branch: none\\n- PR: none\\n- Files changed:\\n  - [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n- Artifacts created: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:25:49.823843+00:00\", \"updated_at\": \"2026-03-16T20:25:49.823843+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"branches\": [\"none\"], \"paths\": [\" recuperadas tras restart/crash pasan a \", \"./scripts/daemon-8082.sh restart\", \"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent/personal_agent/runtime.py\", \"/Users/sebas/personal-agent/scripts/daemon-8082.sh\", \"/Users/sebas/personal-agent/scripts/personal.py\", \"/Users/sebas/personal-agent/tests/test_personal.py\", \"curl -fsS http://127.0.0.1:8082/api/status\", \"python3 scripts/personal.py pause-running ...\", \"stop/start\"]}, \"run_id\": \"run_8ff645c9a9ad4d558df0265495267a41\"}, \"task_title\": \"en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"task_status\": \"completed\"}, {\"id\": \"art_d7f2bb1c7a204e56834b97bc4e77989b\", \"task_id\": \"task_8a866bb8156441ff8cee2f0f9f28e0c5\", \"artifact_type\": \"report\", \"title\": \"Codex result for en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"content\": \"## Summary\\nAgregado soporte markdown para links en artifacts/report renderizados por el daemon. `[USECASE.md](http://...)` ahora sale como `<a>` clickable, no literal. Hecho en worktree nuevo; adem\\u00e1s dej\\u00e9 un test existente compatible con worktrees.\\n\\n## Changes\\n- Link markdown inline en [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py#L630)\\n  - parse `[label](href)`\\n  - `href` allowlist: `http`, `https`, `mailto`, `/`, `./`, `../`, `#`\\n  - links no seguros quedan literales\\n- Tests en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1653)\\n  - cubre render de link local `http://127.0.0.1:8082/artifacts/...`\\n  - cubre fallback seguro para `javascript:...`\\n- Fix de test fr\\u00e1gil para worktree en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1345)\\n  - deja de asumir path absoluto fijo del repo principal\\n\\n## Verification\\n- `./scripts/run-checks.sh`\\n- Resultado: `Ran 36 tests ... OK`\\n\\n## Outputs\\n- Worktree: `/Users/sebas/personal-agent-wt-markdown-links`\\n- Branch: `fix-artifact-markdown-links`\\n- Files changed:\\n  - [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py)\\n  - [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py)\\n- PR: none\\n- Artifacts: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T19:15:50.674755+00:00\", \"updated_at\": \"2026-03-16T19:15:50.674755+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent-wt-markdown-links\", \"[USECASE.md](http://...)\"]}, \"run_id\": \"run_cce5f6d82e0148f6a56c9c12d159711e\"}, \"task_title\": \"en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"task_status\": \"completed\"}, {\"id\": \"art_b418ed73b479471eb1a936388268b7e9\", \"task_id\": \"task_273752f696ea4b87b2dba4497bad37f7\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"content\": \"## Summary\\n\\nAgregu\\u00e9 spacing estable en la UI del dashboard para evitar layout shifts en el resumen `\\\"drafts / running / failed / results\\\"` y en las cajas/listas de estados. El cambio qued\\u00f3 implementado en la UI inline del daemon.\\n\\n## Changes\\n\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L33) ajust\\u00e9 la grilla para alinear cards arriba y dar altura m\\u00ednima a panels.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L52) reemplac\\u00e9 el summary textual por una `summary-grid` con 4 cards de ancho reservado, para que el cambio de n\\u00fameros no mueva el layout.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L56) agregu\\u00e9 `list-slot` y `empty-state` con altura m\\u00ednima para estabilizar Drafts, Active Runs, Recent Results y Failed Runs.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L116) actualic\\u00e9 `renderList()` y sum\\u00e9 `renderSummary()` para render consistente durante refresh y estados vac\\u00edos.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L60) agregu\\u00e9 ajuste responsive para mobile sin mantener alturas forzadas innecesarias.\\n\\n## Verification\\n\\n- `./scripts/run-checks.sh` \\u2705\\n- Smoke UI en instancia temporal `127.0.0.1:8090` \\u2705\\n- Verifiqu\\u00e9 que el HTML servido incluye `summary-grid`, `summary-card`, `list-slot`, `empty-state` \\u2705\\n- No pude reiniciar `127.0.0.1:8082`: el helper detect\\u00f3 listener ajeno `pid 81699` y se neg\\u00f3 a pararlo. El `8082` actual segu\\u00eda sirviendo HTML previo.\\n\\n## Outputs\\n\\n- Branch: sin cambios\\n- PR: ninguno\\n- Archivo modificado: [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py)\\n- Artifact temporal validado: dashboard smoke en `http://127.0.0.1:8090/` durante la verificaci\\u00f3n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:55:10.658042+00:00\", \"updated_at\": \"2026-03-16T18:55:10.658042+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/personal-agent-simple-codex-runner\", \"output_refs\": {\"branches\": [\"sin\"], \"paths\": [\"\\\"drafts / running / failed / results\\\"\", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_382bb0979ec643e5b780c43c49f59103\"}, \"task_title\": \"en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"task_status\": \"completed\"}, {\"id\": \"art_b90cb99f638c45ecbb358d2f51cdad89\", \"task_id\": \"task_12b3a671a5d5494e9f0ed28ac8a16079\", \"artifact_type\": \"report\", \"title\": \"Codex result for quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"content\": \"## Summary\\nAbr\\u00ed un worktree nuevo para `ballbox-payment-integration`, agregu\\u00e9 una gu\\u00eda `USECASE.md` en espa\\u00f1ol explicando c\\u00f3mo se usa el producto end-to-end, la linke\\u00e9 desde el `README.md`, hice commit, push y abr\\u00ed PR.\\n\\n## Changes\\n- Nuevo doc: [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n- Link de acceso r\\u00e1pido en [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\\n- Contenido cubre:\\n  - qu\\u00e9 resuelve el bridge\\n  - actores\\n  - flujo `/pay` -> QR -> webhook -> callback a m\\u00e1quina\\n  - uso local/demo\\n  - prerequisitos de producci\\u00f3n\\n  - l\\u00edmites actuales\\n\\n## Verification\\n- `npm install`\\n- `npm run typecheck`\\n- `npm test`\\n- Resultado: verde\\n- Worktree limpio al final en branch publicada\\n\\n## Outputs\\n- Branch: `docs/usecase-md`\\n- PR: `#1` `Add product usage guide`\\n- Worktree: `/Users/sebas/Code/ballbox-payment-integration-usecase`\\n- Files:\\n  - [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n  - [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:52:19.557278+00:00\", \"updated_at\": \"2026-03-16T18:52:19.557278+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\"/Users/sebas/Code/ballbox-payment-integration-usecase\", \"docs/usecase-md\"]}, \"run_id\": \"run_f6edf712c14d4153bde400000125024b\"}, \"task_title\": \"quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"task_status\": \"completed\"}], \"cwd_options\": [{\"name\": \"personal-agent\", \"path\": \"/mnt/rpi/repos/opencode-harness\", \"source\": \"known\", \"repo_id\": \"repo_personal_agent\"}, {\"name\": \"ballbox-company-agent\", \"path\": \"/mnt/rpi/repos/ballbox-company-agent\", \"source\": \"known\", \"repo_id\": \"repo_ballbox_company_agent\"}, {\"name\": \"ballbox\", \"path\": \"/mnt/rpi/repos/ballbox\", \"source\": \"workspace\"}, {\"name\": \"browser-harness\", \"path\": \"/mnt/rpi/repos/browser-harness\", \"source\": \"workspace\"}, {\"name\": \"FelipeVersion\", \"path\": \"/mnt/rpi/repos/FelipeVersion\", \"source\": \"workspace\"}], \"summary\": {\"draft_count\": 8, \"running_count\": 0, \"failed_count\": 3, \"result_count\": 12}}\n-- http://127.0.0.1:8091/api/status\ncurl: (52) Empty reply from server\n\n\n\n== systemd units ==\nUnit agents-database.service could not be found.\n● personal-agent.service - Personal Agent Daemon\n     Loaded: loaded (/etc/systemd/system/personal-agent.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:10:07 -03; 1s ago\n Invocation: fb008c637bfe4489bc1826b60254ea3a\n    Process: 669913 ExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082 (code=exited, status=203/EXEC)\n   Main PID: 669913 (code=exited, status=203/EXEC)\n        CPU: 8ms\n\n== recent journal personal-agent ==\nApr 19 18:08:28 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54636.\nApr 19 18:08:28 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:28 ballbox-first (python3)[669610]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:28 ballbox-first (python3)[669610]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:28 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:28 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:33 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54637.\nApr 19 18:08:33 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:33 ballbox-first (python3)[669692]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:33 ballbox-first (python3)[669692]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:33 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:33 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:39 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54638.\nApr 19 18:08:39 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:39 ballbox-first (python3)[669694]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:39 ballbox-first (python3)[669694]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:39 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:39 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:44 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54639.\nApr 19 18:08:44 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:44 ballbox-first (python3)[669698]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:44 ballbox-first (python3)[669698]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:44 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:44 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:49 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54640.\nApr 19 18:08:49 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:49 ballbox-first (python3)[669716]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:49 ballbox-first (python3)[669716]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:49 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:49 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:54 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54641.\nApr 19 18:08:54 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:54 ballbox-first (python3)[669729]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:54 ballbox-first (python3)[669729]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:54 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:54 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:08:59 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54642.\nApr 19 18:08:59 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:08:59 ballbox-first (python3)[669733]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:08:59 ballbox-first (python3)[669733]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:08:59 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:08:59 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:05 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54643.\nApr 19 18:09:05 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:05 ballbox-first (python3)[669759]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:05 ballbox-first (python3)[669759]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:05 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:05 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:10 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54644.\nApr 19 18:09:10 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:10 ballbox-first (python3)[669763]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:10 ballbox-first (python3)[669763]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:10 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:10 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:15 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54645.\nApr 19 18:09:15 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:15 ballbox-first (python3)[669765]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:15 ballbox-first (python3)[669765]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:15 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:15 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:20 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54646.\nApr 19 18:09:20 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:20 ballbox-first (python3)[669773]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:20 ballbox-first (python3)[669773]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:20 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:20 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:25 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54647.\nApr 19 18:09:25 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:25 ballbox-first (python3)[669775]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:25 ballbox-first (python3)[669775]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:25 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:25 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:31 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54648.\nApr 19 18:09:31 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:31 ballbox-first (python3)[669803]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:31 ballbox-first (python3)[669803]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:31 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:31 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:36 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54649.\nApr 19 18:09:36 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:36 ballbox-first (python3)[669860]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:36 ballbox-first (python3)[669860]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:36 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:36 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:41 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54650.\nApr 19 18:09:41 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:41 ballbox-first (python3)[669864]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:41 ballbox-first (python3)[669864]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:41 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:41 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:46 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54651.\nApr 19 18:09:46 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:46 ballbox-first (python3)[669867]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:46 ballbox-first (python3)[669867]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:46 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:46 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:52 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54652.\nApr 19 18:09:52 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:52 ballbox-first (python3)[669871]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:52 ballbox-first (python3)[669871]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:52 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:52 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:09:57 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54653.\nApr 19 18:09:57 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:09:57 ballbox-first (python3)[669873]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:09:57 ballbox-first (python3)[669873]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:09:57 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:09:57 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:10:02 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54654.\nApr 19 18:10:02 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:10:02 ballbox-first (python3)[669911]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:10:02 ballbox-first (python3)[669911]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:10:02 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:10:02 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:10:07 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 54655.\nApr 19 18:10:07 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:10:07 ballbox-first (python3)[669913]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:10:07 ballbox-first (python3)[669913]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:10:07 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:10:07 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\n\n== recent journal agents-database ==\n-- No entries --\n"}],"isError":false,"timestamp":1776633008948},{"role":"toolResult","toolCallId":"call_bzaBk4FvQAwAtP7Nc5tsPjpZ|fc_037559ed605dbf880169e544b079e0819692f94f85791fe865","toolName":"bash","content":[{"type":"text","text":"== listening sockets 8082/8091 ==\nState  Recv-Q Send-Q Local Address:Port Peer Address:PortProcess                             \nLISTEN 0      5            0.0.0.0:8082      0.0.0.0:*    users:((\"python3\",pid=161137,fd=3))\nLISTEN 0      5            0.0.0.0:8091      0.0.0.0:*    users:((\"python3\",pid=160605,fd=3))\n\n== processes matching services ==\nroot        1434    1261  0 Apr16 ?        00:00:00 sudo -n -u sebas /usr/sbin/tailscaled serve-taildrive memory /home/sebas/agents-database/data\nsebas       1438    1434  0 Apr16 ?        00:00:00 /usr/sbin/tailscaled serve-taildrive memory /home/sebas/agents-database/data\nroot        1677    1663  0 Apr16 ?        00:00:00 fusermount3 -o rw,nosuid,nodev,fsname=portal,auto_unmount,subtype=portal -- /run/user/1000/doc\nsebas     159913       1  0 Apr16 ?        00:00:12 /home/sebas/eiffel-monitor/venv/bin/python3 /home/sebas/eiffel-monitor/monitor.py\nsebas     160605    1273  0 Apr16 ?        00:00:15 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\nsebas     161137    1273  0 Apr16 ?        00:00:14 python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\nsebas     417973       1  0 Apr18 ?        00:00:06 python3 -m http.server 8000 --bind 0.0.0.0 --directory /home/sebas/downloads/mp3-share\nsebas     651299       1  0 16:08 ?        00:00:00 node /home/sebas/.local/bin/pnpm start\nsebas     669915  669876  0 18:10 ?        00:00:00 /bin/bash -c set -o pipefail printf '== status endpoints ==\\n' for u in http://127.0.0.1:8082/api/status http://127.0.0.1:8091/api/status; do echo \"-- $u\"; curl -sS -D - --max-time 5 \"$u\" -o /tmp/resp.$$ || true; echo; [ -f /tmp/resp.$$ ] && cat /tmp/resp.$$; echo; rm -f /tmp/resp.$$; done printf '\\n== systemd units ==\\n' systemctl --no-pager --full status personal-agent.service agents-database.service || true printf '\\n== recent journal personal-agent ==\\n' journalctl -u personal-agent.service -n 120 --no-pager || true printf '\\n== recent journal agents-database ==\\n' journalctl -u agents-database.service -n 120 --no-pager || true\nsebas     669917  669876  0 18:10 ?        00:00:00 /bin/bash -c set -o pipefail printf '== listening sockets 8082/8091 ==\\n' ss -ltnp '( sport = :8082 or sport = :8091 )' || true printf '\\n== processes matching services ==\\n' ps -ef | rg -i 'personal-agent|agents-database|uvicorn|gunicorn|node|python' || true printf '\\n== local http probes verbose ==\\n' for p in 8082 8091; do echo \"-- port $p /\"; curl -sv --max-time 5 \"http://127.0.0.1:$p/\" -o /dev/null 2>&1 || true; echo; echo \"-- port $p /api/status\"; curl -sv --max-time 5 \"http://127.0.0.1:$p/api/status\" -o /dev/null 2>&1 || true; echo; done\nsebas     669921  669917  0 18:10 ?        00:00:00 rg -i personal-agent|agents-database|uvicorn|gunicorn|node|python\n\n== local http probes verbose ==\n-- port 8082 /\n*   Trying 127.0.0.1:8082...\n* Connected to 127.0.0.1 (127.0.0.1) port 8082\n* using HTTP/1.x\n> GET / HTTP/1.1\r\n> Host: 127.0.0.1:8082\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* HTTP 1.0, assume close after body\n< HTTP/1.0 200 OK\r\n< Server: BaseHTTP/0.6 Python/3.13.5\r\n< Date: Sun, 19 Apr 2026 21:10:08 GMT\r\n< Content-Type: text/html; charset=utf-8\r\n< Content-Length: 12648\r\n< \r\n{ [12648 bytes data]\n* shutting down connection #0\n\n-- port 8082 /api/status\n*   Trying 127.0.0.1:8082...\n* Connected to 127.0.0.1 (127.0.0.1) port 8082\n* using HTTP/1.x\n> GET /api/status HTTP/1.1\r\n> Host: 127.0.0.1:8082\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* HTTP 1.0, assume close after body\n< HTTP/1.0 200 OK\r\n< Server: BaseHTTP/0.6 Python/3.13.5\r\n< Date: Sun, 19 Apr 2026 21:10:08 GMT\r\n< Content-Type: application/json; charset=utf-8\r\n< Content-Length: 97442\r\n< \r\n{ [97442 bytes data]\n* shutting down connection #0\n\n-- port 8091 /\n*   Trying 127.0.0.1:8091...\n* Connected to 127.0.0.1 (127.0.0.1) port 8091\n* using HTTP/1.x\n> GET / HTTP/1.1\r\n> Host: 127.0.0.1:8091\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* HTTP 1.0, assume close after body\n< HTTP/1.0 404 Not Found\r\n< Server: BaseHTTP/0.6 Python/3.13.5\r\n< Date: Sun, 19 Apr 2026 21:10:08 GMT\r\n< Connection: close\r\n< Content-Type: text/html;charset=utf-8\r\n< Content-Length: 330\r\n< \r\n{ [330 bytes data]\n* shutting down connection #0\n\n-- port 8091 /api/status\n*   Trying 127.0.0.1:8091...\n* Connected to 127.0.0.1 (127.0.0.1) port 8091\n* using HTTP/1.x\n> GET /api/status HTTP/1.1\r\n> Host: 127.0.0.1:8091\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* Empty reply from server\n* shutting down connection #0\n\n"}],"isError":false,"timestamp":1776633008952},{"role":"assistant","content":[{"type":"text","text":"Concise health report.\n\n## Summary\n\n- `personal-agent` on `:8082`: partially up from a live orphan/manual process, but its systemd unit is broken and crash-looping.\n- `agents-database` on `:8091`: process is listening, but `/api/status` is broken. No systemd unit found.\n\n## personal-agent (`8082`)\n\n### HTTP\n- `GET /` → `200 OK`\n- `GET /api/status` → `200 OK`\n- Served by `BaseHTTP/0.6 Python/3.13.5`\n\n### Listen/process\n- Listening: `0.0.0.0:8082`\n- PID: `161137`\n- Command:\n  - `python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082`\n\n### systemd\n- Unit exists: `personal-agent.service`\n- State: `activating (auto-restart)` with repeated failure\n- ExecStart:\n  - `/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082`\n\n### Recent errors\n- Repeated:\n  - `Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory`\n  - `Failed at step EXEC`\n  - exit `203/EXEC`\n- Restart counter is huge: `54655`\n\n### Likely cause\n- systemd points to a missing venv/interpreter path.\n- Service works only because another independent `python3` process is already bound to `8082`.\n- So runtime is reachable, but service management is unhealthy and misleading.\n\n---\n\n## agents-database (`8091`)\n\n### HTTP\n- `GET /` → `404 Not Found`\n- `GET /api/status` → connection accepted, then `Empty reply from server`\n\n### Listen/process\n- Listening: `0.0.0.0:8091`\n- PID: `160605`\n- Command:\n  - `python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091`\n\n### systemd\n- `agents-database.service` not found\n\n### Recent logs\n- No journal entries for `agents-database.service`\n- Since no unit exists, there is no systemd-managed log stream under that name\n\n### Likely cause\n- Service is not managed by systemd.\n- Process is alive but handler for `/api/status` is failing internally or crashing mid-request.\n- Could be app bug, bad DB state, or an unhandled exception in that route. Port health alone is false-positive here.\n\n---\n\n## Net conclusion\n\n- `personal-agent`: app responds, but systemd is broken due to stale/missing interpreter path.\n- `agents-database`: process listens, but health endpoint is unhealthy; also not under systemd, so persistence/restart/logging are unmanaged.\n\nIf you want, I can do the next pass: inspect unit files and app stderr/stdout sources only, still without changing anything.","textSignature":"{\"v\":1,\"id\":\"msg_037559ed605dbf880169e544b1fd54819682f189e43272f07d\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":15824,"output":681,"cacheRead":3200,"cacheWrite":0,"totalTokens":19705,"cost":{"input":0.039560000000000005,"output":0.010215,"cacheRead":0.0007999999999999999,"cacheWrite":0,"total":0.05057500000000001}},"stopReason":"stop","timestamp":1776633008952,"responseId":"resp_037559ed605dbf880169e544b145e88196a2cc8dad6615a16c"}],"stderr":"","usage":{"input":18715,"output":1144,"cacheRead":3200,"cacheWrite":0,"cost":0.06474750000000001,"contextTokens":19705,"turns":2},"model":"gpt-5.4","stopReason":"stop"}]},"isError":false,"timestamp":1776633044733}}
{"type":"message","id":"a03f36a8","parentId":"80cb92b7","timestamp":"2026-04-19T21:10:52.166Z","message":{"role":"assistant","content":[{"type":"text","text":"Results:\n\n1. Root disk usage\n- `/` is `88%` full: `12G / 14G`, `1.6G` free.\n- Biggest top-level dirs on root fs:\n  - `/usr` — `6.6G`\n  - `/home` — `2.4G`\n  - `/var` — `2.1G`\n  - `/opt` — `430M`\n  - `/root` — `291M`\n\nLikely pressure points\n- `/var/log` or journald logs under `/var`\n- package cache under `/var/cache`\n- user data under `/home` that lives on root instead of `/mnt/rpi`\n\nSafe cleanup candidates to inspect first\n- journald logs\n- apt cache\n- temp files under `/tmp` or `/var/tmp`\n- large files in `/home/sebas` that should move to `/mnt/rpi`\n\n2. Service health\n- `personal-agent` on `:8082`: partially up, likely responding irregularly from a live process outside clean service state\n- `agents-database` on `:8091`: unhealthy; HTTP status endpoint returns empty reply\n- Likely cause: service process is hung, crashing, or serving broken HTTP despite socket/process presence\n\nI only got the condensed subagent summary back, not the raw detail.\n\nNext best move:\n- I can run a direct follow-up and give you:\n  - exact largest directories/files on `/`\n  - `systemctl status`, recent logs, and listener/process detail for both services\n\nSay `continue` and I’ll do that.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e544d589e0819091c1c0c3abc03abe\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":232,"output":335,"cacheRead":4608,"cacheWrite":0,"totalTokens":5175,"cost":{"input":0.00058,"output":0.005025,"cacheRead":0.001152,"cacheWrite":0,"total":0.006757}},"stopReason":"stop","timestamp":1776633044735,"responseId":"resp_071e452a5a0ea02e0169e544d4fc0081909cc558d2adf3a7f2"}}
{"type":"message","id":"8806887c","parentId":"a03f36a8","timestamp":"2026-04-19T21:46:26.057Z","message":{"role":"user","content":[{"type":"text","text":"fix services. size issues will get better once we move OS to new microsd"}],"timestamp":1776635186057}}
{"type":"message","id":"a3f9d9bf","parentId":"8806887c","timestamp":"2026-04-19T21:46:31.442Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_FeXifkXLvbryaFzreG3CHmig|fc_071e452a5a0ea02e0169e54d336f1481908fcbad0cc9d0edfa","name":"subagent","arguments":{"mode":"single","agentScope":"both","confirmProjectAgents":false,"description":"Service fixer","tools":["bash","read"],"systemPrompt":"You are a focused infra repair agent. Keep output terse. Goal: restore healthy service for personal-agent and agents-database on this machine. You may inspect, restart services, and make low-risk reversible fixes. Do not do destructive cleanup or broad system changes. If a config/code edit seems needed, stop and report before changing files. Return exactly: actions taken, current status, remaining risk.","task":"Investigate and repair personal-agent and agents-database service health on this machine. Check systemd units, recent logs, process/listener state, and local HTTP behavior for ports 8082 and 8091. Apply low-risk reversible fixes like restarting services if appropriate. Do not make file edits unless clearly necessary; if needed, stop and report. Return exactly: actions taken, current status, remaining risk.","cwd":"/home/sebas"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":205,"output":214,"cacheRead":4992,"cacheWrite":0,"totalTokens":5411,"cost":{"input":0.0005125,"output":0.00321,"cacheRead":0.001248,"cacheWrite":0,"total":0.0049705}},"stopReason":"toolUse","timestamp":1776635186057,"responseId":"resp_071e452a5a0ea02e0169e54d32aa408190a9ccaeb185cd0551"}}
{"type":"message","id":"e74c4ddd","parentId":"a3f9d9bf","timestamp":"2026-04-19T21:48:16.038Z","message":{"role":"toolResult","toolCallId":"call_FeXifkXLvbryaFzreG3CHmig|fc_071e452a5a0ea02e0169e54d336f1481908fcbad0cc9d0edfa","toolName":"subagent","content":[{"type":"text","text":"actions taken: checked root and user systemd units, recent logs, listener/process state, and local HTTP on 8082/8091. found root `personal-agent.service` broken and flapping because `ExecStart=/home/sebas/personal-agent/venv/bin/python3` no longer exists; found actual healthy services are user units: `personal-agent.service` on 8082 and `agents-database-http.service` on 8091. verified process/listener state: PID 161137 listening on 8082, PID 160605 listening on 8091. verified HTTP: 8082 returns `200 OK` on `/api/status`; 8091 accepts TCP but returns empty reply. inspected `agents-database-http.service` logs and confirmed runtime error `sqlite3.DatabaseError: database disk image is malformed`. attempted low-risk fix by stopping/disabling the broken root `personal-agent.service` and restarting user services, but root unit control calls timed out and no file edits were made.\n\ncurrent status: `personal-agent` is healthy via user systemd and serves `http://127.0.0.1:8082/api/status` successfully. root `personal-agent.service` remains misconfigured and continues failed restart attempts. `agents-database-http.service` is running as a process and listening on 8091, but the HTTP API is unhealthy because its sqlite database at `/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3` is malformed; `/api/status` does not return a valid HTTP response.\n\nremaining risk: high for `agents-database` until the sqlite file is repaired or restored from backup; that likely needs a data-level recovery step and may require file changes or maintenance actions beyond restart. medium for `personal-agent` because the broken root unit still appears present and may keep flapping until manually cleaned up; the healthy user unit currently masks service loss on 8082."}],"details":{"mode":"single","agentScope":"both","projectAgentsDir":null,"results":[{"agent":"dynamic","agentSource":"user","task":"Investigate and repair personal-agent and agents-database service health on this machine. Check systemd units, recent logs, process/listener state, and local HTTP behavior for ports 8082 and 8091. Apply low-risk reversible fixes like restarting services if appropriate. Do not make file edits unless clearly necessary; if needed, stop and report. Return exactly: actions taken, current status, remaining risk.","exitCode":0,"messages":[{"role":"user","content":[{"type":"text","text":"Task: Investigate and repair personal-agent and agents-database service health on this machine. Check systemd units, recent logs, process/listener state, and local HTTP behavior for ports 8082 and 8091. Apply low-risk reversible fixes like restarting services if appropriate. Do not make file edits unless clearly necessary; if needed, stop and report. Return exactly: actions taken, current status, remaining risk."}],"timestamp":1776635192683},{"role":"assistant","content":[{"type":"toolCall","id":"call_guhHedztDbWfbKfmDTpVgLtM|fc_0a4d3f99a6cd67170169e54d3e546c81978ebefbf8fc891aad","name":"bash","arguments":{"command":"systemctl status personal-agent --no-pager -l || true; echo '---'; systemctl status agents-database --no-pager -l || true","timeout":20}},{"type":"toolCall","id":"call_WPVnaYEKqM2rirCmmIz2IrKY|fc_0a4d3f99a6cd67170169e54d3e547c81978c99fcbb5a6ae948","name":"bash","arguments":{"command":"journalctl -u personal-agent -n 120 --no-pager || true; echo '---'; journalctl -u agents-database -n 120 --no-pager || true","timeout":20}},{"type":"toolCall","id":"call_3710e9v1vlpJBMCvbJ64YQth|fc_0a4d3f99a6cd67170169e54d3e548481978b434223d9931f42","name":"bash","arguments":{"command":"ss -ltnp | grep -E ':(8082|8091)\\b' || true; echo '---'; ps -ef | grep -E 'personal-agent|agents-database' | grep -v grep || true","timeout":20}},{"type":"toolCall","id":"call_pcs6tBAp6e0vbIeop1WdjEhI|fc_0a4d3f99a6cd67170169e54d3e548c8197a54bec6974ec0775","name":"bash","arguments":{"command":"curl -sS -i --max-time 5 http://127.0.0.1:8082/api/status || true; echo '---'; curl -sS -i --max-time 5 http://127.0.0.1:8091/api/status || true","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2947,"output":266,"cacheRead":0,"cacheWrite":0,"totalTokens":3213,"cost":{"input":0.007367500000000001,"output":0.0039900000000000005,"cacheRead":0,"cacheWrite":0,"total":0.011357500000000001}},"stopReason":"toolUse","timestamp":1776635192691,"responseId":"resp_0a4d3f99a6cd67170169e54d390dc48197b0c9e8a47e29e872"},{"role":"toolResult","toolCallId":"call_guhHedztDbWfbKfmDTpVgLtM|fc_0a4d3f99a6cd67170169e54d3e546c81978ebefbf8fc891aad","toolName":"bash","content":[{"type":"text","text":"● personal-agent.service - Personal Agent Daemon\n     Loaded: loaded (/etc/systemd/system/personal-agent.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:46:36 -03; 1s ago\n Invocation: 2b75490670c94468bb33354b55922473\n    Process: 674511 ExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082 (code=exited, status=203/EXEC)\n   Main PID: 674511 (code=exited, status=203/EXEC)\n        CPU: 8ms\n\nApr 19 18:46:36 ballbox-first (python3)[674511]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:36 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:36 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\n---\nUnit agents-database.service could not be found.\n"}],"isError":false,"timestamp":1776635198799},{"role":"toolResult","toolCallId":"call_WPVnaYEKqM2rirCmmIz2IrKY|fc_0a4d3f99a6cd67170169e54d3e547c81978c99fcbb5a6ae948","toolName":"bash","content":[{"type":"text","text":"Apr 19 18:44:57 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55054.\nApr 19 18:44:57 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:44:57 ballbox-first (python3)[674265]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:44:57 ballbox-first (python3)[674265]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:44:57 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:44:57 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:02 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55055.\nApr 19 18:45:02 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:02 ballbox-first (python3)[674281]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:02 ballbox-first (python3)[674281]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:02 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:02 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:07 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55056.\nApr 19 18:45:07 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:07 ballbox-first (python3)[674283]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:07 ballbox-first (python3)[674283]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:07 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:07 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:12 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55057.\nApr 19 18:45:12 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:12 ballbox-first (python3)[674295]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:12 ballbox-first (python3)[674295]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:12 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:12 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:18 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55058.\nApr 19 18:45:18 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:18 ballbox-first (python3)[674297]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:18 ballbox-first (python3)[674297]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:18 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:18 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:23 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55059.\nApr 19 18:45:23 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:23 ballbox-first (python3)[674353]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:23 ballbox-first (python3)[674353]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:23 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:23 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:28 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55060.\nApr 19 18:45:28 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:28 ballbox-first (python3)[674379]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:28 ballbox-first (python3)[674379]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:28 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:28 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:33 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55061.\nApr 19 18:45:33 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:33 ballbox-first (python3)[674383]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:33 ballbox-first (python3)[674383]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:33 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:33 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:39 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55062.\nApr 19 18:45:39 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:39 ballbox-first (python3)[674385]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:39 ballbox-first (python3)[674385]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:39 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:39 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:44 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55063.\nApr 19 18:45:44 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:44 ballbox-first (python3)[674389]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:44 ballbox-first (python3)[674389]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:44 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:44 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:49 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55064.\nApr 19 18:45:49 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:49 ballbox-first (python3)[674391]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:49 ballbox-first (python3)[674391]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:49 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:49 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:45:54 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55065.\nApr 19 18:45:54 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:45:54 ballbox-first (python3)[674395]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:45:54 ballbox-first (python3)[674395]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:45:54 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:45:54 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:00 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55066.\nApr 19 18:46:00 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:00 ballbox-first (python3)[674397]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:00 ballbox-first (python3)[674397]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:00 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:00 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:05 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55067.\nApr 19 18:46:05 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:05 ballbox-first (python3)[674404]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:05 ballbox-first (python3)[674404]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:05 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:05 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:10 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55068.\nApr 19 18:46:10 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:10 ballbox-first (python3)[674407]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:10 ballbox-first (python3)[674407]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:10 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:10 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:15 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55069.\nApr 19 18:46:15 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:15 ballbox-first (python3)[674411]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:15 ballbox-first (python3)[674411]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:15 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:15 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:21 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55070.\nApr 19 18:46:21 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:21 ballbox-first (python3)[674413]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:21 ballbox-first (python3)[674413]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:21 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:21 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:26 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55071.\nApr 19 18:46:26 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:26 ballbox-first (python3)[674493]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:26 ballbox-first (python3)[674493]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:26 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:26 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:31 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55072.\nApr 19 18:46:31 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:31 ballbox-first (python3)[674503]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:31 ballbox-first (python3)[674503]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:31 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:31 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\nApr 19 18:46:36 ballbox-first systemd[1]: personal-agent.service: Scheduled restart job, restart counter is at 55073.\nApr 19 18:46:36 ballbox-first systemd[1]: Started personal-agent.service - Personal Agent Daemon.\nApr 19 18:46:36 ballbox-first (python3)[674511]: personal-agent.service: Unable to locate executable '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nApr 19 18:46:36 ballbox-first (python3)[674511]: personal-agent.service: Failed at step EXEC spawning /home/sebas/personal-agent/venv/bin/python3: No such file or directory\nApr 19 18:46:36 ballbox-first systemd[1]: personal-agent.service: Main process exited, code=exited, status=203/EXEC\nApr 19 18:46:36 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\n---\n-- No entries --\n"}],"isError":false,"timestamp":1776635198800},{"role":"toolResult","toolCallId":"call_3710e9v1vlpJBMCvbJ64YQth|fc_0a4d3f99a6cd67170169e54d3e548481978b434223d9931f42","toolName":"bash","content":[{"type":"text","text":"LISTEN 0      5                          0.0.0.0:8082       0.0.0.0:*    users:((\"python3\",pid=161137,fd=3))         \nLISTEN 0      5                          0.0.0.0:8091       0.0.0.0:*    users:((\"python3\",pid=160605,fd=3))         \n---\nroot        1434    1261  0 Apr16 ?        00:00:00 sudo -n -u sebas /usr/sbin/tailscaled serve-taildrive memory /home/sebas/agents-database/data\nsebas       1438    1434  0 Apr16 ?        00:00:00 /usr/sbin/tailscaled serve-taildrive memory /home/sebas/agents-database/data\nsebas     160605    1273  0 Apr16 ?        00:00:15 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\nsebas     161137    1273  0 Apr16 ?        00:00:14 python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\n"}],"isError":false,"timestamp":1776635198804},{"role":"toolResult","toolCallId":"call_pcs6tBAp6e0vbIeop1WdjEhI|fc_0a4d3f99a6cd67170169e54d3e548c8197a54bec6974ec0775","toolName":"bash","content":[{"type":"text","text":"curl: (52) Empty reply from server\n\n\n[Showing lines 8-9 of 9 (50.0KB limit). Full output: /tmp/pi-bash-890a18ffb192aeee.log]"}],"details":{"truncation":{"content":"curl: (52) Empty reply from server\n","truncated":true,"truncatedBy":"bytes","totalLines":9,"totalBytes":97643,"outputLines":2,"outputBytes":35,"lastLinePartial":false,"firstLineExceedsLimit":false,"maxLines":2000,"maxBytes":51200},"fullOutputPath":"/tmp/pi-bash-890a18ffb192aeee.log"},"isError":false,"timestamp":1776635198842},{"role":"assistant","content":[{"type":"toolCall","id":"call_vzJjfkpKyu7EZjqeU1V9iDUc|fc_0a4d3f99a6cd67170169e54d3fe878819793bfff511f8a9524","name":"bash","arguments":{"command":"set -e\nsystemctl cat personal-agent || true\necho '---'\nls -l /home/sebas/personal-agent/venv/bin/python3 /usr/bin/python3 2>/dev/null || true\necho '---'\ncurl -v --max-time 5 http://127.0.0.1:8082/api/status || true\necho '---'\ncurl -v --max-time 5 http://127.0.0.1:8091/api/status || true","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":8283,"output":129,"cacheRead":0,"cacheWrite":0,"totalTokens":8412,"cost":{"input":0.0207075,"output":0.001935,"cacheRead":0,"cacheWrite":0,"total":0.0226425}},"stopReason":"toolUse","timestamp":1776635198843,"responseId":"resp_0a4d3f99a6cd67170169e54d3f214c8197b3972b1e58784ee8"},{"role":"toolResult","toolCallId":"call_vzJjfkpKyu7EZjqeU1V9iDUc|fc_0a4d3f99a6cd67170169e54d3fe878819793bfff511f8a9524","toolName":"bash","content":[{"type":"text","text":"* shutting down connection #0\n---\n  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n                                 Dload  Upload   Total   Spent    Left  Speed\n\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0*   Trying 127.0.0.1:8091...\n* Connected to 127.0.0.1 (127.0.0.1) port 8091\n* using HTTP/1.x\n> GET /api/status HTTP/1.1\r\n> Host: 127.0.0.1:8091\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* Empty reply from server\n\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n* shutting down connection #0\ncurl: (52) Empty reply from server\n\n\n[Showing lines 40-57 of 57 (50.0KB limit). Full output: /tmp/pi-bash-19e071593e3cbb3a.log]"}],"details":{"truncation":{"content":"* shutting down connection #0\n---\n  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current\n                                 Dload  Upload   Total   Spent    Left  Speed\n\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0*   Trying 127.0.0.1:8091...\n* Connected to 127.0.0.1 (127.0.0.1) port 8091\n* using HTTP/1.x\n> GET /api/status HTTP/1.1\r\n> Host: 127.0.0.1:8091\r\n> User-Agent: curl/8.14.1\r\n> Accept: */*\r\n> \r\n* Request completely sent off\n* Empty reply from server\n\r  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0\n* shutting down connection #0\ncurl: (52) Empty reply from server\n","truncated":true,"truncatedBy":"bytes","totalLines":57,"totalBytes":99429,"outputLines":18,"outputBytes":663,"lastLinePartial":false,"firstLineExceedsLimit":false,"maxLines":2000,"maxBytes":51200},"fullOutputPath":"/tmp/pi-bash-19e071593e3cbb3a.log"},"isError":false,"timestamp":1776635202434},{"role":"assistant","content":[{"type":"toolCall","id":"call_NoztcByGGed4Q5wA7lb6BBle|fc_0a4d3f99a6cd67170169e54d4371408197a2400eac6bbca3ec","name":"bash","arguments":{"command":"echo 'UNIT'; systemctl cat personal-agent 2>&1 | tail -n +1; echo '---FILES'; ls -l /home/sebas/personal-agent/venv/bin/python3 /usr/bin/python3 2>&1; echo '---PS'; ps -fp 160605,161137; echo '---CMDLINES'; tr '\\0' ' ' </proc/160605/cmdline; echo; tr '\\0' ' ' </proc/161137/cmdline; echo; echo '---HTTP8082'; python3 - <<'PY'\nimport urllib.request\nfor url in ['http://127.0.0.1:8082/api/status','http://127.0.0.1:8091/api/status']:\n    print('URL', url)\n    try:\n        with urllib.request.urlopen(url, timeout=5) as r:\n            print(r.status, r.read(500))\n    except Exception as e:\n        print('ERR', repr(e))\nPY","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":394,"output":239,"cacheRead":8320,"cacheWrite":0,"totalTokens":8953,"cost":{"input":0.000985,"output":0.003585,"cacheRead":0.00208,"cacheWrite":0,"total":0.00665}},"stopReason":"toolUse","timestamp":1776635202435,"responseId":"resp_0a4d3f99a6cd67170169e54d42b2e88197be8b670b6d53c061"},{"role":"toolResult","toolCallId":"call_NoztcByGGed4Q5wA7lb6BBle|fc_0a4d3f99a6cd67170169e54d4371408197a2400eac6bbca3ec","toolName":"bash","content":[{"type":"text","text":"UNIT\n# /etc/systemd/system/personal-agent.service\n[Unit]\nDescription=Personal Agent Daemon\nAfter=network-online.target\n\n[Service]\nType=simple\nUser=sebas\nWorkingDirectory=/home/sebas/personal-agent\nEnvironment=\"PATH=/home/sebas/personal-agent/venv/bin:/usr/local/bin:/usr/bin:/bin\"\nExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\nRestart=always\nRestartSec=5\n\n[Install]\nWantedBy=multi-user.target\n---FILES\nls: cannot access '/home/sebas/personal-agent/venv/bin/python3': No such file or directory\nlrwxrwxrwx 1 root root 10 Jun 30  2025 /usr/bin/python3 -> python3.13\n---PS\nUID          PID    PPID  C STIME TTY          TIME CMD\nsebas     160605    1273  0 Apr16 ?        00:00:15 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\nsebas     161137    1273  0 Apr16 ?        00:00:14 python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\n---CMDLINES\npython3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091 \npython3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082 \n---HTTP8082\nURL http://127.0.0.1:8082/api/status\n200 b'{\"draft_tasks\": [{\"id\": \"task_e5c6b42addce4f0cbc9d67a6e176fbb7\", \"title\": \"Build the Ballbox TV/display shortlist and first-pilot buying decision\", \"intent\": \"Build a concrete Ballbox TV/display recommendation for the first pilot in covered padel clubs. Cover environment assumptions (indoor vs semi-outdoor/sunlight exposure), shortlist candidate 50+ inch displays, validate Android/browser/fullscreen or kiosk-app paths, compare brightness/connectivity/installation fit, prepare supplier questions,'\nURL http://127.0.0.1:8091/api/status\nERR RemoteDisconnected('Remote end closed connection without response')\n"}],"isError":false,"timestamp":1776635208022},{"role":"assistant","content":[{"type":"toolCall","id":"call_tgqF3h8EfUU4NmcUV4yJxm0j|fc_0a4d3f99a6cd67170169e54d492e248197aec7bce5b068b64b","name":"bash","arguments":{"command":"systemctl --user status personal-agent --no-pager -l || true; echo '---'; systemctl --user list-units --type=service --all | grep -E 'agent|memory|personal' || true; echo '---'; journalctl --user -u personal-agent -n 80 --no-pager || true; echo '---'; journalctl --user -n 80 --no-pager | grep -E 'shared_agent_memory|personal.py|8091|8082' || true","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":708,"output":127,"cacheRead":8832,"cacheWrite":0,"totalTokens":9667,"cost":{"input":0.00177,"output":0.001905,"cacheRead":0.002208,"cacheWrite":0,"total":0.005883}},"stopReason":"toolUse","timestamp":1776635208023,"responseId":"resp_0a4d3f99a6cd67170169e54d48617881978ee063a5fecbbee6"},{"role":"toolResult","toolCallId":"call_tgqF3h8EfUU4NmcUV4yJxm0j|fc_0a4d3f99a6cd67170169e54d492e248197aec7bce5b068b64b","toolName":"bash","content":[{"type":"text","text":"● personal-agent.service - Personal Agent daemon\n     Loaded: loaded (/home/sebas/.config/systemd/user/personal-agent.service; enabled; preset: enabled)\n     Active: active (running) since Thu 2026-04-16 22:44:04 -03; 2 days ago\n Invocation: 19b199d97b8b4a84bbec69c3aef99773\n   Main PID: 161137 (python3)\n      Tasks: 1 (limit: 9571)\n        CPU: 14.663s\n     CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/personal-agent.service\n             └─161137 python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\n\nNotice: journal has been rotated since unit was started, output may be incomplete.\n---\n  agents-database-http.service                 loaded    active   running Agents Database HTTP API\n● agents-database-maintenance.service          not-found failed   failed  agents-database-maintenance.service\n  gcr-ssh-agent.service                        loaded    inactive dead    GCR ssh-agent wrapper\n  gpg-agent.service                            loaded    inactive dead    GnuPG cryptographic agent and passphrase cache\n  personal-agent.service                       loaded    active   running Personal Agent daemon\n  ssh-agent.service                            loaded    inactive dead    OpenSSH Agent\n---\nNo journal files were found.\n-- No entries --\n---\nNo journal files were found.\n"}],"isError":false,"timestamp":1776635211540},{"role":"assistant","content":[{"type":"toolCall","id":"call_lXlfb4VutlSkN8VQgR7qc7gk|fc_0a4d3f99a6cd67170169e54d4cb38c81978d2df9ced42016b8","name":"bash","arguments":{"command":"systemctl --user status agents-database-http --no-pager -l || true; echo '---'; systemctl --user cat agents-database-http || true; echo '---'; journalctl --user -u agents-database-http -n 120 --no-pager || true; echo '---'; python3 - <<'PY'\nimport socket, time\nfor port in (8082,8091):\n    s=socket.socket(); s.settimeout(3)\n    try:\n        s.connect(('127.0.0.1', port))\n        s.sendall(b'GET /api/status HTTP/1.1\\r\\nHost: 127.0.0.1\\r\\nConnection: close\\r\\n\\r\\n')\n        data=s.recv(4096)\n        print('PORT',port,'RESP',data[:300])\n    except Exception as e:\n        print('PORT',port,'ERR',repr(e))\n    finally:\n        s.close()\nPY","timeout":20}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":527,"output":244,"cacheRead":9472,"cacheWrite":0,"totalTokens":10243,"cost":{"input":0.0013175,"output":0.00366,"cacheRead":0.002368,"cacheWrite":0,"total":0.0073455}},"stopReason":"toolUse","timestamp":1776635211541,"responseId":"resp_0a4d3f99a6cd67170169e54d4be9e88197909f4ab7aa89a486"},{"role":"toolResult","toolCallId":"call_lXlfb4VutlSkN8VQgR7qc7gk|fc_0a4d3f99a6cd67170169e54d4cb38c81978d2df9ced42016b8","toolName":"bash","content":[{"type":"text","text":"● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: active (running) since Thu 2026-04-16 22:41:04 -03; 2 days ago\n Invocation: 5f6b97d07c454a639b14c14156a3f4cf\n   Main PID: 160605 (python3)\n      Tasks: 1 (limit: 9571)\n        CPU: 15.241s\n     CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/agents-database-http.service\n             └─160605 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\n\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:                          ~~~~~~~~~~~~^\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:         \"\"\"\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:         ^^^\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:     ...<6 lines>...\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:         (SCHEMA_VERSION,),\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:         ^^^^^^^^^^^^^^^^^^\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:     ).fetchone()[\"count\"]\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]:     ^\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]: sqlite3.DatabaseError: database disk image is malformed\nApr 19 18:46:48 ballbox-first run-http-api.sh[160605]: ----------------------------------------\n---\n# /home/sebas/.config/systemd/user/agents-database-http.service\n[Unit]\nDescription=Agents Database HTTP API\nAfter=network-online.target\nWants=network-online.target\n\n[Service]\nType=simple\nWorkingDirectory=/mnt/rpi/agents-database\nEnvironment=DB_PATH=/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nEnvironment=HOST=0.0.0.0\nEnvironment=PORT=8091\nExecStart=/mnt/rpi/agents-database/scripts/run-http-api.sh\nRestart=always\nRestartSec=10\n\n[Install]\nWantedBy=default.target\n---\nNo journal files were found.\n-- No entries --\n---\nPORT 8082 RESP b'HTTP/1.0 200 OK\\r\\nServer: BaseHTTP/0.6 Python/3.13.5\\r\\nDate: Sun, 19 Apr 2026 21:47:01 GMT\\r\\nContent-Type: application/json; charset=utf-8\\r\\nContent-Length: 97442\\r\\n\\r\\n'\nPORT 8091 RESP b''\n"}],"isError":false,"timestamp":1776635221363},{"role":"assistant","content":[{"type":"toolCall","id":"call_8HJnFvocC6yNUH6tRKBDMJ2S|fc_0a4d3f99a6cd67170169e54d5671f08197bc481f03bf3346d3","name":"bash","arguments":{"command":"set -e\nsystemctl stop personal-agent\nsystemctl reset-failed personal-agent || true\nsystemctl disable personal-agent || true\nsystemctl --user restart personal-agent\nsystemctl --user restart agents-database-http\nsleep 2\necho '---root'; systemctl status personal-agent --no-pager -l || true\necho '---user-pa'; systemctl --user status personal-agent --no-pager -l || true\necho '---user-db'; systemctl --user status agents-database-http --no-pager -l || true\necho '---http'; python3 - <<'PY'\nimport urllib.request\nfor url in ['http://127.0.0.1:8082/api/status','http://127.0.0.1:8091/api/status']:\n    print('URL', url)\n    try:\n        with urllib.request.urlopen(url, timeout=5) as r:\n            print(r.status, r.read(200))\n    except Exception as e:\n        print('ERR', repr(e))\nPY","timeout":30}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":820,"output":250,"cacheRead":10112,"cacheWrite":0,"totalTokens":11182,"cost":{"input":0.00205,"output":0.0037500000000000003,"cacheRead":0.002528,"cacheWrite":0,"total":0.008328}},"stopReason":"toolUse","timestamp":1776635221363,"responseId":"resp_0a4d3f99a6cd67170169e54d55b4148197b7c2fb68863f7ff3"},{"role":"toolResult","toolCallId":"call_8HJnFvocC6yNUH6tRKBDMJ2S|fc_0a4d3f99a6cd67170169e54d5671f08197bc481f03bf3346d3","toolName":"bash","content":[{"type":"text","text":"Failed to stop personal-agent.service: Connection timed out\nSee system logs and 'systemctl status personal-agent.service' for details.\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635252122},{"role":"assistant","content":[{"type":"toolCall","id":"call_psiIF93aEDYEdxw7Dk9AzCsk|fc_0a4d3f99a6cd67170169e54d7507d08197813b91c586c2925b","name":"bash","arguments":{"command":"systemctl kill personal-agent || true; sleep 1; systemctl stop personal-agent || true; systemctl reset-failed personal-agent || true; systemctl disable personal-agent || true; systemctl --user restart personal-agent || true; systemctl --user restart agents-database-http || true; sleep 2; echo '---root'; systemctl status personal-agent --no-pager -l || true; echo '---user-pa'; systemctl --user status personal-agent --no-pager -l || true; echo '---user-db'; systemctl --user status agents-database-http --no-pager -l || true; echo '---http'; python3 - <<'PY'\nimport urllib.request\nfor url in ['http://127.0.0.1:8082/api/status','http://127.0.0.1:8091/api/status']:\n    print('URL', url)\n    try:\n        with urllib.request.urlopen(url, timeout=5) as r:\n            print(r.status, r.read(200))\n    except Exception as e:\n        print('ERR', repr(e))\nPY","timeout":30}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":217,"output":260,"cacheRead":11008,"cacheWrite":0,"totalTokens":11485,"cost":{"input":0.0005425,"output":0.0039000000000000003,"cacheRead":0.0027519999999999997,"cacheWrite":0,"total":0.0071944999999999995}},"stopReason":"toolUse","timestamp":1776635252123,"responseId":"resp_0a4d3f99a6cd67170169e54d7460a081979596543932b2c1fa"},{"role":"toolResult","toolCallId":"call_psiIF93aEDYEdxw7Dk9AzCsk|fc_0a4d3f99a6cd67170169e54d7507d08197813b91c586c2925b","toolName":"bash","content":[{"type":"text","text":"Failed to kill unit personal-agent.service: Connection timed out\n\n\nCommand timed out after 30 seconds"}],"details":{},"isError":true,"timestamp":1776635287750},{"role":"assistant","content":[{"type":"text","text":"actions taken: checked root and user systemd units, recent logs, listener/process state, and local HTTP on 8082/8091. found root `personal-agent.service` broken and flapping because `ExecStart=/home/sebas/personal-agent/venv/bin/python3` no longer exists; found actual healthy services are user units: `personal-agent.service` on 8082 and `agents-database-http.service` on 8091. verified process/listener state: PID 161137 listening on 8082, PID 160605 listening on 8091. verified HTTP: 8082 returns `200 OK` on `/api/status`; 8091 accepts TCP but returns empty reply. inspected `agents-database-http.service` logs and confirmed runtime error `sqlite3.DatabaseError: database disk image is malformed`. attempted low-risk fix by stopping/disabling the broken root `personal-agent.service` and restarting user services, but root unit control calls timed out and no file edits were made.\n\ncurrent status: `personal-agent` is healthy via user systemd and serves `http://127.0.0.1:8082/api/status` successfully. root `personal-agent.service` remains misconfigured and continues failed restart attempts. `agents-database-http.service` is running as a process and listening on 8091, but the HTTP API is unhealthy because its sqlite database at `/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3` is malformed; `/api/status` does not return a valid HTTP response.\n\nremaining risk: high for `agents-database` until the sqlite file is repaired or restored from backup; that likely needs a data-level recovery step and may require file changes or maintenance actions beyond restart. medium for `personal-agent` because the broken root unit still appears present and may keep flapping until manually cleaned up; the healthy user unit currently masks service loss on 8082.","textSignature":"{\"v\":1,\"id\":\"msg_0a4d3f99a6cd67170169e54d98afdc8197b451b89441aca2fb\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":123,"output":393,"cacheRead":11392,"cacheWrite":0,"totalTokens":11908,"cost":{"input":0.00030750000000000005,"output":0.005895,"cacheRead":0.002848,"cacheWrite":0,"total":0.0090505}},"stopReason":"stop","timestamp":1776635287751,"responseId":"resp_0a4d3f99a6cd67170169e54d98127c8197a8ef2049bf63ff2e"}],"stderr":"","usage":{"input":14019,"output":1908,"cacheRead":59136,"cacheWrite":0,"cost":0.07845150000000001,"contextTokens":11908,"turns":8},"model":"gpt-5.4","stopReason":"stop"}]},"isError":false,"timestamp":1776635296038}}
{"type":"message","id":"a59d5842","parentId":"e74c4ddd","timestamp":"2026-04-19T21:48:19.852Z","message":{"role":"assistant","content":[{"type":"text","text":"State:\n\n- `personal-agent`: healthy on user service, `:8082` works\n- `agents-database`: broken at data layer\n- Root `personal-agent.service`: stale/broken, still present\n\nCause:\n- Broken root `personal-agent.service` points to missing venv python\n- `agents-database` SQLite file is malformed:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3`\n\nBest fix path now:\n1. disable/stop broken root `personal-agent.service`\n2. repair or restore the malformed SQLite DB for `agents-database`\n3. restart and verify `agents-database-http.service`\n\nBoth steps can affect service availability and DB contents.\n\nConfirm and I’ll do the repair work.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e54da0daa48190b631c4bb58197281\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":563,"output":156,"cacheRead":5248,"cacheWrite":0,"totalTokens":5967,"cost":{"input":0.0014075000000000001,"output":0.00234,"cacheRead":0.001312,"cacheWrite":0,"total":0.0050595}},"stopReason":"stop","timestamp":1776635296040,"responseId":"resp_071e452a5a0ea02e0169e54da04d988190a6d978007a10e8d0"}}
{"type":"message","id":"e81b6e07","parentId":"a59d5842","timestamp":"2026-04-19T21:48:55.497Z","message":{"role":"user","content":[{"type":"text","text":"y"}],"timestamp":1776635335495}}
{"type":"message","id":"56fcb90e","parentId":"e81b6e07","timestamp":"2026-04-19T21:49:01.345Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_palTTNsKUBxRl9V69Ph3xNRi|fc_071e452a5a0ea02e0169e54dcd0468819085c7be6992c96fa0","name":"bash","arguments":{"command":"set -e\nsystemctl stop personal-agent.service || true\nsystemctl disable personal-agent.service || true\nsystemctl reset-failed personal-agent.service || true\nsystemctl status personal-agent.service --no-pager -n 20 || true","timeout":30}},{"type":"toolCall","id":"call_z22Mf7WZCjvvs9T8i1nQyARu|fc_071e452a5a0ea02e0169e54dcd04748190889da11f8e0c1bec","name":"bash","arguments":{"command":"set -e\nsystemctl --user status personal-agent.service --no-pager -n 20 || true\nsystemctl --user status agents-database-http.service --no-pager -n 20 || true","timeout":30}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":86,"output":146,"cacheRead":5888,"cacheWrite":0,"totalTokens":6120,"cost":{"input":0.00021500000000000002,"output":0.00219,"cacheRead":0.001472,"cacheWrite":0,"total":0.0038770000000000002}},"stopReason":"toolUse","timestamp":1776635335497,"responseId":"resp_071e452a5a0ea02e0169e54dc7c9dc8190b93bfde34f7f2948"}}
{"type":"message","id":"9f8a94c7","parentId":"56fcb90e","timestamp":"2026-04-19T21:49:31.352Z","message":{"role":"toolResult","toolCallId":"call_palTTNsKUBxRl9V69Ph3xNRi|fc_071e452a5a0ea02e0169e54dcd0468819085c7be6992c96fa0","toolName":"bash","content":[{"type":"text","text":"Failed to stop personal-agent.service: Connection timed out\nSee system logs and 'systemctl status personal-agent.service' for details.\n\n\nCommand timed out after 30 seconds"}],"details":{},"isError":true,"timestamp":1776635371352}}
{"type":"message","id":"230fe4d0","parentId":"9f8a94c7","timestamp":"2026-04-19T21:49:31.353Z","message":{"role":"toolResult","toolCallId":"call_z22Mf7WZCjvvs9T8i1nQyARu|fc_071e452a5a0ea02e0169e54dcd04748190889da11f8e0c1bec","toolName":"bash","content":[{"type":"text","text":"● personal-agent.service - Personal Agent daemon\n     Loaded: loaded (/home/sebas/.config/systemd/user/personal-agent.service; enabled; preset: enabled)\n     Active: active (running) since Thu 2026-04-16 22:44:04 -03; 2 days ago\n Invocation: 19b199d97b8b4a84bbec69c3aef99773\n   Main PID: 161137 (python3)\n      Tasks: 1 (limit: 9571)\n        CPU: 14.724s\n     CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/personal-agent.service\n             └─161137 python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\n\nNotice: journal has been rotated since unit was started, output may be incomplete.\n● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: active (running) since Thu 2026-04-16 22:41:04 -03; 2 days ago\n Invocation: 5f6b97d07c454a639b14c14156a3f4cf\n   Main PID: 160605 (python3)\n      Tasks: 1 (limit: 9571)\n        CPU: 15.259s\n     CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/agents-database-http.service\n             └─160605 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\n\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     self.handle_one_request()\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     ~~~~~~~~~~~~~~~~~~~~~~~^^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:   File \"/usr/lib/python3.13/http/server.py\", line 424, in handle_one_request\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     method()\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     ~~~~~~^^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:   File \"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py\", line 65, in do_GET\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     \"audit\": service.audit_v2(),\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:              ~~~~~~~~~~~~~~~~^^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:   File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 938, in audit_v2\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     legacy_memory_rows = conn.execute(\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:                          ~~~~~~~~~~~~^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:         \"\"\"\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:         ^^^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     ...<6 lines>...\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:         (SCHEMA_VERSION,),\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:         ^^^^^^^^^^^^^^^^^^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     ).fetchone()[\"count\"]\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]:     ^\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]: sqlite3.DatabaseError: database disk image is malformed\nApr 19 18:47:01 ballbox-first run-http-api.sh[160605]: ----------------------------------------\n"}],"isError":false,"timestamp":1776635371352}}
{"type":"message","id":"b20bf147","parentId":"230fe4d0","timestamp":"2026-04-19T21:49:38.140Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_D1oTdx3XEnOcDryR2iY6W1RS|fc_071e452a5a0ea02e0169e54dec57dc81908a118c17730ec4f9","name":"bash","arguments":{"command":"set -euo pipefail\nDB='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nDIR=$(dirname \"$DB\")\nTS=$(date +%Y%m%d-%H%M%S)\nBACKUP=\"$DIR/shared-agent-memory.sqlite3.bak-$TS\"\nRECOVERED=\"$DIR/shared-agent-memory.recovered-$TS.sqlite3\"\n\necho \"DB=$DB\"\nls -lh \"$DB\"\ncp -a \"$DB\" \"$BACKUP\"\necho \"backup=$BACKUP\"\n\nsystemctl --user stop agents-database-http.service\n\npython3 - <<'PY'\nimport sqlite3, sys, os\nsrc = '/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ndst = os.environ['RECOVERED']\ntry:\n    con = sqlite3.connect(src)\n    cur = con.cursor()\n    rows = cur.execute(\"PRAGMA integrity_check;\").fetchall()\n    print('integrity_check:', rows[:5])\nexcept Exception as e:\n    print('integrity_check_error:', repr(e))\ntry:\n    con = sqlite3.connect(src)\n    with sqlite3.connect(dst) as out:\n        con.backup(out)\n    print('backup_api_copy_ok')\nexcept Exception as e:\n    print('backup_api_copy_error:', repr(e))\nPY\n","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1124,"output":321,"cacheRead":6016,"cacheWrite":0,"totalTokens":7461,"cost":{"input":0.0028100000000000004,"output":0.004815,"cacheRead":0.001504,"cacheWrite":0,"total":0.009129}},"stopReason":"toolUse","timestamp":1776635371355,"responseId":"resp_071e452a5a0ea02e0169e54deba9ac8190bf5a31d9c71e2732"}}
{"type":"message","id":"fbeec7b8","parentId":"b20bf147","timestamp":"2026-04-19T21:49:43.672Z","message":{"role":"toolResult","toolCallId":"call_D1oTdx3XEnOcDryR2iY6W1RS|fc_071e452a5a0ea02e0169e54dec57dc81908a118c17730ec4f9","toolName":"bash","content":[{"type":"text","text":"DB=/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\n-rw-r--r-- 1 sebas sebas 104M Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nbackup=/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3.bak-20260419-184938\nTraceback (most recent call last):\n  File \"<stdin>\", line 3, in <module>\n  File \"<frozen os>\", line 717, in __getitem__\nKeyError: 'RECOVERED'\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635383672}}
{"type":"message","id":"8aefa094","parentId":"fbeec7b8","timestamp":"2026-04-19T21:49:49.974Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_YssGVS83P68X7xj3W76oqv1J|fc_071e452a5a0ea02e0169e54df8b7b08190a5056aee8879e642","name":"bash","arguments":{"command":"set -euo pipefail\nDB='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nDIR=$(dirname \"$DB\")\nTS=$(date +%Y%m%d-%H%M%S)\nRECOVERED=\"$DIR/shared-agent-memory.recovered-$TS.sqlite3\"\nexport RECOVERED\n\necho \"recovered=$RECOVERED\"\npython3 - <<'PY'\nimport sqlite3, os\nsrc = '/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ndst = os.environ['RECOVERED']\ntry:\n    con = sqlite3.connect(src)\n    cur = con.cursor()\n    rows = cur.execute('PRAGMA integrity_check;').fetchall()\n    print('integrity_check:', rows[:5])\nexcept Exception as e:\n    print('integrity_check_error:', repr(e))\ntry:\n    con = sqlite3.connect(src)\n    with sqlite3.connect(dst) as out:\n        con.backup(out)\n    print('backup_api_copy_ok')\nexcept Exception as e:\n    print('backup_api_copy_error:', repr(e))\nPY\nls -lh \"$RECOVERED\" 2>/dev/null || true","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":304,"output":288,"cacheRead":7296,"cacheWrite":0,"totalTokens":7888,"cost":{"input":0.00076,"output":0.00432,"cacheRead":0.0018239999999999999,"cacheWrite":0,"total":0.006904}},"stopReason":"toolUse","timestamp":1776635383673,"responseId":"resp_071e452a5a0ea02e0169e54df7fc5481909faa831e93c945a9"}}
{"type":"message","id":"c21d86bc","parentId":"8aefa094","timestamp":"2026-04-19T21:50:05.660Z","message":{"role":"toolResult","toolCallId":"call_YssGVS83P68X7xj3W76oqv1J|fc_071e452a5a0ea02e0169e54df8b7b08190a5056aee8879e642","toolName":"bash","content":[{"type":"text","text":"recovered=/mnt/rpi/agents-database/data/shared-agent-memory.recovered-20260419-184949.sqlite3\nintegrity_check_error: DatabaseError('database disk image is malformed')\nbackup_api_copy_ok\n-rw-r--r-- 1 sebas sebas 104M Apr 19 18:49 /mnt/rpi/agents-database/data/shared-agent-memory.recovered-20260419-184949.sqlite3\n"}],"isError":false,"timestamp":1776635405660}}
{"type":"message","id":"a5670658","parentId":"c21d86bc","timestamp":"2026-04-19T21:50:11.686Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_E7jT957M7volJTJjEweNd7bQ|fc_071e452a5a0ea02e0169e54e0ec8288190baeef6fdd5b7e99a","name":"bash","arguments":{"command":"set -euo pipefail\nDB='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nLATEST=$(ls -1t /mnt/rpi/agents-database/data/shared-agent-memory.recovered-*.sqlite3 | head -n1)\necho \"using=$LATEST\"\npython3 - <<'PY'\nimport sqlite3, glob\np = sorted(glob.glob('/mnt/rpi/agents-database/data/shared-agent-memory.recovered-*.sqlite3'))[-1]\ncon = sqlite3.connect(p)\ncur = con.cursor()\ntry:\n    print('integrity_check:', cur.execute('PRAGMA integrity_check;').fetchall()[:5])\nexcept Exception as e:\n    print('integrity_check_error:', repr(e))\nfor q in [\n    \"select name from sqlite_master where type='table' order by name limit 20\",\n    \"select count(*) from sqlite_master\",\n]:\n    try:\n        print('query:', q)\n        print(cur.execute(q).fetchall()[:20])\n    except Exception as e:\n        print('query_error:', repr(e))\nPY","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":182,"output":270,"cacheRead":7808,"cacheWrite":0,"totalTokens":8260,"cost":{"input":0.00045500000000000006,"output":0.00405,"cacheRead":0.001952,"cacheWrite":0,"total":0.006456999999999999}},"stopReason":"toolUse","timestamp":1776635405661,"responseId":"resp_071e452a5a0ea02e0169e54e0e1ce08190a246a5b274ac4ec2"}}
{"type":"message","id":"df5311a9","parentId":"a5670658","timestamp":"2026-04-19T21:50:11.800Z","message":{"role":"toolResult","toolCallId":"call_E7jT957M7volJTJjEweNd7bQ|fc_071e452a5a0ea02e0169e54e0ec8288190baeef6fdd5b7e99a","toolName":"bash","content":[{"type":"text","text":"using=/mnt/rpi/agents-database/data/shared-agent-memory.recovered-20260419-184949.sqlite3\nintegrity_check_error: DatabaseError('database disk image is malformed')\nquery: select name from sqlite_master where type='table' order by name limit 20\n[('artifacts',), ('ingestion_events',), ('maintenance_jobs',), ('maintenance_runs',), ('memories',), ('memories_fts',), ('memories_fts_config',), ('memories_fts_content',), ('memories_fts_data',), ('memories_fts_docsize',), ('memories_fts_idx',), ('memory_conflicts',), ('memory_links',), ('profiles',), ('projects',), ('repos',), ('retrieval_logs',), ('sources',), ('task_runs',), ('tasks',)]\nquery: select count(*) from sqlite_master\n[(55,)]\n"}],"isError":false,"timestamp":1776635411800}}
{"type":"message","id":"e9daff85","parentId":"df5311a9","timestamp":"2026-04-19T21:50:16.067Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_dTBbSt2n2HymlWyzIgml4V3z|fc_071e452a5a0ea02e0169e54e14cb908190ba9167416e58c710","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nif [ -d .git ]; then\n  git status --short\n  git rev-parse --abbrev-ref HEAD\nfi\npython3 - <<'PY'\nimport sqlite3\np='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(p)\ncur=con.cursor()\nfor table in ['memories','tasks','sources','artifacts','projects','repos']:\n    try:\n        r=cur.execute(f'SELECT COUNT(*) FROM {table}').fetchone()\n        print(table, r)\n    except Exception as e:\n        print(table, 'ERR', repr(e))\nPY","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":395,"output":180,"cacheRead":8064,"cacheWrite":0,"totalTokens":8639,"cost":{"input":0.0009875,"output":0.0027,"cacheRead":0.002016,"cacheWrite":0,"total":0.0057035}},"stopReason":"toolUse","timestamp":1776635411801,"responseId":"resp_071e452a5a0ea02e0169e54e140e3881909eef066e1081edae"}}
{"type":"message","id":"3191ad20","parentId":"e9daff85","timestamp":"2026-04-19T21:50:17.376Z","message":{"role":"toolResult","toolCallId":"call_dTBbSt2n2HymlWyzIgml4V3z|fc_071e452a5a0ea02e0169e54e14cb908190ba9167416e58c710","toolName":"bash","content":[{"type":"text","text":" M .gitignore\n M data/shared-agent-memory.sqlite3\n M docs/memory-consolidation-rfc.md\n M docs/system-v1.md\n M scripts/run-maintenance-daemon.sh\n M src/shared_agent_memory/cli.py\n M src/shared_agent_memory/service.py\n M tests/test_memory_service.py\n?? data/shared-agent-memory.recovered-20260419-184949.sqlite3\n?? data/shared-agent-memory.sqlite3.bak-20260419-184938\n?? docs/http-api.md\n?? scripts/run-http-api.sh\n?? src/shared_agent_memory/http_api.py\n?? systemd/\nmain\nmemories (320,)\ntasks (194,)\nsources (0,)\nartifacts (163,)\nprojects (4,)\nrepos (7,)\n"}],"isError":false,"timestamp":1776635417376}}
{"type":"message","id":"fec08c29","parentId":"3191ad20","timestamp":"2026-04-19T21:50:23.573Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_g5A3rZnU1Ja7NjTLHjpgWqX9|fc_071e452a5a0ea02e0169e54e1abcc08190b341ae03c651ac37","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nsqlite3 --version >/dev/null\npython3 - <<'PY'\nimport sqlite3, os\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(src)\ncur=con.cursor()\nfor q in [\n  'SELECT COUNT(*) FROM memories',\n  'SELECT COUNT(*) FROM tasks',\n  'SELECT COUNT(*) FROM artifacts',\n  'SELECT COUNT(*) FROM projects',\n  'SELECT COUNT(*) FROM repos',\n  'SELECT COUNT(*) FROM retrieval_logs',\n  'SELECT COUNT(*) FROM task_runs',\n]:\n    try:\n        print(q, cur.execute(q).fetchone())\n    except Exception as e:\n        print(q, 'ERR', repr(e))\nPY\nsqlite3 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 \".recover\" > /tmp/agents-db-recover.sql\nwc -l /tmp/agents-db-recover.sql\nhead -n 5 /tmp/agents-db-recover.sql","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":354,"output":265,"cacheRead":8448,"cacheWrite":0,"totalTokens":9067,"cost":{"input":0.000885,"output":0.003975,"cacheRead":0.0021119999999999997,"cacheWrite":0,"total":0.006972000000000001}},"stopReason":"toolUse","timestamp":1776635417378,"responseId":"resp_071e452a5a0ea02e0169e54e19a4cc8190a28c69adf9544bd8"}}
{"type":"message","id":"bb16ef2a","parentId":"fec08c29","timestamp":"2026-04-19T21:50:23.583Z","message":{"role":"toolResult","toolCallId":"call_g5A3rZnU1Ja7NjTLHjpgWqX9|fc_071e452a5a0ea02e0169e54e1abcc08190b341ae03c651ac37","toolName":"bash","content":[{"type":"text","text":"/bin/bash: line 3: sqlite3: command not found\n\n\nCommand exited with code 127"}],"details":{},"isError":true,"timestamp":1776635423583}}
{"type":"message","id":"1178610c","parentId":"bb16ef2a","timestamp":"2026-04-19T21:50:30.149Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_fP3DYJLPlZT1fFkI6GO8iTxZ|fc_071e452a5a0ea02e0169e54e20a0cc819094b263e31d7200d6","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, os, glob, subprocess, sys\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nfor q in [\n  'SELECT COUNT(*) FROM memories',\n  'SELECT COUNT(*) FROM tasks',\n  'SELECT COUNT(*) FROM artifacts',\n  'SELECT COUNT(*) FROM projects',\n  'SELECT COUNT(*) FROM repos',\n  'SELECT COUNT(*) FROM retrieval_logs',\n  'SELECT COUNT(*) FROM task_runs',\n  'SELECT COUNT(*) FROM sqlite_master',\n]:\n    con=sqlite3.connect(src)\n    cur=con.cursor()\n    try:\n        print(q, cur.execute(q).fetchone())\n    except Exception as e:\n        print(q, 'ERR', repr(e))\nPY\nsystemctl --user start agents-database-http.service\nsleep 2\ncurl -sS -m 10 -D - -o /tmp/adb.out http://127.0.0.1:8091/api/status || true\necho '--- body ---'\ncat /tmp/adb.out || true\njournalctl --user -u agents-database-http.service -n 40 --no-pager | tail -n 20","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":138,"output":303,"cacheRead":8960,"cacheWrite":0,"totalTokens":9401,"cost":{"input":0.00034500000000000004,"output":0.004545,"cacheRead":0.00224,"cacheWrite":0,"total":0.00713}},"stopReason":"toolUse","timestamp":1776635423584,"responseId":"resp_071e452a5a0ea02e0169e54e1fe660819087a230e4eafe3fb5"}}
{"type":"message","id":"1950eda9","parentId":"1178610c","timestamp":"2026-04-19T21:50:32.224Z","message":{"role":"toolResult","toolCallId":"call_fP3DYJLPlZT1fFkI6GO8iTxZ|fc_071e452a5a0ea02e0169e54e20a0cc819094b263e31d7200d6","toolName":"bash","content":[{"type":"text","text":"SELECT COUNT(*) FROM memories (320,)\nSELECT COUNT(*) FROM tasks (194,)\nSELECT COUNT(*) FROM artifacts (163,)\nSELECT COUNT(*) FROM projects (4,)\nSELECT COUNT(*) FROM repos (7,)\nSELECT COUNT(*) FROM retrieval_logs (6901,)\nSELECT COUNT(*) FROM task_runs (63,)\nSELECT COUNT(*) FROM sqlite_master (55,)\ncurl: (7) Failed to connect to 127.0.0.1 port 8091 after 0 ms: Could not connect to server\ncat: /tmp/adb.out: No such file or directory\n--- body ---\nNo journal files were found.\n-- No entries --\n"}],"isError":false,"timestamp":1776635432224}}
{"type":"message","id":"fee8c1e1","parentId":"1950eda9","timestamp":"2026-04-19T21:50:35.863Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_02KiiPtBKo5GE6KyC78Ve7GS|fc_071e452a5a0ea02e0169e54e2981e0819097ae1e45adf3bc02","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user status agents-database-http.service --no-pager -n 50 || true\nsystemctl --user restart agents-database-http.service || true\nsleep 2\nsystemctl --user status agents-database-http.service --no-pager -n 50 || true\nss -ltnp | grep ':8091' || true\nps -fp $(systemctl --user show -p MainPID --value agents-database-http.service 2>/dev/null) || true","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":323,"output":129,"cacheRead":9216,"cacheWrite":0,"totalTokens":9668,"cost":{"input":0.0008075000000000001,"output":0.001935,"cacheRead":0.002304,"cacheWrite":0,"total":0.005046500000000001}},"stopReason":"toolUse","timestamp":1776635432225,"responseId":"resp_071e452a5a0ea02e0169e54e28abcc81908df2bce465342a6e"}}
{"type":"message","id":"7a015e63","parentId":"fee8c1e1","timestamp":"2026-04-19T21:50:37.939Z","message":{"role":"toolResult","toolCallId":"call_02KiiPtBKo5GE6KyC78Ve7GS|fc_071e452a5a0ea02e0169e54e2981e0819097ae1e45adf3bc02","toolName":"bash","content":[{"type":"text","text":"● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:50:30 -03; 5s ago\n Invocation: 29d9d5bcd1274d879069413167c6976f\n    Process: 675111 ExecStart=/mnt/rpi/agents-database/scripts/run-http-api.sh (code=exited, status=1/FAILURE)\n   Main PID: 675111 (code=exited, status=1/FAILURE)\n        CPU: 127ms\n● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:50:36 -03; 1s ago\n Invocation: 106fbc9869b1477eba5547e007338a29\n    Process: 675149 ExecStart=/mnt/rpi/agents-database/scripts/run-http-api.sh (code=exited, status=1/FAILURE)\n   Main PID: 675149 (code=exited, status=1/FAILURE)\n        CPU: 143ms\nerror: process ID out of range\n\nUsage:\n ps [options]\n\n Try 'ps --help <simple|list|output|threads|misc|all>'\n  or 'ps --help <s|l|o|t|m|a>'\n for additional help text.\n\nFor more details see ps(1).\n"}],"isError":false,"timestamp":1776635437939}}
{"type":"message","id":"4f3f2f9d","parentId":"7a015e63","timestamp":"2026-04-19T21:50:40.833Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_ifO1GBXKWrbFNaadyx814fuu|fc_071e452a5a0ea02e0169e54e2f04f8819085a714c0103f1a4f","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user cat agents-database-http.service\nprintf '\\n--- script ---\\n'\nsed -n '1,220p' /mnt/rpi/agents-database/scripts/run-http-api.sh\nprintf '\\n--- direct run ---\\n'\n/mnt/rpi/agents-database/scripts/run-http-api.sh","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":587,"output":96,"cacheRead":9472,"cacheWrite":0,"totalTokens":10155,"cost":{"input":0.0014675,"output":0.00144,"cacheRead":0.002368,"cacheWrite":0,"total":0.005275500000000001}},"stopReason":"toolUse","timestamp":1776635437940,"responseId":"resp_071e452a5a0ea02e0169e54e2e3c888190bb3906fba897993c"}}
{"type":"message","id":"1a233faa","parentId":"4f3f2f9d","timestamp":"2026-04-19T21:50:40.972Z","message":{"role":"toolResult","toolCallId":"call_ifO1GBXKWrbFNaadyx814fuu|fc_071e452a5a0ea02e0169e54e2f04f8819085a714c0103f1a4f","toolName":"bash","content":[{"type":"text","text":"# /home/sebas/.config/systemd/user/agents-database-http.service\n[Unit]\nDescription=Agents Database HTTP API\nAfter=network-online.target\nWants=network-online.target\n\n[Service]\nType=simple\nWorkingDirectory=/mnt/rpi/agents-database\nEnvironment=DB_PATH=/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nEnvironment=HOST=0.0.0.0\nEnvironment=PORT=8091\nExecStart=/mnt/rpi/agents-database/scripts/run-http-api.sh\nRestart=always\nRestartSec=10\n\n[Install]\nWantedBy=default.target\n\n--- script ---\n#!/usr/bin/env bash\nset -euo pipefail\n\nREPO_ROOT=\"$(cd \"$(dirname \"${BASH_SOURCE[0]}\")/..\" && pwd)\"\nDB_PATH=\"${DB_PATH:-${REPO_ROOT}/data/shared-agent-memory.sqlite3}\"\nHOST=\"${HOST:-0.0.0.0}\"\nPORT=\"${PORT:-8091}\"\n\nexport PATH=\"/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin:${PATH}\"\nexport PYTHONPATH=\"${REPO_ROOT}/src${PYTHONPATH:+:${PYTHONPATH}}\"\n\nexec python3 -m shared_agent_memory.cli \\\n  --db \"${DB_PATH}\" \\\n  serve-http \\\n  --host \"${HOST}\" \\\n  --port \"${PORT}\"\n\n--- direct run ---\nTraceback (most recent call last):\n  File \"<frozen runpy>\", line 198, in _run_module_as_main\n  File \"<frozen runpy>\", line 88, in _run_code\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 287, in <module>\n    main()\n    ~~~~^^\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 138, in main\n    service = MemoryService(args.db)\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 67, in __init__\n    self.migrate_v2()\n    ~~~~~~~~~~~~~~~^^\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 973, in migrate_v2\n    before = self.audit_v2()\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 938, in audit_v2\n    legacy_memory_rows = conn.execute(\n                         ~~~~~~~~~~~~^\n        \"\"\"\n        ^^^\n    ...<6 lines>...\n        (SCHEMA_VERSION,),\n        ^^^^^^^^^^^^^^^^^^\n    ).fetchone()[\"count\"]\n    ^\nsqlite3.DatabaseError: database disk image is malformed\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635440972}}
{"type":"message","id":"2e3dd96a","parentId":"1a233faa","timestamp":"2026-04-19T21:50:42.816Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_132aGv8Ez8uaYpdWFIpxpxSp|fc_071e452a5a0ea02e0169e54e3205cc8190a25791fd780b36cf","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/service.py","offset":40,"limit":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":739,"output":38,"cacheRead":9984,"cacheWrite":0,"totalTokens":10761,"cost":{"input":0.0018475000000000002,"output":0.00057,"cacheRead":0.002496,"cacheWrite":0,"total":0.0049135}},"stopReason":"toolUse","timestamp":1776635440973,"responseId":"resp_071e452a5a0ea02e0169e54e3143f0819080da25757fe4ba6f"}}
{"type":"message","id":"326ce04b","parentId":"2e3dd96a","timestamp":"2026-04-19T21:50:42.856Z","message":{"role":"toolResult","toolCallId":"call_132aGv8Ez8uaYpdWFIpxpxSp|fc_071e452a5a0ea02e0169e54e3205cc8190a25791fd780b36cf","toolName":"read","content":[{"type":"text","text":"    explanation: str\n    facet_score: float\n    lexical_score: float\n    semantic_score: float\n\n    def as_dict(self) -> dict[str, Any]:\n        return {\n            \"memory\": self.memory,\n            \"score\": self.score,\n            \"score_breakdown\": {\n                \"facet\": self.facet_score,\n                \"lexical\": self.lexical_score,\n                \"semantic\": self.semantic_score,\n                \"confidence\": self.memory[\"confidence\"],\n                \"freshness\": self.memory[\"freshness\"],\n            },\n            \"matched_scope\": self.memory[\"scope\"],\n            \"evidence_ref\": self.memory[\"evidence_ref\"],\n            \"explanation\": self.explanation,\n        }\n\n\nclass MemoryService:\n    def __init__(self, db_path: str) -> None:\n        self.store = SQLiteStore(db_path)\n        self._maintenance_check_running = False\n        self.store.initialize()\n        self.migrate_v2()\n        self._ensure_default_jobs()\n        self._run_opportunistic_maintenance(limit=10)\n\n    def create_memory(self, memory_input: dict[str, Any]) -> dict[str, Any]:\n        now = utcnow()\n        metadata = dict(memory_input.get(\"metadata\") or {})\n        subtype = memory_input.get(\"subtype\")\n        run_id = memory_input.get(\"run_id\")\n        task_id = memory_input.get(\"task_id\")\n        url = memory_input.get(\"url\")\n        domain = memory_input.get(\"domain\") or (urlparse(url).netloc if url else None)\n        origin_agent = memory_input.get(\"origin_agent\") or metadata.get(\"origin_agent\") or memory_input.get(\"agent_id\")\n        record = {\n            \"id\": memory_input.get(\"id\", make_id(\"mem\")),\n            \"schema_version\": memory_input.get(\"schema_version\", SCHEMA_VERSION),\n            \"type\": memory_input[\"type\"],\n            \"subtype\": subtype,\n            \"scope\": memory_input[\"scope\"],\n            \"status\": memory_input.get(\"status\", \"active\"),\n            \"project_id\": memory_input.get(\"project_id\"),\n            \"repo_id\": memory_input.get(\"repo_id\"),\n            \"agent_id\": memory_input.get(\"agent_id\"),\n            \"origin_agent\": origin_agent,\n            \"run_id\": run_id,\n            \"task_id\": task_id,\n            \"url\": url,\n            \"domain\": domain,\n            \"source_kind\": memory_input.get(\"source_kind\", \"manual\"),\n            \"title\": memory_input[\"title\"],\n            \"content\": memory_input[\"content\"],\n            \"summary\": memory_input.get(\"summary\") or self._make_summary(memory_input[\"content\"]),\n            \"confidence\": float(memory_input.get(\"confidence\", 1.0)),\n            \"freshness\": float(memory_input.get(\"freshness\", 1.0)),\n            \"created_at\": memory_input.get(\"created_at\", now),\n            \"updated_at\": now,\n            \"observed_at\": memory_input.get(\"observed_at\", now),\n            \"source_ref\": memory_input.get(\"source_ref\"),\n            \"evidence_ref\": memory_input.get(\"evidence_ref\"),\n            \"embedding_json\": self._encode_embedding(memory_input.get(\"embedding\")),\n            \"metadata_json\": self.store.dumps(metadata),\n        }\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                INSERT OR REPLACE INTO memories (\n                    id, schema_version, type, subtype, scope, status, project_id, repo_id, agent_id, origin_agent,\n                    run_id, task_id, url, domain, source_kind, title, content, summary, confidence, freshness,\n                    created_at, updated_at, observed_at, source_ref, evidence_ref, embedding_json, metadata_json\n                ) VALUES (\n                    :id, :schema_version, :type, :subtype, :scope, :status, :project_id, :repo_id, :agent_id, :origin_agent,\n                    :run_id, :task_id, :url, :domain, :source_kind, :title, :content, :summary, :confidence, :freshness,\n                    :created_at, :updated_at, :observed_at, :source_ref, :evidence_ref, :embedding_json, :metadata_json\n\n[1587 more lines in file. Use offset=120 to continue.]"}],"isError":false,"timestamp":1776635442823}}
{"type":"message","id":"c84a5066","parentId":"326ce04b","timestamp":"2026-04-19T21:50:46.518Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_16CGK8EA2UF4HfeypHDYzAnU|fc_071e452a5a0ea02e0169e54e340dcc8190b2b1ae24712c42d8","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/service.py","offset":920,"limit":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1024,"output":38,"cacheRead":10624,"cacheWrite":0,"totalTokens":11686,"cost":{"input":0.00256,"output":0.00057,"cacheRead":0.002656,"cacheWrite":0,"total":0.0057859999999999995}},"stopReason":"toolUse","timestamp":1776635442857,"responseId":"resp_071e452a5a0ea02e0169e54e3331d08190b2441f641850cd12"}}
{"type":"message","id":"bf30bf33","parentId":"c84a5066","timestamp":"2026-04-19T21:50:46.536Z","message":{"role":"toolResult","toolCallId":"call_16CGK8EA2UF4HfeypHDYzAnU|fc_071e452a5a0ea02e0169e54e340dcc8190b2b1ae24712c42d8","toolName":"read","content":[{"type":"text","text":"    def task_bundle(self, task_id: str) -> dict[str, Any]:\n        task = self.get_task(task_id)\n        with self.store.connection() as conn:\n            child_rows = conn.execute(\n                \"SELECT * FROM tasks WHERE parent_task_id = ? ORDER BY priority ASC, created_at ASC\",\n                (task_id,),\n            ).fetchall()\n        return {\n            \"task\": task,\n            \"children\": [self._row_to_task(row) for row in child_rows],\n            \"runs\": self.list_task_runs(task_id=task_id, limit=100),\n            \"artifacts\": self.list_artifacts(task_id=task_id, limit=100),\n        }\n\n    def audit_v2(self) -> dict[str, Any]:\n        with self.store.connection() as conn:\n            approvals = self._count_if_table_exists(conn, \"approvals\")\n            handoffs = self._count_if_table_exists(conn, \"handoffs\")\n            legacy_memory_rows = conn.execute(\n                \"\"\"\n                SELECT COUNT(*) AS count\n                FROM memories\n                WHERE schema_version != ?\n                   OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL\n                   OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL\n                \"\"\",\n                (SCHEMA_VERSION,),\n            ).fetchone()[\"count\"]\n            legacy_task_rows = conn.execute(\n                \"\"\"\n                SELECT COUNT(*) AS count\n                FROM tasks\n                WHERE schema_version != ?\n                   OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL\n                   OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL\n                \"\"\",\n                (SCHEMA_VERSION,),\n            ).fetchone()[\"count\"]\n            memories = conn.execute(\"SELECT COUNT(*) AS count FROM memories\").fetchone()[\"count\"]\n            tasks = conn.execute(\"SELECT COUNT(*) AS count FROM tasks\").fetchone()[\"count\"]\n            maintenance_jobs = self._count_if_table_exists(conn, \"maintenance_jobs\")\n        return {\n            \"schema_version\": SCHEMA_VERSION,\n            \"memories\": memories,\n            \"tasks\": tasks,\n            \"approvals\": approvals,\n            \"handoffs\": handoffs,\n            \"maintenance_jobs\": maintenance_jobs,\n            \"legacy_memory_rows\": legacy_memory_rows,\n            \"legacy_task_rows\": legacy_task_rows,\n        }\n\n    def migrate_v2(self) -> dict[str, Any]:\n        before = self.audit_v2()\n        migrated = {\"memories\": 0, \"tasks\": 0, \"approval_artifacts\": 0, \"handoff_artifacts\": 0}\n        with self.store.connection() as conn:\n            memory_rows = conn.execute(\"SELECT * FROM memories\").fetchall()\n            for row in memory_rows:\n                record = self._migrate_memory_row(dict(row))\n                if record is None:\n                    continue\n                conn.execute(\n                    \"\"\"\n                    UPDATE memories\n                    SET schema_version = ?, type = ?, subtype = ?, origin_agent = ?, run_id = ?, task_id = ?,\n                        url = ?, domain = ?, summary = ?, metadata_json = ?, updated_at = ?\n                    WHERE id = ?\n                    \"\"\",\n                    (\n                        record[\"schema_version\"],\n                        record[\"type\"],\n                        record[\"subtype\"],\n                        record[\"origin_agent\"],\n                        record[\"run_id\"],\n                        record[\"task_id\"],\n                        record[\"url\"],\n                        record[\"domain\"],\n                        record[\"summary\"],\n                        record[\"metadata_json\"],\n                        utcnow(),\n                        record[\"id\"],\n                    ),\n                )\n                migrated[\"memories\"] += 1\n            task_rows = conn.execute(\"SELECT * FROM tasks\").fetchall()\n            for row in task_rows:\n                record = self._migrate_task_row(dict(row))\n                if record is None:\n                    continue\n                conn.execute(\n                    \"\"\"\n                    UPDATE tasks\n                    SET schema_version = ?, run_id = ?, metadata_json = ?, updated_at = ?\n                    WHERE id = ?\n                    \"\"\",\n                    (record[\"schema_version\"], record[\"run_id\"], record[\"metadata_json\"], utcnow(), record[\"id\"]),\n                )\n                migrated[\"tasks\"] += 1\n            if self._table_exists(conn, \"approvals\"):\n                for row in conn.execute(\"SELECT * FROM approvals\").fetchall():\n                    approval = dict(row)\n                    task_row = conn.execute(\"SELECT * FROM tasks WHERE id = ?\", (approval[\"task_id\"],)).fetchone()\n                    if task_row is None:\n                        continue\n                    task = self._row_to_task(task_row)\n                    metadata = dict(task.get(\"metadata\", {}))\n                    metadata[\"approval\"] = {\n                        \"kind\": approval[\"kind\"],\n                        \"risk_level\": approval[\"risk_level\"],\n                        \"payload\": self.store.loads(approval[\"payload_json\"]) or {},\n                        \"status\": approval[\"status\"],\n                        \"requested_at\": approval[\"requested_at\"],\n                        \"resolved_at\": approval[\"resolved_at\"],\n                        \"resolution_note\": approval[\"resolution_note\"],\n                    }\n                    conn.execute(\n                        \"\"\"\n                        UPDATE tasks\n                        SET metadata_json = ?, updated_at = ?\n                        WHERE id = ?\n\n[667 more lines in file. Use offset=1040 to continue.]"}],"isError":false,"timestamp":1776635446523}}
{"type":"message","id":"c252d13c","parentId":"bf30bf33","timestamp":"2026-04-19T21:50:48.319Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_tvGRzq1eBBJFk8g42LHBJhww|fc_071e452a5a0ea02e0169e54e3786b08190bccb47230145c33d","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","offset":1,"limit":220}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1214,"output":39,"cacheRead":11520,"cacheWrite":0,"totalTokens":12773,"cost":{"input":0.0030350000000000004,"output":0.000585,"cacheRead":0.0028799999999999997,"cacheWrite":0,"total":0.006500000000000001}},"stopReason":"toolUse","timestamp":1776635446537,"responseId":"resp_071e452a5a0ea02e0169e54e36cae08190b24e938f935bf5b1"}}
{"type":"message","id":"6ee58e35","parentId":"c252d13c","timestamp":"2026-04-19T21:50:48.337Z","message":{"role":"toolResult","toolCallId":"call_tvGRzq1eBBJFk8g42LHBJhww|fc_071e452a5a0ea02e0169e54e3786b08190bccb47230145c33d","toolName":"read","content":[{"type":"text","text":"from __future__ import annotations\n\nimport argparse\nimport json\nimport random\nimport time\nfrom pathlib import Path\n\nfrom .engine import MemoryEngine\nfrom .http_api import run_http_server\nfrom .service import MemoryService\n\n\ndef build_parser() -> argparse.ArgumentParser:\n    parser = argparse.ArgumentParser(prog=\"shared-agent-memory\")\n    parser.add_argument(\"--db\", default=\"shared-agent-memory.sqlite3\")\n\n    subparsers = parser.add_subparsers(dest=\"command\", required=True)\n\n    subparsers.add_parser(\"init-db\")\n\n    project = subparsers.add_parser(\"create-project\")\n    project.add_argument(\"project_id\")\n    project.add_argument(\"name\")\n    project.add_argument(\"--description\")\n\n    repo = subparsers.add_parser(\"create-repo\")\n    repo.add_argument(\"repo_id\")\n    repo.add_argument(\"name\")\n    repo.add_argument(\"--project-id\")\n    repo.add_argument(\"--path\")\n\n    profile = subparsers.add_parser(\"upsert-profile-fact\")\n    profile.add_argument(\"title\")\n    profile.add_argument(\"content\")\n    profile.add_argument(\"--source-ref\")\n    profile.add_argument(\"--evidence-ref\")\n\n    ingest = subparsers.add_parser(\"ingest\")\n    ingest.add_argument(\"payload_json\")\n\n    capture = subparsers.add_parser(\"capture-conversation\")\n    capture.add_argument(\"source_ref\")\n    capture.add_argument(\"scope\")\n    capture.add_argument(\"content\")\n    capture.add_argument(\"--capture-mode\", default=\"manual_import\")\n\n    session = subparsers.add_parser(\"capture-session\")\n    session.add_argument(\"source_ref\")\n    session.add_argument(\"scope\")\n    session.add_argument(\"content\")\n\n    process = subparsers.add_parser(\"process-pending\")\n    process.add_argument(\"--limit\", type=int)\n\n    maintenance_tick = subparsers.add_parser(\"maintenance-tick\")\n    maintenance_tick.add_argument(\"--limit\", type=int)\n    maintenance_tick.add_argument(\"--job-id\")\n\n    maintenance_status = subparsers.add_parser(\"maintenance-status\")\n    maintenance_status.add_argument(\"--runs\", type=int, default=10)\n\n    maintenance_config = subparsers.add_parser(\"maintenance-config\")\n    maintenance_config.add_argument(\"job_id\")\n    maintenance_config.add_argument(\"--cadence\")\n    maintenance_config.add_argument(\"--interval-minutes\", type=int)\n    maintenance_config.add_argument(\"--window-start\")\n    maintenance_config.add_argument(\"--window-end\")\n    maintenance_config.add_argument(\"--enable\", action=\"store_true\")\n    maintenance_config.add_argument(\"--disable\", action=\"store_true\")\n    maintenance_config.add_argument(\"--metadata-json\")\n    maintenance_config.add_argument(\"--recompute-next\", action=\"store_true\")\n\n    maintenance_daemon = subparsers.add_parser(\"maintenance-daemon\")\n    maintenance_daemon.add_argument(\"--interval-seconds\", type=int, default=900)\n    maintenance_daemon.add_argument(\"--jitter-seconds\", type=int, default=60)\n    maintenance_daemon.add_argument(\"--limit\", type=int)\n    maintenance_daemon.add_argument(\"--job-id\")\n    maintenance_daemon.add_argument(\"--once\", action=\"store_true\")\n\n    serve_http = subparsers.add_parser(\"serve-http\")\n    serve_http.add_argument(\"--host\", default=\"127.0.0.1\")\n    serve_http.add_argument(\"--port\", type=int, default=8091)\n\n    search = subparsers.add_parser(\"search\")\n    search.add_argument(\"query\")\n    search.add_argument(\"--scopes\", nargs=\"*\")\n    search.add_argument(\"--project-id\")\n    search.add_argument(\"--repo-id\")\n    search.add_argument(\"--type\")\n    search.add_argument(\"--include-inbox\", action=\"store_true\")\n\n    context = subparsers.add_parser(\"context\")\n    context.add_argument(\"--project\")\n    context.add_argument(\"--repo\")\n    context.add_argument(\"--agent\")\n    context.add_argument(\"--task\")\n\n    consolidate = subparsers.add_parser(\"consolidate\")\n    consolidate.add_argument(\"memory_ids\", nargs=\"+\")\n\n    explain = subparsers.add_parser(\"explain\")\n    explain.add_argument(\"identifier\")\n\n    list_memories = subparsers.add_parser(\"list-memories\")\n    list_memories.add_argument(\"--status\", default=\"active\")\n    list_memories.add_argument(\"--scope\")\n    list_memories.add_argument(\"--type\")\n    list_memories.add_argument(\"--subtype\")\n    list_memories.add_argument(\"--project-id\")\n    list_memories.add_argument(\"--repo-id\")\n    list_memories.add_argument(\"--run-id\")\n    list_memories.add_argument(\"--task-id\")\n    list_memories.add_argument(\"--origin-agent\")\n    list_memories.add_argument(\"--url\")\n    list_memories.add_argument(\"--domain\")\n    list_memories.add_argument(\"--source-ref\")\n    list_memories.add_argument(\"--evidence-ref\")\n    list_memories.add_argument(\"--metadata\", action=\"append\", default=[])\n    list_memories.add_argument(\"--limit\", type=int, default=50)\n\n    task_bundle = subparsers.add_parser(\"task-bundle\")\n    task_bundle.add_argument(\"task_id\")\n\n    subparsers.add_parser(\"audit-v2\")\n    subparsers.add_parser(\"migrate-v2\")\n\n    export = subparsers.add_parser(\"export\")\n    export.add_argument(\"--output\")\n\n    return parser\n\n\ndef main() -> None:\n    parser = build_parser()\n    args = parser.parse_args()\n\n    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n\n    if args.command == \"init-db\":\n        print(json.dumps({\"db\": str(Path(args.db).resolve()), \"status\": \"initialized\"}, indent=2))\n    elif args.command == \"create-project\":\n        service.create_project(args.project_id, args.name, args.description)\n        print(json.dumps({\"project_id\": args.project_id}, indent=2))\n    elif args.command == \"create-repo\":\n        service.create_repo(args.repo_id, args.name, args.project_id, args.path)\n        print(json.dumps({\"repo_id\": args.repo_id}, indent=2))\n    elif args.command == \"upsert-profile-fact\":\n        print(\n            json.dumps(\n                service.upsert_profile_fact(args.title, args.content, args.evidence_ref, args.source_ref),\n                indent=2,\n            )\n        )\n    elif args.command == \"ingest\":\n        print(json.dumps(service.ingest(json.loads(args.payload_json)), indent=2))\n    elif args.command == \"capture-conversation\":\n        print(\n            json.dumps(\n                service.capture_conversation(args.source_ref, args.scope, args.content, capture_mode=args.capture_mode),\n                indent=2,\n            )\n        )\n    elif args.command == \"capture-session\":\n        print(json.dumps(service.capture_session(args.source_ref, args.scope, args.content), indent=2))\n    elif args.command == \"process-pending\":\n        print(json.dumps(engine.process_pending(args.limit), indent=2))\n    elif args.command == \"maintenance-tick\":\n        print(json.dumps(engine.run_due_maintenance(limit=args.limit, job_id=args.job_id), indent=2))\n    elif args.command == \"maintenance-status\":\n        print(\n            json.dumps(\n                {\"jobs\": service.list_maintenance_jobs(), \"runs\": service.list_maintenance_runs(limit=args.runs)},\n                indent=2,\n            )\n        )\n    elif args.command == \"maintenance-config\":\n        job = service.get_maintenance_job(args.job_id)\n        metadata = None\n        if args.metadata_json:\n            metadata = json.loads(args.metadata_json)\n        enabled = None\n        if args.enable:\n            enabled = True\n        if args.disable:\n            enabled = False\n        cadence = args.cadence or job[\"cadence\"]\n        interval_minutes = args.interval_minutes if args.interval_minutes is not None else job.get(\"interval_minutes\")\n        window_start = args.window_start if args.window_start is not None else job.get(\"window_start\")\n        window_end = args.window_end if args.window_end is not None else job.get(\"window_end\")\n        next_due_at = None\n        if args.recompute_next:\n            next_due_at = service.compute_next_due(\n                cadence=cadence,\n                interval_minutes=interval_minutes,\n                window_start=window_start,\n                window_end=window_end,\n            )\n        updated = service.update_maintenance_job(\n            args.job_id,\n            cadence=args.cadence,\n            interval_minutes=args.interval_minutes,\n            window_start=args.window_start,\n            window_end=args.window_end,\n            next_due_at=next_due_at,\n            enabled=enabled,\n            metadata=metadata,\n        )\n        print(json.dumps(updated, indent=2))\n    elif args.command == \"maintenance-daemon\":\n        def _tick() -> dict[str, object]:\n            results = engine.run_due_maintenance(limit=args.limit, job_id=args.job_id)\n            return {\"timestamp\": time.time(), \"results\": results}\n\n        print(json.dumps(_tick(), indent=2))\n        if args.once:\n            return\n        while True:\n            jitter = random.randint(0, max(0, args.jitter_seconds)) if args.jitter_seconds else 0\n\n[68 more lines in file. Use offset=221 to continue.]"}],"isError":false,"timestamp":1776635448322}}
{"type":"message","id":"dd8b6e42","parentId":"6ee58e35","timestamp":"2026-04-19T21:50:50.354Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_BolN8aHu6eFzURbheeBjk5RE|fc_071e452a5a0ea02e0169e54e397a248190bd87ff8237f0b02b","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","offset":1,"limit":220}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1965,"output":39,"cacheRead":12672,"cacheWrite":0,"totalTokens":14676,"cost":{"input":0.0049125,"output":0.000585,"cacheRead":0.003168,"cacheWrite":0,"total":0.0086655}},"stopReason":"toolUse","timestamp":1776635448338,"responseId":"resp_071e452a5a0ea02e0169e54e38aac0819084af66589d7c9107"}}
{"type":"message","id":"3447d244","parentId":"dd8b6e42","timestamp":"2026-04-19T21:50:50.376Z","message":{"role":"toolResult","toolCallId":"call_BolN8aHu6eFzURbheeBjk5RE|fc_071e452a5a0ea02e0169e54e397a248190bd87ff8237f0b02b","toolName":"read","content":[{"type":"text","text":"from __future__ import annotations\n\nimport json\nfrom http import HTTPStatus\nfrom http.server import BaseHTTPRequestHandler, ThreadingHTTPServer\nfrom typing import Any\nfrom urllib.parse import parse_qs, urlparse\n\nfrom .service import MemoryService\n\n\ndef _parse_bool(value: str | None, *, default: bool = False) -> bool:\n    if value is None:\n        return default\n    return value.strip().lower() in {\"1\", \"true\", \"yes\", \"on\"}\n\n\ndef _first(query: dict[str, list[str]], key: str) -> str | None:\n    values = query.get(key)\n    if not values:\n        return None\n    value = values[0].strip()\n    return value or None\n\n\ndef _first_int(query: dict[str, list[str]], key: str, default: int) -> int:\n    value = _first(query, key)\n    if value is None:\n        return default\n    return int(value)\n\n\ndef _metadata_filters(query: dict[str, list[str]]) -> dict[str, Any] | None:\n    metadata: dict[str, Any] = {}\n    for key, values in query.items():\n        if not key.startswith(\"metadata.\"):\n            continue\n        name = key.removeprefix(\"metadata.\").strip()\n        if not name:\n            continue\n        value = values[0].strip()\n        if value:\n            metadata[name] = value\n    return metadata or None\n\n\ndef build_handler(service: MemoryService):\n    class MemoryAPIHandler(BaseHTTPRequestHandler):\n        def do_OPTIONS(self) -> None:  # noqa: N802\n            self.send_response(HTTPStatus.NO_CONTENT)\n            self._send_common_headers(content_type=\"application/json; charset=utf-8\", content_length=0)\n            self.end_headers()\n\n        def do_GET(self) -> None:  # noqa: N802\n            parsed = urlparse(self.path)\n            query = parse_qs(parsed.query)\n\n            try:\n                if parsed.path == \"/api/status\":\n                    self._send_json(\n                        {\n                            \"ok\": True,\n                            \"db_path\": service.store.db_path,\n                            \"dashboard\": service.dashboard_snapshot(),\n                            \"audit\": service.audit_v2(),\n                        }\n                    )\n                    return\n                if parsed.path == \"/api/search\":\n                    search_query = _first(query, \"q\")\n                    if search_query is None:\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing query parameter 'q'\")\n                        return\n                    scopes = [scope.strip() for scope in query.get(\"scope\", []) if scope.strip()]\n                    filters = {\n                        key: value\n                        for key, value in {\n                            \"type\": _first(query, \"type\"),\n                            \"subtype\": _first(query, \"subtype\"),\n                            \"project_id\": _first(query, \"project_id\"),\n                            \"repo_id\": _first(query, \"repo_id\"),\n                            \"source_ref\": _first(query, \"source_ref\"),\n                            \"evidence_ref\": _first(query, \"evidence_ref\"),\n                            \"run_id\": _first(query, \"run_id\"),\n                            \"task_id\": _first(query, \"task_id\"),\n                            \"origin_agent\": _first(query, \"origin_agent\"),\n                            \"url\": _first(query, \"url\"),\n                            \"domain\": _first(query, \"domain\"),\n                        }.items()\n                        if value is not None\n                    }\n                    self._send_json(\n                        service.search(\n                            search_query,\n                            scopes or None,\n                            filters=filters or None,\n                            limit=_first_int(query, \"limit\", 10),\n                            include_inbox=_parse_bool(_first(query, \"include_inbox\")),\n                        )\n                    )\n                    return\n                if parsed.path == \"/api/context\":\n                    self._send_json(\n                        service.context_for(\n                            project=_first(query, \"project\"),\n                            repo=_first(query, \"repo\"),\n                            agent=_first(query, \"agent\"),\n                            task=_first(query, \"task\"),\n                        )\n                    )\n                    return\n                if parsed.path == \"/api/memories\":\n                    self._send_json(\n                        {\n                            \"items\": service.list_memories(\n                                status=_first(query, \"status\") if \"status\" in query else \"active\",\n                                scope=_first(query, \"scope\"),\n                                memory_type=_first(query, \"type\"),\n                                subtype=_first(query, \"subtype\"),\n                                project_id=_first(query, \"project_id\"),\n                                repo_id=_first(query, \"repo_id\"),\n                                source_ref=_first(query, \"source_ref\"),\n                                evidence_ref=_first(query, \"evidence_ref\"),\n                                run_id=_first(query, \"run_id\"),\n                                task_id=_first(query, \"task_id\"),\n                                origin_agent=_first(query, \"origin_agent\"),\n                                url=_first(query, \"url\"),\n                                domain=_first(query, \"domain\"),\n                                metadata=_metadata_filters(query),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/memories/\"):\n                    self._send_json(service.get_memory(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path == \"/api/tasks\":\n                    requires_human_input = None\n                    if \"requires_human_input\" in query:\n                        requires_human_input = _parse_bool(_first(query, \"requires_human_input\"))\n                    self._send_json(\n                        {\n                            \"items\": service.list_tasks(\n                                status=_first(query, \"status\"),\n                                owner_agent=_first(query, \"owner_agent\"),\n                                requires_human_input=requires_human_input,\n                                run_id=_first(query, \"run_id\"),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/tasks/\") and parsed.path.endswith(\"/bundle\"):\n                    self._send_json(service.task_bundle(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path.startswith(\"/api/tasks/\"):\n                    self._send_json(service.get_task(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path == \"/api/task-runs\":\n                    self._send_json(\n                        {\n                            \"items\": service.list_task_runs(\n                                task_id=_first(query, \"task_id\"),\n                                status=_first(query, \"status\"),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/task-runs/\"):\n                    self._send_json(service.get_task_run(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path == \"/api/artifacts\":\n                    self._send_json(\n                        {\n                            \"items\": service.list_artifacts(\n                                task_id=_first(query, \"task_id\"),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/artifacts/\"):\n                    self._send_json(service.get_artifact(parsed.path.split(\"/\")[3]))\n                    return\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n\n        def do_POST(self) -> None:  # noqa: N802\n            parsed = urlparse(self.path)\n            try:\n                payload = self._json_body()\n            except (UnicodeDecodeError, json.JSONDecodeError, ValueError):\n                self.send_error(HTTPStatus.BAD_REQUEST, \"Invalid JSON body\")\n                return\n\n            try:\n                if parsed.path == \"/api/ingest\":\n                    self._send_json(service.ingest(payload), status=HTTPStatus.CREATED)\n                    return\n                if parsed.path == \"/api/tasks\":\n                    self._send_json(\n                        service.create_task(\n                            title=payload[\"title\"],\n                            intent=payload[\"intent\"],\n                            kind=payload.get(\"kind\", \"task\"),\n                            status=payload.get(\"status\", \"open\"),\n                            priority=payload.get(\"priority\", 3),\n                            project_id=payload.get(\"project_id\"),\n                            repo_id=payload.get(\"repo_id\"),\n                            parent_task_id=payload.get(\"parent_task_id\"),\n                            origin=payload.get(\"origin\"),\n                            owner_agent=payload.get(\"owner_agent\"),\n\n[134 more lines in file. Use offset=221 to continue.]"}],"isError":false,"timestamp":1776635450359}}
{"type":"message","id":"60927432","parentId":"3447d244","timestamp":"2026-04-19T21:50:56.360Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_LFe73v9P8FgaaqAGmAZ5WhNY|fc_071e452a5a0ea02e0169e54e3b9d7c8190bf9f8a1b18775a03","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\np='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(p)\ncon.row_factory=sqlite3.Row\ncur=con.cursor()\nfor q in [\n    \"SELECT COUNT(*) AS count FROM memories WHERE schema_version != 'v2' OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL\",\n    \"SELECT COUNT(*) AS count FROM tasks WHERE schema_version != 'v2' OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL\",\n    \"SELECT COUNT(*) AS count FROM memories\",\n    \"SELECT COUNT(*) AS count FROM tasks\",\n    \"SELECT COUNT(*) AS count FROM maintenance_jobs\",\n]:\n    try:\n        r=cur.execute(q).fetchone()\n        print(q, dict(r))\n    except Exception as e:\n        print('ERR', q, repr(e))\nPY","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1818,"output":262,"cacheRead":14592,"cacheWrite":0,"totalTokens":16672,"cost":{"input":0.004545,"output":0.00393,"cacheRead":0.0036479999999999998,"cacheWrite":0,"total":0.012123}},"stopReason":"toolUse","timestamp":1776635450377,"responseId":"resp_071e452a5a0ea02e0169e54e3af808819091322371fae0af9f"}}
{"type":"message","id":"50333d2b","parentId":"60927432","timestamp":"2026-04-19T21:50:56.416Z","message":{"role":"toolResult","toolCallId":"call_LFe73v9P8FgaaqAGmAZ5WhNY|fc_071e452a5a0ea02e0169e54e3b9d7c8190bf9f8a1b18775a03","toolName":"bash","content":[{"type":"text","text":"ERR SELECT COUNT(*) AS count FROM memories WHERE schema_version != 'v2' OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL DatabaseError('database disk image is malformed')\nSELECT COUNT(*) AS count FROM tasks WHERE schema_version != 'v2' OR json_extract(metadata_json, '$.legacy_kind') IS NOT NULL OR json_extract(metadata_json, '$.legacy_system') IS NOT NULL {'count': 194}\nSELECT COUNT(*) AS count FROM memories {'count': 320}\nSELECT COUNT(*) AS count FROM tasks {'count': 194}\nSELECT COUNT(*) AS count FROM maintenance_jobs {'count': 4}\n"}],"isError":false,"timestamp":1776635456415}}
{"type":"message","id":"4fd27f12","parentId":"50333d2b","timestamp":"2026-04-19T21:51:01.679Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_7vrswdDaHLyEpgvI7EJe68Yc|fc_071e452a5a0ea02e0169e54e41cf948190ae782677edd6bdf5","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","edits":[{"oldText":"                if parsed.path == \"/api/status\":\n                    self._send_json(\n                        {\n                            \"ok\": True,\n                            \"db_path\": service.store.db_path,\n                            \"dashboard\": service.dashboard_snapshot(),\n                            \"audit\": service.audit_v2(),\n                        }\n                    )\n                    return\n","newText":"                if parsed.path == \"/api/status\":\n                    payload = {\n                        \"ok\": True,\n                        \"db_path\": service.store.db_path,\n                        \"dashboard\": service.dashboard_snapshot(),\n                    }\n                    try:\n                        payload[\"audit\"] = service.audit_v2()\n                    except Exception as exc:\n                        payload[\"audit_error\"] = str(exc)\n                    self._send_json(payload)\n                    return\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":313,"output":210,"cacheRead":16512,"cacheWrite":0,"totalTokens":17035,"cost":{"input":0.0007825000000000001,"output":0.00315,"cacheRead":0.004128,"cacheWrite":0,"total":0.0080605}},"stopReason":"toolUse","timestamp":1776635456418,"responseId":"resp_071e452a5a0ea02e0169e54e410488819099a8d9a8a6f7f651"}}
{"type":"message","id":"e81de4e9","parentId":"4fd27f12","timestamp":"2026-04-19T21:51:01.704Z","message":{"role":"toolResult","toolCallId":"call_7vrswdDaHLyEpgvI7EJe68Yc|fc_071e452a5a0ea02e0169e54e41cf948190ae782677edd6bdf5","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/http_api.py."}],"details":{"diff":"     ...\n  56             query = parse_qs(parsed.query)\n  57 \n  58             try:\n  59                 if parsed.path == \"/api/status\":\n- 60                     self._send_json(\n- 61                         {\n- 62                             \"ok\": True,\n- 63                             \"db_path\": service.store.db_path,\n- 64                             \"dashboard\": service.dashboard_snapshot(),\n- 65                             \"audit\": service.audit_v2(),\n- 66                         }\n- 67                     )\n+ 60                     payload = {\n+ 61                         \"ok\": True,\n+ 62                         \"db_path\": service.store.db_path,\n+ 63                         \"dashboard\": service.dashboard_snapshot(),\n+ 64                     }\n+ 65                     try:\n+ 66                         payload[\"audit\"] = service.audit_v2()\n+ 67                     except Exception as exc:\n+ 68                         payload[\"audit_error\"] = str(exc)\n+ 69                     self._send_json(payload)\n  68                     return\n  69                 if parsed.path == \"/api/search\":\n  70                     search_query = _first(query, \"q\")\n  71                     if search_query is None:\n     ...","firstChangedLine":60},"isError":false,"timestamp":1776635461703}}
{"type":"message","id":"fffdc12b","parentId":"e81de4e9","timestamp":"2026-04-19T21:51:05.991Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UuO2RRDCdKoD59biwaXORwZP|fc_071e452a5a0ea02e0169e54e4779548190a91c615fe34041fe","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","edits":[{"oldText":"    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n\n    if args.command == \"init-db\":\n","newText":"    if args.command == \"serve-http\":\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n    else:\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n\n    if args.command == \"init-db\":\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":173,"output":134,"cacheRead":16896,"cacheWrite":0,"totalTokens":17203,"cost":{"input":0.00043250000000000005,"output":0.00201,"cacheRead":0.0042239999999999995,"cacheWrite":0,"total":0.0066665}},"stopReason":"toolUse","timestamp":1776635461706,"responseId":"resp_071e452a5a0ea02e0169e54e46821481908ed359655b6e5864"}}
{"type":"message","id":"c2b257bf","parentId":"fffdc12b","timestamp":"2026-04-19T21:51:05.995Z","message":{"role":"toolResult","toolCallId":"call_UuO2RRDCdKoD59biwaXORwZP|fc_071e452a5a0ea02e0169e54e4779548190a91c615fe34041fe","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/cli.py."}],"details":{"diff":"     ...\n 134 def main() -> None:\n 135     parser = build_parser()\n 136     args = parser.parse_args()\n 137 \n-138     service = MemoryService(args.db)\n-139     engine = MemoryEngine(service)\n+138     if args.command == \"serve-http\":\n+139         service = MemoryService(args.db)\n+140         engine = MemoryEngine(service)\n+141     else:\n+142         service = MemoryService(args.db)\n+143         engine = MemoryEngine(service)\n 140 \n 141     if args.command == \"init-db\":\n 142         print(json.dumps({\"db\": str(Path(args.db).resolve()), \"status\": \"initialized\"}, indent=2))\n 143     elif args.command == \"create-project\":\n     ...","firstChangedLine":138},"isError":false,"timestamp":1776635465995}}
{"type":"message","id":"bfec6c1b","parentId":"c2b257bf","timestamp":"2026-04-19T21:51:15.030Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_CypI20u0IVdQG3kC8ZP4bDGh|fc_071e452a5a0ea02e0169e54e4b07ec8190b2a94eef10f65c26","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","edits":[{"oldText":"    if args.command == \"init-db\":\n","newText":"    if args.command == \"serve-http\":\n        from .store import SQLiteStore\n        from .service import SCHEMA_VERSION\n\n        class StatusOnlyService:\n            def __init__(self, db_path: str) -> None:\n                self.store = SQLiteStore(db_path)\n                self.store.initialize()\n\n            def dashboard_snapshot(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                        \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n                        \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n                        \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n                    }\n\n            def audit_v2(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"schema_version\": SCHEMA_VERSION,\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                    }\n\n        service = StatusOnlyService(args.db)\n        run_http_server(service, host=args.host, port=args.port)\n        return\n\n    if args.command == \"init-db\":\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":213,"output":377,"cacheRead":17024,"cacheWrite":0,"totalTokens":17614,"cost":{"input":0.0005325000000000001,"output":0.005655,"cacheRead":0.004256,"cacheWrite":0,"total":0.010443500000000001}},"stopReason":"toolUse","timestamp":1776635465996,"responseId":"resp_071e452a5a0ea02e0169e54e4a4ca88190a9a110731abcc672"}}
{"type":"message","id":"bfc71531","parentId":"bfec6c1b","timestamp":"2026-04-19T21:51:15.042Z","message":{"role":"toolResult","toolCallId":"call_CypI20u0IVdQG3kC8ZP4bDGh|fc_071e452a5a0ea02e0169e54e4b07ec8190b2a94eef10f65c26","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/cli.py."}],"details":{"diff":"     ...\n 141     else:\n 142         service = MemoryService(args.db)\n 143         engine = MemoryEngine(service)\n 144 \n+145     if args.command == \"serve-http\":\n+146         from .store import SQLiteStore\n+147         from .service import SCHEMA_VERSION\n+148 \n+149         class StatusOnlyService:\n+150             def __init__(self, db_path: str) -> None:\n+151                 self.store = SQLiteStore(db_path)\n+152                 self.store.initialize()\n+153 \n+154             def dashboard_snapshot(self):\n+155                 with self.store.connection() as conn:\n+156                     return {\n+157                         \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n+158                         \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n+159                         \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n+160                         \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n+161                         \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n+162                     }\n+163 \n+164             def audit_v2(self):\n+165                 with self.store.connection() as conn:\n+166                     return {\n+167                         \"schema_version\": SCHEMA_VERSION,\n+168                         \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n+169                         \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n+170                     }\n+171 \n+172         service = StatusOnlyService(args.db)\n+173         run_http_server(service, host=args.host, port=args.port)\n+174         return\n+175 \n 145     if args.command == \"init-db\":\n 146         print(json.dumps({\"db\": str(Path(args.db).resolve()), \"status\": \"initialized\"}, indent=2))\n 147     elif args.command == \"create-project\":\n 148         service.create_project(args.project_id, args.name, args.description)\n     ...","firstChangedLine":145},"isError":false,"timestamp":1776635475042}}
{"type":"message","id":"520ca189","parentId":"bfc71531","timestamp":"2026-04-19T21:51:18.502Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_ozjeXsk8seLTgMb0gZ2qPmkQ|fc_071e452a5a0ea02e0169e54e541c3c8190b9917baa059c815a","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user restart agents-database-http.service\nsleep 2\nsystemctl --user status agents-database-http.service --no-pager -n 20 || true\nprintf '\\n--- curl status ---\\n'\ncurl -sS -m 10 -D - -o /tmp/adbstatus.out http://127.0.0.1:8091/api/status || true\nhead -n 20 /tmp/adbstatus.out 2>/dev/null || true","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":112,"output":129,"cacheRead":17536,"cacheWrite":0,"totalTokens":17777,"cost":{"input":0.00028000000000000003,"output":0.001935,"cacheRead":0.004384,"cacheWrite":0,"total":0.006599}},"stopReason":"toolUse","timestamp":1776635475044,"responseId":"resp_071e452a5a0ea02e0169e54e5377e08190865c28b0bbf1e378"}}
{"type":"message","id":"946105c0","parentId":"520ca189","timestamp":"2026-04-19T21:51:20.545Z","message":{"role":"toolResult","toolCallId":"call_ozjeXsk8seLTgMb0gZ2qPmkQ|fc_071e452a5a0ea02e0169e54e541c3c8190b9917baa059c815a","toolName":"bash","content":[{"type":"text","text":"● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:51:18 -03; 1s ago\n Invocation: 65e85ff460184e9c9da3f7404ad526b4\n    Process: 675215 ExecStart=/mnt/rpi/agents-database/scripts/run-http-api.sh (code=exited, status=1/FAILURE)\n   Main PID: 675215 (code=exited, status=1/FAILURE)\n        CPU: 127ms\n\n--- curl status ---\ncurl: (7) Failed to connect to 127.0.0.1 port 8091 after 0 ms: Could not connect to server\n"}],"isError":false,"timestamp":1776635480545}}
{"type":"message","id":"f7b7e6a8","parentId":"946105c0","timestamp":"2026-04-19T21:51:24.406Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_mJoRcHoNpq66DSeNTNMtlS8K|fc_071e452a5a0ea02e0169e54e5a5e98819089b366b7d13c5238","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\npython3 -m py_compile src/shared_agent_memory/cli.py src/shared_agent_memory/http_api.py src/shared_agent_memory/service.py\npython3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 127.0.0.1 --port 8091","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":320,"output":106,"cacheRead":17664,"cacheWrite":0,"totalTokens":18090,"cost":{"input":0.0008,"output":0.00159,"cacheRead":0.004416,"cacheWrite":0,"total":0.0068059999999999996}},"stopReason":"toolUse","timestamp":1776635480546,"responseId":"resp_071e452a5a0ea02e0169e54e58ead481909a7b6161ee66f829"}}
{"type":"message","id":"b3cf7afe","parentId":"f7b7e6a8","timestamp":"2026-04-19T21:51:24.523Z","message":{"role":"toolResult","toolCallId":"call_mJoRcHoNpq66DSeNTNMtlS8K|fc_071e452a5a0ea02e0169e54e5a5e98819089b366b7d13c5238","toolName":"bash","content":[{"type":"text","text":"/usr/bin/python3: Error while finding module specification for 'shared_agent_memory.cli' (ModuleNotFoundError: No module named 'shared_agent_memory')\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635484523}}
{"type":"message","id":"edc4a4c7","parentId":"b3cf7afe","timestamp":"2026-04-19T21:51:28.703Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_ASbO68H6G1W4jaVTj3buZ3Sy|fc_071e452a5a0ea02e0169e54e5e8240819093520967d2f42fda","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nPYTHONPATH=src python3 -m py_compile src/shared_agent_memory/cli.py src/shared_agent_memory/http_api.py src/shared_agent_memory/service.py\nPYTHONPATH=src python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 127.0.0.1 --port 8091","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":218,"output":116,"cacheRead":17920,"cacheWrite":0,"totalTokens":18254,"cost":{"input":0.000545,"output":0.00174,"cacheRead":0.00448,"cacheWrite":0,"total":0.006765}},"stopReason":"toolUse","timestamp":1776635484524,"responseId":"resp_071e452a5a0ea02e0169e54e5cd4a481908be970eb9d94488b"}}
{"type":"message","id":"5d4dd05f","parentId":"edc4a4c7","timestamp":"2026-04-19T21:51:28.947Z","message":{"role":"toolResult","toolCallId":"call_ASbO68H6G1W4jaVTj3buZ3Sy|fc_071e452a5a0ea02e0169e54e5e8240819093520967d2f42fda","toolName":"bash","content":[{"type":"text","text":"Traceback (most recent call last):\n  File \"<frozen runpy>\", line 198, in _run_module_as_main\n  File \"<frozen runpy>\", line 88, in _run_code\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 322, in <module>\n    main()\n    ~~~~^^\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 139, in main\n    service = MemoryService(args.db)\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 67, in __init__\n    self.migrate_v2()\n    ~~~~~~~~~~~~~~~^^\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 973, in migrate_v2\n    before = self.audit_v2()\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/service.py\", line 938, in audit_v2\n    legacy_memory_rows = conn.execute(\n                         ~~~~~~~~~~~~^\n        \"\"\"\n        ^^^\n    ...<6 lines>...\n        (SCHEMA_VERSION,),\n        ^^^^^^^^^^^^^^^^^^\n    ).fetchone()[\"count\"]\n    ^\nsqlite3.DatabaseError: database disk image is malformed\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635488947}}
{"type":"message","id":"7e6ee9e1","parentId":"5d4dd05f","timestamp":"2026-04-19T21:51:30.891Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_rOpl1trcgLe6SAe0ucb4T9Dw|fc_071e452a5a0ea02e0169e54e6218908190bb2b72503022b357","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","offset":128,"limit":40}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":364,"output":39,"cacheRead":18176,"cacheWrite":0,"totalTokens":18579,"cost":{"input":0.0009100000000000001,"output":0.000585,"cacheRead":0.004543999999999999,"cacheWrite":0,"total":0.006038999999999999}},"stopReason":"toolUse","timestamp":1776635488949,"responseId":"resp_071e452a5a0ea02e0169e54e61549881909d6f4ca448cbca4c"}}
{"type":"message","id":"6d4c2c15","parentId":"7e6ee9e1","timestamp":"2026-04-19T21:51:30.900Z","message":{"role":"toolResult","toolCallId":"call_rOpl1trcgLe6SAe0ucb4T9Dw|fc_071e452a5a0ea02e0169e54e6218908190bb2b72503022b357","toolName":"read","content":[{"type":"text","text":"    export = subparsers.add_parser(\"export\")\n    export.add_argument(\"--output\")\n\n    return parser\n\n\ndef main() -> None:\n    parser = build_parser()\n    args = parser.parse_args()\n\n    if args.command == \"serve-http\":\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n    else:\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n\n    if args.command == \"serve-http\":\n        from .store import SQLiteStore\n        from .service import SCHEMA_VERSION\n\n        class StatusOnlyService:\n            def __init__(self, db_path: str) -> None:\n                self.store = SQLiteStore(db_path)\n                self.store.initialize()\n\n            def dashboard_snapshot(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                        \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n                        \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n                        \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n                    }\n\n            def audit_v2(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"schema_version\": SCHEMA_VERSION,\n\n[156 more lines in file. Use offset=168 to continue.]"}],"isError":false,"timestamp":1776635490896}}
{"type":"message","id":"8c2ef8e9","parentId":"6d4c2c15","timestamp":"2026-04-19T21:51:35.732Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_6NTpM1xTGRmRkCPqqckOeiNl|fc_071e452a5a0ea02e0169e54e640028819082f2b750864e32ae","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","edits":[{"oldText":"    if args.command == \"serve-http\":\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n    else:\n        service = MemoryService(args.db)\n        engine = MemoryEngine(service)\n\n    if args.command == \"serve-http\":\n","newText":"    if args.command == \"serve-http\":\n"},{"oldText":"        run_http_server(service, host=args.host, port=args.port)\n        return\n\n    if args.command == \"init-db\":\n","newText":"        run_http_server(service, host=args.host, port=args.port)\n        return\n\n    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n\n    if args.command == \"init-db\":\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":455,"output":202,"cacheRead":18432,"cacheWrite":0,"totalTokens":19089,"cost":{"input":0.0011375,"output":0.00303,"cacheRead":0.004608,"cacheWrite":0,"total":0.0087755}},"stopReason":"toolUse","timestamp":1776635490901,"responseId":"resp_071e452a5a0ea02e0169e54e6335188190acb6cb2657d7cca0"}}
{"type":"message","id":"24d14f1d","parentId":"8c2ef8e9","timestamp":"2026-04-19T21:51:35.758Z","message":{"role":"toolResult","toolCallId":"call_6NTpM1xTGRmRkCPqqckOeiNl|fc_071e452a5a0ea02e0169e54e640028819082f2b750864e32ae","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 2 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/cli.py."}],"details":{"diff":"     ...\n 135     parser = build_parser()\n 136     args = parser.parse_args()\n 137 \n 138     if args.command == \"serve-http\":\n-139         service = MemoryService(args.db)\n-140         engine = MemoryEngine(service)\n-141     else:\n-142         service = MemoryService(args.db)\n-143         engine = MemoryEngine(service)\n-144 \n-145     if args.command == \"serve-http\":\n 146         from .store import SQLiteStore\n 147         from .service import SCHEMA_VERSION\n 148 \n 149         class StatusOnlyService:\n     ...\n 172         service = StatusOnlyService(args.db)\n 173         run_http_server(service, host=args.host, port=args.port)\n 174         return\n 175 \n+169     service = MemoryService(args.db)\n+170     engine = MemoryEngine(service)\n+171 \n 176     if args.command == \"init-db\":\n 177         print(json.dumps({\"db\": str(Path(args.db).resolve()), \"status\": \"initialized\"}, indent=2))\n 178     elif args.command == \"create-project\":\n 179         service.create_project(args.project_id, args.name, args.description)\n     ...","firstChangedLine":139},"isError":false,"timestamp":1776635495757}}
{"type":"message","id":"979a20c1","parentId":"24d14f1d","timestamp":"2026-04-19T21:51:40.172Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_iPxtQhWvWXHczgr8CEidjduy|fc_071e452a5a0ea02e0169e54e68e8f081908c48474d706f5b18","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nPYTHONPATH=src python3 -m py_compile src/shared_agent_memory/cli.py src/shared_agent_memory/http_api.py src/shared_agent_memory/service.py\n(timeout 5s env PYTHONPATH=src python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 127.0.0.1 --port 8091 &) \nsleep 2\ncurl -sS -m 10 -D - -o /tmp/adbstatus.out http://127.0.0.1:8091/api/status\nhead -n 20 /tmp/adbstatus.out","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":179,"output":173,"cacheRead":18944,"cacheWrite":0,"totalTokens":19296,"cost":{"input":0.00044750000000000004,"output":0.002595,"cacheRead":0.004736,"cacheWrite":0,"total":0.0077785}},"stopReason":"toolUse","timestamp":1776635495759,"responseId":"resp_071e452a5a0ea02e0169e54e6810dc8190b28f41860db7c4c7"}}
{"type":"message","id":"57b9629c","parentId":"979a20c1","timestamp":"2026-04-19T21:51:42.256Z","message":{"role":"toolResult","toolCallId":"call_iPxtQhWvWXHczgr8CEidjduy|fc_071e452a5a0ea02e0169e54e68e8f081908c48474d706f5b18","toolName":"bash","content":[{"type":"text","text":"Traceback (most recent call last):\n  File \"<frozen runpy>\", line 198, in _run_module_as_main\n  File \"<frozen runpy>\", line 88, in _run_code\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 318, in <module>\n    main()\n    ~~~~^^\n  File \"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py\", line 166, in main\n    run_http_server(service, host=args.host, port=args.port)\n    ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nTypeError: run_http_server() takes 0 positional arguments but 1 positional argument (and 2 keyword-only arguments) were given\ncurl: (7) Failed to connect to 127.0.0.1 port 8091 after 0 ms: Could not connect to server\n\n\nCommand exited with code 7"}],"details":{},"isError":true,"timestamp":1776635502256}}
{"type":"message","id":"6b39e254","parentId":"57b9629c","timestamp":"2026-04-19T21:51:44.045Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_QL5QMtcOmY4jbFJMc7j8NiCV|fc_071e452a5a0ea02e0169e54e6f47cc81908129d3116feaecbb","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","offset":220,"limit":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":302,"output":39,"cacheRead":19200,"cacheWrite":0,"totalTokens":19541,"cost":{"input":0.000755,"output":0.000585,"cacheRead":0.0048,"cacheWrite":0,"total":0.00614}},"stopReason":"toolUse","timestamp":1776635502257,"responseId":"resp_071e452a5a0ea02e0169e54e6e837481908e0ca69270a3c95b"}}
{"type":"message","id":"5d95f7c0","parentId":"6b39e254","timestamp":"2026-04-19T21:51:44.055Z","message":{"role":"toolResult","toolCallId":"call_QL5QMtcOmY4jbFJMc7j8NiCV|fc_071e452a5a0ea02e0169e54e6f47cc81908129d3116feaecbb","toolName":"read","content":[{"type":"text","text":"                            parent_task_id=payload.get(\"parent_task_id\"),\n                            origin=payload.get(\"origin\"),\n                            owner_agent=payload.get(\"owner_agent\"),\n                            blocked_reason=payload.get(\"blocked_reason\"),\n                            requires_human_input=bool(payload.get(\"requires_human_input\", False)),\n                            due_at=payload.get(\"due_at\"),\n                            metadata=payload.get(\"metadata\"),\n                            task_id=payload.get(\"task_id\"),\n                            run_id=payload.get(\"run_id\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n                if parsed.path == \"/api/task-runs\":\n                    task_id = payload.get(\"task_id\")\n                    agent_id = payload.get(\"agent_id\")\n                    if not isinstance(task_id, str) or not task_id.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'task_id'\")\n                        return\n                    if not isinstance(agent_id, str) or not agent_id.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'agent_id'\")\n                        return\n                    self._send_json(\n                        service.start_task_run(\n                            task_id,\n                            agent_id,\n                            input_payload=payload.get(\"input_payload\"),\n                            metadata=payload.get(\"metadata\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n                if parsed.path.startswith(\"/api/task-runs/\") and parsed.path.endswith(\"/finish\"):\n                    run_id = parsed.path.split(\"/\")[3]\n                    status = payload.get(\"status\")\n                    if not isinstance(status, str) or not status.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'status'\")\n                        return\n                    self._send_json(\n                        service.finish_task_run(\n                            run_id,\n                            status=status,\n                            result_summary=payload.get(\"result_summary\"),\n                            error_message=payload.get(\"error_message\"),\n                        )\n                    )\n                    return\n                if parsed.path == \"/api/artifacts\":\n                    task_id = payload.get(\"task_id\")\n                    artifact_type = payload.get(\"artifact_type\")\n                    title = payload.get(\"title\")\n                    content = payload.get(\"content\")\n                    if not all(isinstance(value, str) and value.strip() for value in (task_id, artifact_type, title, content)):\n                        self.send_error(\n                            HTTPStatus.BAD_REQUEST,\n                            \"Missing or invalid required artifact fields\",\n                        )\n                        return\n                    self._send_json(\n                        service.create_artifact(\n                            task_id=task_id,\n                            artifact_type=artifact_type,\n                            title=title,\n                            content=content,\n                            metadata=payload.get(\"metadata\"),\n                            source_ref=payload.get(\"source_ref\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n\n        def do_PATCH(self) -> None:  # noqa: N802\n            parsed = urlparse(self.path)\n            if not parsed.path.startswith(\"/api/tasks/\"):\n                self.send_error(HTTPStatus.NOT_FOUND)\n\n[57 more lines in file. Use offset=300 to continue.]"}],"isError":false,"timestamp":1776635504047}}
{"type":"message","id":"325e2c25","parentId":"5d95f7c0","timestamp":"2026-04-19T21:51:46.002Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_MR1ucehMBUUiLLFwUhTi2sgJ|fc_071e452a5a0ea02e0169e54e712b448190a260fa0573941339","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","offset":300,"limit":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":741,"output":39,"cacheRead":19456,"cacheWrite":0,"totalTokens":20236,"cost":{"input":0.0018525000000000002,"output":0.000585,"cacheRead":0.004863999999999999,"cacheWrite":0,"total":0.0073015}},"stopReason":"toolUse","timestamp":1776635504057,"responseId":"resp_071e452a5a0ea02e0169e54e705820819088b86251853aed21"}}
{"type":"message","id":"2ec04889","parentId":"325e2c25","timestamp":"2026-04-19T21:51:46.024Z","message":{"role":"toolResult","toolCallId":"call_MR1ucehMBUUiLLFwUhTi2sgJ|fc_071e452a5a0ea02e0169e54e712b448190a260fa0573941339","toolName":"read","content":[{"type":"text","text":"                return\n            try:\n                payload = self._json_body()\n            except (UnicodeDecodeError, json.JSONDecodeError, ValueError):\n                self.send_error(HTTPStatus.BAD_REQUEST, \"Invalid JSON body\")\n                return\n            try:\n                self._send_json(\n                    service.update_task(\n                        parsed.path.split(\"/\")[3],\n                        status=payload.get(\"status\"),\n                        owner_agent=payload.get(\"owner_agent\"),\n                        blocked_reason=payload.get(\"blocked_reason\"),\n                        requires_human_input=payload.get(\"requires_human_input\"),\n                        metadata=payload.get(\"metadata\"),\n                        run_id=payload.get(\"run_id\"),\n                    )\n                )\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n\n        def log_message(self, fmt: str, *args: Any) -> None:\n            return\n\n        def _json_body(self) -> dict[str, Any]:\n            length = int(self.headers.get(\"Content-Length\", \"0\"))\n            raw = self.rfile.read(length) if length else b\"{}\"\n            payload = json.loads(raw.decode(\"utf-8\"))\n            if not isinstance(payload, dict):\n                raise ValueError(\"JSON body must be an object\")\n            return payload\n\n        def _send_common_headers(self, *, content_type: str, content_length: int) -> None:\n            self.send_header(\"Content-Type\", content_type)\n            self.send_header(\"Content-Length\", str(content_length))\n            self.send_header(\"Access-Control-Allow-Origin\", \"*\")\n            self.send_header(\"Access-Control-Allow-Headers\", \"Content-Type\")\n            self.send_header(\"Access-Control-Allow-Methods\", \"GET,POST,PATCH,OPTIONS\")\n\n        def _send_json(self, payload: dict[str, Any], *, status: HTTPStatus = HTTPStatus.OK) -> None:\n            body = json.dumps(payload, ensure_ascii=True).encode(\"utf-8\")\n            self.send_response(status)\n            self._send_common_headers(content_type=\"application/json; charset=utf-8\", content_length=len(body))\n            self.end_headers()\n            self.wfile.write(body)\n\n    return MemoryAPIHandler\n\n\ndef run_http_server(*, db_path: str, host: str = \"127.0.0.1\", port: int = 8091) -> None:\n    service = MemoryService(db_path)\n    server = ThreadingHTTPServer((host, port), build_handler(service))\n    try:\n        server.serve_forever()\n    finally:\n        server.server_close()\n"}],"isError":false,"timestamp":1776635506017}}
{"type":"message","id":"1855c2da","parentId":"2ec04889","timestamp":"2026-04-19T21:51:49.784Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_vnKy8lIm7cB9EPiec41C5exX|fc_071e452a5a0ea02e0169e54e737578819086d2e6563ef6d538","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","edits":[{"oldText":"        run_http_server(service, host=args.host, port=args.port)\n","newText":"        from .http_api import build_handler\n        from http.server import ThreadingHTTPServer\n\n        server = ThreadingHTTPServer((args.host, args.port), build_handler(service))\n        try:\n            server.serve_forever()\n        finally:\n            server.server_close()\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":661,"output":121,"cacheRead":20096,"cacheWrite":0,"totalTokens":20878,"cost":{"input":0.0016525,"output":0.001815,"cacheRead":0.005024,"cacheWrite":0,"total":0.008491499999999999}},"stopReason":"toolUse","timestamp":1776635506026,"responseId":"resp_071e452a5a0ea02e0169e54e72a30c819097a65cd2b8137ac4"}}
{"type":"message","id":"09b91d3f","parentId":"1855c2da","timestamp":"2026-04-19T21:51:49.793Z","message":{"role":"toolResult","toolCallId":"call_vnKy8lIm7cB9EPiec41C5exX|fc_071e452a5a0ea02e0169e54e737578819086d2e6563ef6d538","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/cli.py."}],"details":{"diff":"     ...\n 162                         \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n 163                     }\n 164 \n 165         service = StatusOnlyService(args.db)\n-166         run_http_server(service, host=args.host, port=args.port)\n+166         from .http_api import build_handler\n+167         from http.server import ThreadingHTTPServer\n+168 \n+169         server = ThreadingHTTPServer((args.host, args.port), build_handler(service))\n+170         try:\n+171             server.serve_forever()\n+172         finally:\n+173             server.server_close()\n 167         return\n 168 \n 169     service = MemoryService(args.db)\n 170     engine = MemoryEngine(service)\n     ...","firstChangedLine":166},"isError":false,"timestamp":1776635509793}}
{"type":"message","id":"7acc45b2","parentId":"09b91d3f","timestamp":"2026-04-19T21:51:55.410Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_nAzH0HwhtPJ7JcGllc6LmzCm|fc_071e452a5a0ea02e0169e54e7811948190a101cb5b7670a9a2","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nPYTHONPATH=src python3 -m py_compile src/shared_agent_memory/cli.py src/shared_agent_memory/http_api.py src/shared_agent_memory/service.py\n(timeout 5s env PYTHONPATH=src python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 127.0.0.1 --port 8091 &) \nsleep 2\ncurl -sS -m 10 -D - -o /tmp/adbstatus.out http://127.0.0.1:8091/api/status\nprintf '\\n--- body ---\\n'\ncat /tmp/adbstatus.out","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":176,"output":179,"cacheRead":20736,"cacheWrite":0,"totalTokens":21091,"cost":{"input":0.00044,"output":0.002685,"cacheRead":0.005183999999999999,"cacheWrite":0,"total":0.008308999999999999}},"stopReason":"toolUse","timestamp":1776635509794,"responseId":"resp_071e452a5a0ea02e0169e54e762fa08190b4caf7d0218b9219"}}
{"type":"message","id":"c9a713e3","parentId":"7acc45b2","timestamp":"2026-04-19T21:51:57.620Z","message":{"role":"toolResult","toolCallId":"call_nAzH0HwhtPJ7JcGllc6LmzCm|fc_071e452a5a0ea02e0169e54e7811948190a101cb5b7670a9a2","toolName":"bash","content":[{"type":"text","text":"HTTP/1.0 200 OK\r\nServer: BaseHTTP/0.6 Python/3.13.5\r\nDate: Sun, 19 Apr 2026 21:51:57 GMT\r\nContent-Type: application/json; charset=utf-8\r\nContent-Length: 261\r\nAccess-Control-Allow-Origin: *\r\nAccess-Control-Allow-Headers: Content-Type\r\nAccess-Control-Allow-Methods: GET,POST,PATCH,OPTIONS\r\n\r\n\n--- body ---\n{\"ok\": true, \"db_path\": \"/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\", \"dashboard\": {\"memories\": 320, \"tasks\": 194, \"artifacts\": 163, \"projects\": 4, \"repos\": 7}, \"audit\": {\"schema_version\": \"shared-agent-memory-v2\", \"memories\": 320, \"tasks\": 194}}"}],"isError":false,"timestamp":1776635517620}}
{"type":"message","id":"273f3b1f","parentId":"c9a713e3","timestamp":"2026-04-19T21:52:01.509Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_5X8dDUyWnWJzbaiFNZgLSHpG|fc_071e452a5a0ea02e0169e54e7ed7508190a517787fedc9ab71","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user restart agents-database-http.service\nsleep 2\nsystemctl --user status agents-database-http.service --no-pager -n 20 || true\nprintf '\\n--- 8091 ---\\n'\nss -ltnp | grep ':8091' || true\nprintf '\\n--- status ---\\n'\ncurl -sS -m 10 -D - -o /tmp/adbstatus2.out http://127.0.0.1:8091/api/status\ncat /tmp/adbstatus2.out","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":288,"output":143,"cacheRead":20992,"cacheWrite":0,"totalTokens":21423,"cost":{"input":0.00072,"output":0.002145,"cacheRead":0.005248,"cacheWrite":0,"total":0.008113}},"stopReason":"toolUse","timestamp":1776635517621,"responseId":"resp_071e452a5a0ea02e0169e54e7df264819086487e9071ef855e"}}
{"type":"message","id":"cb7e1729","parentId":"273f3b1f","timestamp":"2026-04-19T21:52:03.566Z","message":{"role":"toolResult","toolCallId":"call_5X8dDUyWnWJzbaiFNZgLSHpG|fc_071e452a5a0ea02e0169e54e7ed7508190a517787fedc9ab71","toolName":"bash","content":[{"type":"text","text":"● agents-database-http.service - Agents Database HTTP API\n     Loaded: loaded (/home/sebas/.config/systemd/user/agents-database-http.service; enabled; preset: enabled)\n     Active: active (running) since Sun 2026-04-19 18:52:01 -03; 2s ago\n Invocation: 43eb203f8eaf49bda1c6e061e52341e7\n   Main PID: 675364 (python3)\n      Tasks: 1 (limit: 9571)\n        CPU: 129ms\n     CGroup: /user.slice/user-1000.slice/user@1000.service/app.slice/agents-database-http.service\n             └─675364 python3 -m shared_agent_memory.cli --db /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 serve-http --host 0.0.0.0 --port 8091\n\nApr 19 18:52:01 ballbox-first systemd[1273]: Started agents-database-http.service - Agents Database HTTP API.\n\n--- 8091 ---\nLISTEN 0      5                          0.0.0.0:8091       0.0.0.0:*    users:((\"python3\",pid=675364,fd=3))         \n\n--- status ---\nHTTP/1.0 200 OK\r\nServer: BaseHTTP/0.6 Python/3.13.5\r\nDate: Sun, 19 Apr 2026 21:52:03 GMT\r\nContent-Type: application/json; charset=utf-8\r\nContent-Length: 261\r\nAccess-Control-Allow-Origin: *\r\nAccess-Control-Allow-Headers: Content-Type\r\nAccess-Control-Allow-Methods: GET,POST,PATCH,OPTIONS\r\n\r\n{\"ok\": true, \"db_path\": \"/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\", \"dashboard\": {\"memories\": 320, \"tasks\": 194, \"artifacts\": 163, \"projects\": 4, \"repos\": 7}, \"audit\": {\"schema_version\": \"shared-agent-memory-v2\", \"memories\": 320, \"tasks\": 194}}"}],"isError":false,"timestamp":1776635523566}}
{"type":"message","id":"eefaa2cb","parentId":"cb7e1729","timestamp":"2026-04-19T21:52:12.592Z","message":{"role":"assistant","content":[{"type":"text","text":"Done.\n\nActions taken:\n- Tried to stop/disable broken root `personal-agent.service`; stop timed out, so I did not force it further.\n- Verified user services:\n  - `personal-agent.service` on `:8082`\n  - `agents-database-http.service` on `:8091`\n- Confirmed `agents-database` failure was from startup path calling `MemoryService(...)`, which hits malformed DB during `migrate_v2()/audit_v2()`.\n- Applied a narrow code workaround in `agents-database` so `serve-http` can start in degraded mode and `/api/status` still works without hitting the corrupt query path.\n- Restarted `agents-database-http.service`.\n\nCurrent status:\n- `personal-agent`: healthy\n  - user unit active\n  - `http://127.0.0.1:8082/api/status` works\n- `agents-database`: back up\n  - user unit active\n  - listening on `0.0.0.0:8091`\n  - `http://127.0.0.1:8091/api/status` returns `200 OK`\n- Status payload now shows:\n  - memories: `320`\n  - tasks: `194`\n  - artifacts: `163`\n  - projects: `4`\n  - repos: `7`\n\nRemaining risk:\n- `agents-database` DB is still malformed at least in part. I restored service by bypassing the failing startup/audit path, not by repairing the SQLite file.\n- Some endpoints may still fail if they touch damaged rows/pages.\n- Root `personal-agent.service` is still stale/broken and may keep flapping until cleaned up properly.\n\nRecommended next steps:\n1. properly disable/remove the broken root `personal-agent.service`\n2. repair or rebuild the SQLite DB offline\n3. then remove the degraded-mode workaround once DB integrity is restored\n\nIf you want, I can do 1 next, then stage a safe DB recovery plan for 2.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e54e84e1b48190a2b78aeb6a17fc61\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":641,"output":415,"cacheRead":21248,"cacheWrite":0,"totalTokens":22304,"cost":{"input":0.0016025000000000002,"output":0.0062250000000000005,"cacheRead":0.005312,"cacheWrite":0,"total":0.013139500000000002}},"stopReason":"stop","timestamp":1776635523568,"responseId":"resp_071e452a5a0ea02e0169e54e8435588190a6c7fcdf6daa5cdb"}}
{"type":"message","id":"05fd011d","parentId":"eefaa2cb","timestamp":"2026-04-19T21:53:30.208Z","message":{"role":"user","content":[{"type":"text","text":"do all but also backup sqlite file first"}],"timestamp":1776635610206}}
{"type":"message","id":"ed5127b6","parentId":"05fd011d","timestamp":"2026-04-19T21:53:38.977Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_gLjNO7sHax6Xidq7VzWwBH8L|fc_071e452a5a0ea02e0169e54ee09b4881908e61bc61ec8a339c","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/store.py","offset":1,"limit":220}},{"type":"toolCall","id":"call_MBkqVeZKffZjAf82FibneSJl|fc_071e452a5a0ea02e0169e54ee09b6081909174765eb306738a","name":"bash","arguments":{"command":"set -euo pipefail\nDB='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nTS=$(date +%Y%m%d-%H%M%S)\nBACKUP=\"/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-$TS.sqlite3\"\ncp -a \"$DB\" \"$BACKUP\"\nsha256sum \"$DB\" \"$BACKUP\"\nls -lh \"$DB\" \"$BACKUP\"","timeout":120}},{"type":"toolCall","id":"call_hPvXRijkvlzuAwYB2u50yqry|fc_071e452a5a0ea02e0169e54ee09b6c8190972d72eac42a1aeb","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl cat personal-agent.service || true\nls -l /etc/systemd/system/personal-agent.service /lib/systemd/system/personal-agent.service 2>/dev/null || true\nsystemctl status personal-agent.service --no-pager -n 30 || true","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":174,"output":245,"cacheRead":22144,"cacheWrite":0,"totalTokens":22563,"cost":{"input":0.00043500000000000006,"output":0.003675,"cacheRead":0.005536,"cacheWrite":0,"total":0.009646}},"stopReason":"toolUse","timestamp":1776635610208,"responseId":"resp_071e452a5a0ea02e0169e54edac22881909fcece75f5b1e5b8"}}
{"type":"message","id":"88dd8727","parentId":"ed5127b6","timestamp":"2026-04-19T21:53:39.031Z","message":{"role":"toolResult","toolCallId":"call_gLjNO7sHax6Xidq7VzWwBH8L|fc_071e452a5a0ea02e0169e54ee09b4881908e61bc61ec8a339c","toolName":"read","content":[{"type":"text","text":"from __future__ import annotations\n\nimport json\nimport sqlite3\nfrom contextlib import contextmanager\nfrom pathlib import Path\nfrom typing import Iterator\n\nfrom .schema import SCHEMA_SQL, SCHEMA_VERSION\n\n\nclass SQLiteStore:\n    def __init__(self, db_path: str | Path) -> None:\n        self.db_path = str(db_path)\n\n    def initialize(self) -> None:\n        with self.connection() as conn:\n            conn.executescript(SCHEMA_SQL)\n            self._ensure_column(conn, \"memories\", \"schema_version\", f\"TEXT NOT NULL DEFAULT '{SCHEMA_VERSION}'\")\n            self._ensure_column(conn, \"memories\", \"subtype\", \"TEXT\")\n            self._ensure_column(conn, \"memories\", \"run_id\", \"TEXT\")\n            self._ensure_column(conn, \"memories\", \"task_id\", \"TEXT\")\n            self._ensure_column(conn, \"memories\", \"url\", \"TEXT\")\n            self._ensure_column(conn, \"memories\", \"domain\", \"TEXT\")\n            self._ensure_column(conn, \"memories\", \"origin_agent\", \"TEXT\")\n            self._ensure_column(conn, \"tasks\", \"schema_version\", f\"TEXT NOT NULL DEFAULT '{SCHEMA_VERSION}'\")\n            self._ensure_column(conn, \"tasks\", \"run_id\", \"TEXT\")\n\n    @contextmanager\n    def connection(self) -> Iterator[sqlite3.Connection]:\n        conn = sqlite3.connect(self.db_path)\n        conn.row_factory = sqlite3.Row\n        conn.execute(\"PRAGMA foreign_keys = ON\")\n        try:\n            yield conn\n            conn.commit()\n        finally:\n            conn.close()\n\n    @staticmethod\n    def dumps(value: object) -> str:\n        return json.dumps(value, ensure_ascii=True, sort_keys=True)\n\n    @staticmethod\n    def loads(value: str | None) -> object:\n        if not value:\n            return None\n        return json.loads(value)\n\n    @staticmethod\n    def _ensure_column(conn: sqlite3.Connection, table: str, column: str, definition: str) -> None:\n        existing = {row[\"name\"] for row in conn.execute(f\"PRAGMA table_info({table})\")}\n        if column in existing:\n            return\n        conn.execute(f\"ALTER TABLE {table} ADD COLUMN {column} {definition}\")\n"}],"isError":false,"timestamp":1776635619011}}
{"type":"message","id":"85cb826e","parentId":"88dd8727","timestamp":"2026-04-19T21:53:39.235Z","message":{"role":"toolResult","toolCallId":"call_MBkqVeZKffZjAf82FibneSJl|fc_071e452a5a0ea02e0169e54ee09b6081909174765eb306738a","toolName":"bash","content":[{"type":"text","text":"6f9d550363b851ba477cfdfe1b889fb99f95e39e8e0de16a3d189ca97179b706  /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\n6f9d550363b851ba477cfdfe1b889fb99f95e39e8e0de16a3d189ca97179b706  /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3\n-rw-r--r-- 1 sebas sebas 104M Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3\n-rw-r--r-- 1 sebas sebas 104M Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\n"}],"isError":false,"timestamp":1776635619235}}
{"type":"message","id":"fb49f7bd","parentId":"85cb826e","timestamp":"2026-04-19T21:53:39.235Z","message":{"role":"toolResult","toolCallId":"call_hPvXRijkvlzuAwYB2u50yqry|fc_071e452a5a0ea02e0169e54ee09b6c8190972d72eac42a1aeb","toolName":"bash","content":[{"type":"text","text":"# /etc/systemd/system/personal-agent.service\n[Unit]\nDescription=Personal Agent Daemon\nAfter=network-online.target\n\n[Service]\nType=simple\nUser=sebas\nWorkingDirectory=/home/sebas/personal-agent\nEnvironment=\"PATH=/home/sebas/personal-agent/venv/bin:/usr/local/bin:/usr/bin:/bin\"\nExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082\nRestart=always\nRestartSec=5\n\n[Install]\nWantedBy=multi-user.target\n-rw-r--r-- 1 root root 432 Mar 28 10:14 /etc/systemd/system/personal-agent.service\n● personal-agent.service - Personal Agent Daemon\n     Loaded: loaded (/etc/systemd/system/personal-agent.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:53:36 -03; 2s ago\n Invocation: 8afc0deaae6546ecbc93fb8d750913d0\n    Process: 675592 ExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082 (code=exited, status=203/EXEC)\n   Main PID: 675592 (code=exited, status=203/EXEC)\n        CPU: 8ms\n\nApr 19 18:53:36 ballbox-first systemd[1]: personal-agent.service: Failed with result 'exit-code'.\n"}],"isError":false,"timestamp":1776635619235}}
{"type":"message","id":"1e920a37","parentId":"fb49f7bd","timestamp":"2026-04-19T21:53:41.732Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_MS2b3gzDYX295WR7xbkhZZ8B|fc_071e452a5a0ea02e0169e54ee446b88190a4341b44c8098138","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl disable --now personal-agent.service\nsystemctl reset-failed personal-agent.service || true\nsystemctl status personal-agent.service --no-pager -n 20 || true\nsystemctl is-enabled personal-agent.service || true","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1238,"output":74,"cacheRead":22400,"cacheWrite":0,"totalTokens":23712,"cost":{"input":0.003095,"output":0.00111,"cacheRead":0.0056,"cacheWrite":0,"total":0.009805000000000001}},"stopReason":"toolUse","timestamp":1776635619237,"responseId":"resp_071e452a5a0ea02e0169e54ee389448190bfa448f8bf221cdc"}}
{"type":"message","id":"568faa3e","parentId":"1e920a37","timestamp":"2026-04-19T21:54:06.765Z","message":{"role":"toolResult","toolCallId":"call_MS2b3gzDYX295WR7xbkhZZ8B|fc_071e452a5a0ea02e0169e54ee446b88190a4341b44c8098138","toolName":"bash","content":[{"type":"text","text":"Failed to disable unit: Connection timed out\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635646765}}
{"type":"message","id":"63542152","parentId":"568faa3e","timestamp":"2026-04-19T21:54:09.433Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_RTrODCIb8huXIUdNeY8RHMjL|fc_071e452a5a0ea02e0169e54effd9448190962e0019c3a1e523","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl mask personal-agent.service || true\nsystemctl stop personal-agent.service || true\nsystemctl reset-failed personal-agent.service || true\nsystemctl is-enabled personal-agent.service || true\nsystemctl status personal-agent.service --no-pager -n 20 || true","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":186,"output":83,"cacheRead":23552,"cacheWrite":0,"totalTokens":23821,"cost":{"input":0.000465,"output":0.001245,"cacheRead":0.005888,"cacheWrite":0,"total":0.007598000000000001}},"stopReason":"toolUse","timestamp":1776635646768,"responseId":"resp_071e452a5a0ea02e0169e54eff27408190ac8b91ad199d0123"}}
{"type":"message","id":"34478e59","parentId":"63542152","timestamp":"2026-04-19T21:55:24.525Z","message":{"role":"toolResult","toolCallId":"call_RTrODCIb8huXIUdNeY8RHMjL|fc_071e452a5a0ea02e0169e54effd9448190962e0019c3a1e523","toolName":"bash","content":[{"type":"text","text":"Failed to mask unit: Connection timed out\nFailed to stop personal-agent.service: Connection timed out\nSee system logs and 'systemctl status personal-agent.service' for details.\nFailed to reset failed state of unit personal-agent.service: Connection timed out\nenabled\n● personal-agent.service - Personal Agent Daemon\n     Loaded: loaded (/etc/systemd/system/personal-agent.service; enabled; preset: enabled)\n     Active: activating (auto-restart) (Result: exit-code) since Sun 2026-04-19 18:55:21 -03; 2s ago\n Invocation: d4859fcf6f56493fbf90d69e9dd46538\n    Process: 675788 ExecStart=/home/sebas/personal-agent/venv/bin/python3 /home/sebas/personal-agent/scripts/personal.py daemon --host 0.0.0.0 --port 8082 (code=exited, status=203/EXEC)\n   Main PID: 675788 (code=exited, status=203/EXEC)\n        CPU: 8ms\n"}],"isError":false,"timestamp":1776635724524}}
{"type":"message","id":"3f939948","parentId":"34478e59","timestamp":"2026-04-19T21:55:24.530Z","message":{"role":"user","content":[{"type":"text","text":"also new tmux setup only allows me to connect to existing session so cant open multiple sessions in parallel. suggestions?"}],"timestamp":1776635659616}}
{"type":"message","id":"0a152417","parentId":"3f939948","timestamp":"2026-04-19T21:55:35.660Z","message":{"role":"assistant","content":[{"type":"text","text":"Yes. Best fix is to keep your “auto-attach” flow, but add an escape hatch.\n\nGood options:\n\n1. separate alias/script for new sessions\n- Keep current `tmux` wrapper as “attach existing”.\n- Add:\n  - `ta` -> attach existing/default\n  - `tn <name>` -> create/switch to named session\n  - `tls` -> list sessions\n- Best balance.\n\n2. auto-attach only for plain login shells\n- In shell rc, only attach when:\n  - interactive shell\n  - no `$TMUX`\n  - no command args\n  - maybe only on tty login, not ssh command/non-login shell\n- Then `tmux new -s foo` still works normally.\n\n3. use tmux session groups\n- If your need is shared windows with separate clients:\n  - `tmux new-session -t main -s main2`\n- Good for parallel views, not true separate workspaces.\n\n4. use windows instead of sessions\n- If the blocker is just parallel tasks, multiple windows may be enough.\n- But if you want separate environments/context, sessions are better.\n\nRecommended setup:\n- Auto-attach only when you run plain shell login.\n- Do not override `tmux` itself.\n- Add small helpers:\n  - `t` attach-or-create main\n  - `tn` new named session\n  - `ta` attach chooser\n  - `tk` kill named session\n\nExample shell setup:\n```bash\n# auto-attach only on plain interactive login, not inside tmux\nif [[ $- == *i* ]] && [[ -z \"${TMUX:-}\" ]] && [[ -z \"${TMUX_AUTO_DISABLED:-}\" ]]; then\n  if command -v tmux >/dev/null 2>&1; then\n    tmux attach -t main 2>/dev/null || tmux new -s main\n    exit\n  fi\nfi\n\nt() {\n  tmux attach -t main 2>/dev/null || tmux new -s main\n}\n\ntn() {\n  tmux new -A -s \"${1:?session name required}\"\n}\n\nta() {\n  tmux list-sessions\n}\n\ntk() {\n  tmux kill-session -t \"${1:?session name required}\"\n}\n```\n\nIf your current setup overrides `tmux` via alias/function, remove that part first. That’s usually the thing causing the lock-in.\n\nIf you want, I can inspect your current tmux/shell config and patch it so:\n- login auto-attaches to `main`\n- `tmux new -s foo` works again\n- multiple parallel sessions work normally","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e54f4d76508190b3227fb1f71a3d68\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":407,"output":554,"cacheRead":23680,"cacheWrite":0,"totalTokens":24641,"cost":{"input":0.0010175000000000002,"output":0.00831,"cacheRead":0.00592,"cacheWrite":0,"total":0.015247499999999999}},"stopReason":"stop","timestamp":1776635724529,"responseId":"resp_071e452a5a0ea02e0169e54f4cd80881908be54ffda7465288"}}
{"type":"message","id":"d953f2f3","parentId":"0a152417","timestamp":"2026-04-19T21:56:59.399Z","message":{"role":"user","content":[{"type":"text","text":"can a new ssh session open a tmux session picker (with a \"new\" option)?"}],"timestamp":1776635819397}}
{"type":"message","id":"d90a0641","parentId":"d953f2f3","timestamp":"2026-04-19T21:57:11.724Z","message":{"role":"assistant","content":[{"type":"text","text":"Yes.\n\nBest pattern:\n- new SSH login checks:\n  - interactive shell\n  - not already in tmux\n- then launches a tmux picker:\n  - choose existing session\n  - or create new named session\n\nSimplest implementation:\n- use `fzf` over `tmux list-sessions`\n- prepend a `+ new session` entry\n\nExample:\n```bash\ntmux_pick() {\n  local choice name\n  choice=\"$(\n    {\n      echo \"+ new session\"\n      tmux list-sessions -F '#S' 2>/dev/null || true\n    } | awk '!seen[$0]++' | fzf --prompt='tmux> '\n  )\" || return 1\n\n  if [[ \"$choice\" == \"+ new session\" ]]; then\n    read -rp \"session name: \" name\n    [[ -n \"$name\" ]] || return 1\n    exec tmux new -s \"$name\"\n  else\n    exec tmux attach -t \"$choice\"\n  fi\n}\n```\n\nThen auto-run on SSH login:\n```bash\nif [[ $- == *i* ]] && [[ -n \"${SSH_CONNECTION:-}\" ]] && [[ -z \"${TMUX:-}\" ]]; then\n  tmux_pick\nfi\n```\n\nBetter version:\n- default to `main` if no sessions exist\n- allow cancel to stay in plain shell\n- sanitize session names\n- use `tmux new -A -s <name>` so existing names are safe\n\nSafer version:\n```bash\ntmux_pick() {\n  local sessions choice name\n  sessions=\"$(tmux list-sessions -F '#S' 2>/dev/null || true)\"\n\n  choice=\"$(\n    {\n      echo \"+ new session\"\n      [[ -n \"$sessions\" ]] && printf '%s\\n' \"$sessions\"\n    } | awk 'NF && !seen[$0]++' | fzf --prompt='tmux> ' --height=40%\n  )\" || return 0\n\n  if [[ \"$choice\" == \"+ new session\" ]]; then\n    read -rp \"session name: \" name\n    name=\"${name//[^[:alnum:]_.-]/-}\"\n    [[ -n \"$name\" ]] || return 0\n    exec tmux new -A -s \"$name\"\n  else\n    exec tmux attach -t \"$choice\"\n  fi\n}\n```\n\nAlternative without `fzf`:\n- `tmux choose-tree -s`\n- but that works best from inside tmux, not as a pre-attach SSH picker.\n\nSo: yes, and `fzf` is the cleanest UX.\n\nIf you want, I can wire this into your shell config and make it:\n- SSH login -> picker\n- local terminal login -> default `main`\n- cancel picker -> plain shell\n- supports multiple parallel sessions cleanly","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e54faca558819096f83b28229fa4f0\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":24666,"output":601,"cacheRead":0,"cacheWrite":0,"totalTokens":25267,"cost":{"input":0.061665000000000005,"output":0.009015,"cacheRead":0,"cacheWrite":0,"total":0.07068}},"stopReason":"stop","timestamp":1776635819400,"responseId":"resp_071e452a5a0ea02e0169e54fabd4108190a9d052d7220d9681"}}
{"type":"message","id":"04823920","parentId":"d90a0641","timestamp":"2026-04-19T21:58:37.970Z","message":{"role":"user","content":[{"type":"text","text":"do that, i like it. i also cant seem to scroll on tmux sessions"}],"timestamp":1776635917967}}
{"type":"message","id":"76c7f2ae","parentId":"04823920","timestamp":"2026-04-19T21:58:41.963Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_HZ2Zru67NkFo2ghHmNhVTvdt|fc_071e452a5a0ea02e0169e55011d2588190b4f929ee175b776d","name":"bash","arguments":{"command":"set -euo pipefail\nprintf 'shell=%s\\n' \"$SHELL\"\nfor f in ~/.bashrc ~/.bash_profile ~/.profile ~/.zshrc ~/.zprofile ~/.tmux.conf; do [ -f \"$f\" ] && echo \"--- $f\" && sed -n '1,240p' \"$f\"; done","timeout":120}},{"type":"toolCall","id":"call_Vikkme4swynxG2Ja7K87GqKe|fc_071e452a5a0ea02e0169e55011d2688190959cddd2747c628e","name":"read","arguments":{"path":"/home/sebas/.agents/skills/memory-write/SKILL.md"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":202,"output":137,"cacheRead":25088,"cacheWrite":0,"totalTokens":25427,"cost":{"input":0.000505,"output":0.002055,"cacheRead":0.006272,"cacheWrite":0,"total":0.008832}},"stopReason":"toolUse","timestamp":1776635917970,"responseId":"resp_071e452a5a0ea02e0169e5500e861c8190aa23ce7027abd9a1"}}
{"type":"message","id":"1cd5a191","parentId":"76c7f2ae","timestamp":"2026-04-19T21:58:41.977Z","message":{"role":"toolResult","toolCallId":"call_HZ2Zru67NkFo2ghHmNhVTvdt|fc_071e452a5a0ea02e0169e55011d2588190b4f929ee175b776d","toolName":"bash","content":[{"type":"text","text":"shell=/bin/bash\n--- /home/sebas/.bashrc\n# ~/.bashrc: executed by bash(1) for non-login shells.\n# see /usr/share/doc/bash/examples/startup-files (in the package bash-doc)\n# for examples\n\n# If not running interactively, don't do anything\ncase $- in\n    *i*) ;;\n      *) return;;\nesac\n\n# don't put duplicate lines or lines starting with space in the history.\n# See bash(1) for more options\nHISTCONTROL=ignoreboth\n\n# append to the history file, don't overwrite it\nshopt -s histappend\n\n# for setting history length see HISTSIZE and HISTFILESIZE in bash(1)\nHISTSIZE=1000\nHISTFILESIZE=2000\n\n# check the window size after each command and, if necessary,\n# update the values of LINES and COLUMNS.\nshopt -s checkwinsize\n\n# If set, the pattern \"**\" used in a pathname expansion context will\n# match all files and zero or more directories and subdirectories.\n#shopt -s globstar\n\n# make less more friendly for non-text input files, see lesspipe(1)\n#[ -x /usr/bin/lesspipe ] && eval \"$(SHELL=/bin/sh lesspipe)\"\n\n# set variable identifying the chroot you work in (used in the prompt below)\nif [ -z \"${debian_chroot:-}\" ] && [ -r /etc/debian_chroot ]; then\n    debian_chroot=$(cat /etc/debian_chroot)\nfi\n\n# set a fancy prompt (non-color, unless we know we \"want\" color)\ncase \"$TERM\" in\n    xterm-color|*-256color) color_prompt=yes;;\nesac\n\n# uncomment for a colored prompt, if the terminal has the capability; turned\n# off by default to not distract the user: the focus in a terminal window\n# should be on the output of commands, not on the prompt\nforce_color_prompt=yes\n\nif [ -n \"$force_color_prompt\" ]; then\n    if [ -x /usr/bin/tput ] && tput setaf 1 >&/dev/null; then\n\t# We have color support; assume it's compliant with Ecma-48\n\t# (ISO/IEC-6429). (Lack of such support is extremely rare, and such\n\t# a case would tend to support setf rather than setaf.)\n\tcolor_prompt=yes\n    else\n\tcolor_prompt=\n    fi\nfi\n\nif [ \"$color_prompt\" = yes ]; then\n    PS1='${debian_chroot:+($debian_chroot)}\\[\\033[01;32m\\]\\u@\\h\\[\\033[00m\\]:\\[\\033[01;34m\\]\\w \\$\\[\\033[00m\\] '\nelse\n    PS1='${debian_chroot:+($debian_chroot)}\\u@\\h:\\w\\$ '\nfi\nunset color_prompt force_color_prompt\n\n# If this is an xterm set the title to user@host:dir\ncase \"$TERM\" in\nxterm*|rxvt*)\n    PS1=\"\\[\\e]0;${debian_chroot:+($debian_chroot)}\\u@\\h: \\w\\a\\]$PS1\"\n    ;;\n*)\n    ;;\nesac\n\n# enable color support of ls and also add handy aliases\nif [ -x /usr/bin/dircolors ]; then\n    test -r ~/.dircolors && eval \"$(dircolors -b ~/.dircolors)\" || eval \"$(dircolors -b)\"\n    alias ls='ls --color=auto'\n    #alias dir='dir --color=auto'\n    #alias vdir='vdir --color=auto'\n\n    alias grep='grep --color=auto'\n    alias fgrep='fgrep --color=auto'\n    alias egrep='egrep --color=auto'\nfi\n\n# colored GCC warnings and errors\n#export GCC_COLORS='error=01;31:warning=01;35:note=01;36:caret=01;32:locus=01:quote=01'\n\n# some more ls aliases\n#alias ll='ls -l'\n#alias la='ls -A'\n#alias l='ls -CF'\n\n# Alias definitions.\n# You may want to put all your additions into a separate file like\n# ~/.bash_aliases, instead of adding them here directly.\n# See /usr/share/doc/bash-doc/examples in the bash-doc package.\n\nif [ -f ~/.bash_aliases ]; then\n    . ~/.bash_aliases\nfi\n\n# enable programmable completion features (you don't need to enable\n# this, if it's already enabled in /etc/bash.bashrc and /etc/profile\n# sources /etc/bash.bashrc).\nif ! shopt -oq posix; then\n  if [ -f /usr/share/bash-completion/bash_completion ]; then\n    . /usr/share/bash-completion/bash_completion\n  elif [ -f /etc/bash_completion ]; then\n    . /etc/bash_completion\n  fi\nfi\nexport PATH=\"$HOME/.local/bin:$PATH\"\nexport PATH=\"$HOME/.npm-global/bin:$PATH\"\nexport PI_CODING_AGENT_DIR=/mnt/rpi/pi-config\n# opencode\nexport PATH=/home/sebas/.opencode/bin:$PATH\nexport PERSONAL_AGENT_SHARED_MEMORY_DB_PATH=~/agents-database/data/shared-agent-memory.sqlite3\n\n# Auto-start tmux for interactive SSH shells.\n# Keeps long-running work alive if the client disconnects.\n# Ghostty may advertise TERM=xterm-ghostty, which is often missing on remote hosts.\n# Fall back before starting tmux so SSH sessions still attach cleanly.\nif [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n    case \"$TERM\" in\n        xterm-ghostty)\n            export TERM=xterm-256color\n            ;;\n    esac\nfi\n\nif [ -n \"$SSH_CONNECTION\" ] && command -v tmux >/dev/null 2>&1; then\n    if [ -z \"$TMUX\" ]; then\n        exec tmux new-session -A -s main\n    fi\nfi\n--- /home/sebas/.profile\n# ~/.profile: executed by the command interpreter for login shells.\n# This file is not read by bash(1), if ~/.bash_profile or ~/.bash_login\n# exists.\n# see /usr/share/doc/bash/examples/startup-files for examples.\n# the files are located in the bash-doc package.\n\n# the default umask is set in /etc/profile; for setting the umask\n# for ssh logins, install and configure the libpam-umask package.\n#umask 022\n\n# if running bash\nif [ -n \"$BASH_VERSION\" ]; then\n    # include .bashrc if it exists\n    if [ -f \"$HOME/.bashrc\" ]; then\n\t. \"$HOME/.bashrc\"\n    fi\nfi\n\n# set PATH so it includes user's private bin if it exists\nif [ -d \"$HOME/bin\" ] ; then\n    PATH=\"$HOME/bin:$PATH\"\nfi\n\n# set PATH so it includes user's private bin if it exists\nif [ -d \"$HOME/.local/bin\" ] ; then\n    PATH=\"/mnt/rpi/pi-config/bin:$HOME/.local/bin:$PATH\"\nfi\n\nexport LC_ALL=en_US.UTF-8\nexport LANG=en_US.UTF-8\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635921977}}
{"type":"message","id":"48751a36","parentId":"1cd5a191","timestamp":"2026-04-19T21:58:41.995Z","message":{"role":"toolResult","toolCallId":"call_Vikkme4swynxG2Ja7K87GqKe|fc_071e452a5a0ea02e0169e55011d2688190959cddd2747c628e","toolName":"read","content":[{"type":"text","text":"---\nname: memory-write\ndescription: Save a durable high-signal memory into agents-database\n---\n\n# memory-write\n\n## Use When\n\n- new information is likely useful beyond current chat or task\n- saving a decision, preference, project fact, reusable source/artifact, or handoff summary\n- user asks to remember something durable\n\n## Do Not Use When\n\n- content is trivial, redundant, ephemeral, or likely useless later\n- content is secret unless user explicitly asked to store it\n\n## Required Workflow\n\n1. If useful context may already exist, optionally check first:\n   - `curl -fsSL \"${AGENTS_DB_API:-http://100.116.176.16:8091}/api/search?q=<query>&scope=global&scope=project&limit=10\"`\n2. Choose best memory type:\n   - `profile`: stable user preference, priority, recurring constraint\n   - `decision`: chosen approach or operating rule\n   - `project`: durable project fact or invariant\n   - `artifact`: reusable source, claim, reference, output\n   - `episode`: concise session summary, blocked state, handoff context\n3. Build a concise payload with:\n   - required: `type`, `scope`, `title`, `content`\n   - recommended when known: `subtype`, `project_id`, `repo_id`, `task_id`, `run_id`, `source_ref`, `origin_agent`, `url`, `domain`, `metadata`\n4. Save it with the helper:\n   - `~/.agents/skills/memory-write/memory-write --type <type> --scope <scope> --title \"<title>\" --content \"<content>\"`\n5. Confirm the created memory id and what was stored.\n\n## Quick Examples\n\n```bash\n~/.agents/skills/memory-write/memory-write \\\n  --type profile \\\n  --subtype working_preference \\\n  --scope global \\\n  --title \"User prefers concise status updates\" \\\n  --content \"Sebas prefers short, direct updates with business impact first.\" \\\n  --source-ref \"conversation:2026-04-17\" \\\n  --origin-agent personal-agent\n\n~/.agents/skills/memory-write/memory-write \\\n  --type decision \\\n  --subtype operating_rule \\\n  --scope global \\\n  --title \"Agents should save durable high-signal memory opportunistically\" \\\n  --content \"Treat agents-database as shared durable memory, not only search.\" \\\n  --metadata '{\"source\":\"conversation\"}'\n```\n\n## Rules\n\n- prefer one strong memory over many weak ones\n- keep `title` short and searchable\n- keep `content` factual and compact\n- use `episode` for summaries, not for every chat turn\n- include `url` and `domain` for web-derived artifacts when known\n- include `project_id`, `repo_id`, `task_id`, and `run_id` when context exists\n"}],"isError":false,"timestamp":1776635921981}}
{"type":"message","id":"5da4a7f4","parentId":"48751a36","timestamp":"2026-04-19T21:58:56.909Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_NJa5F3egfpbhXhEyZSbQmffk|fc_071e452a5a0ea02e0169e5501333688190b2fabc4aa2adac87","name":"edit","arguments":{"path":"/home/sebas/.bashrc","edits":[{"oldText":"# Auto-start tmux for interactive SSH shells.\n# Keeps long-running work alive if the client disconnects.\n# Ghostty may advertise TERM=xterm-ghostty, which is often missing on remote hosts.\n# Fall back before starting tmux so SSH sessions still attach cleanly.\nif [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n    case \"$TERM\" in\n        xterm-ghostty)\n            export TERM=xterm-256color\n            ;;\n    esac\nfi\n\nif [ -n \"$SSH_CONNECTION\" ] && command -v tmux >/dev/null 2>&1; then\n    if [ -z \"$TMUX\" ]; then\n        exec tmux new-session -A -s main\n    fi\nfi\n","newText":"# Auto-start tmux for interactive SSH shells with a session picker.\n# Cancel keeps a plain shell. Choose an existing session or create a new one.\n# Ghostty may advertise TERM=xterm-ghostty, which is often missing on remote hosts.\nif [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n    case \"$TERM\" in\n        xterm-ghostty)\n            export TERM=xterm-256color\n            ;;\n    esac\nfi\n\ntmux_pick() {\n    command -v tmux >/dev/null 2>&1 || return 0\n\n    local sessions choice name\n    sessions=\"$(tmux list-sessions -F '#S' 2>/dev/null || true)\"\n\n    if command -v fzf >/dev/null 2>&1; then\n        choice=\"$({\n            echo '+ new session'\n            [ -n \"$sessions\" ] && printf '%s\\n' \"$sessions\"\n        } | awk 'NF && !seen[$0]++' | fzf --prompt='tmux> ' --height=40%)\" || return 0\n    else\n        printf 'tmux sessions:\\n' >&2\n        printf '  [n] new session\\n' >&2\n        if [ -n \"$sessions\" ]; then\n            printf '%s\\n' \"$sessions\" | nl -w2 -s'] ' >&2\n        fi\n        read -r -p 'choice (name or n, blank for shell): ' choice\n        [ -n \"$choice\" ] || return 0\n    fi\n\n    if [ \"$choice\" = '+ new session' ] || [ \"$choice\" = 'n' ]; then\n        read -r -p 'session name: ' name\n        name=${name//[^[:alnum:]_.-]/-}\n        [ -n \"$name\" ] || return 0\n        exec tmux new-session -A -s \"$name\"\n    fi\n\n    if printf '%s\\n' \"$sessions\" | grep -Fxq \"$choice\"; then\n        exec tmux attach-session -t \"$choice\"\n    fi\n\n    name=${choice//[^[:alnum:]_.-]/-}\n    [ -n \"$name\" ] || return 0\n    exec tmux new-session -A -s \"$name\"\n}\n\nif [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n    tmux_pick\nfi\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2271,"output":753,"cacheRead":25344,"cacheWrite":0,"totalTokens":28368,"cost":{"input":0.0056775,"output":0.011295,"cacheRead":0.006336,"cacheWrite":0,"total":0.023308500000000003}},"stopReason":"toolUse","timestamp":1776635921997,"responseId":"resp_071e452a5a0ea02e0169e5501250248190acd62bba7ab9fdca"}}
{"type":"message","id":"392bd10a","parentId":"5da4a7f4","timestamp":"2026-04-19T21:58:56.926Z","message":{"role":"toolResult","toolCallId":"call_NJa5F3egfpbhXhEyZSbQmffk|fc_071e452a5a0ea02e0169e5501333688190b2fabc4aa2adac87","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /home/sebas/.bashrc."}],"details":{"diff":"     ...\n 117 # opencode\n 118 export PATH=/home/sebas/.opencode/bin:$PATH\n 119 export PERSONAL_AGENT_SHARED_MEMORY_DB_PATH=~/agents-database/data/shared-agent-memory.sqlite3\n 120 \n-121 # Auto-start tmux for interactive SSH shells.\n-122 # Keeps long-running work alive if the client disconnects.\n+121 # Auto-start tmux for interactive SSH shells with a session picker.\n+122 # Cancel keeps a plain shell. Choose an existing session or create a new one.\n 123 # Ghostty may advertise TERM=xterm-ghostty, which is often missing on remote hosts.\n-124 # Fall back before starting tmux so SSH sessions still attach cleanly.\n 125 if [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n 126     case \"$TERM\" in\n 127         xterm-ghostty)\n 128             export TERM=xterm-256color\n 129             ;;\n 130     esac\n 131 fi\n 132 \n-133 if [ -n \"$SSH_CONNECTION\" ] && command -v tmux >/dev/null 2>&1; then\n-134     if [ -z \"$TMUX\" ]; then\n-135         exec tmux new-session -A -s main\n+132 tmux_pick() {\n+133     command -v tmux >/dev/null 2>&1 || return 0\n+134 \n+135     local sessions choice name\n+136     sessions=\"$(tmux list-sessions -F '#S' 2>/dev/null || true)\"\n+137 \n+138     if command -v fzf >/dev/null 2>&1; then\n+139         choice=\"$({\n+140             echo '+ new session'\n+141             [ -n \"$sessions\" ] && printf '%s\\n' \"$sessions\"\n+142         } | awk 'NF && !seen[$0]++' | fzf --prompt='tmux> ' --height=40%)\" || return 0\n+143     else\n+144         printf 'tmux sessions:\\n' >&2\n+145         printf '  [n] new session\\n' >&2\n+146         if [ -n \"$sessions\" ]; then\n+147             printf '%s\\n' \"$sessions\" | nl -w2 -s'] ' >&2\n+148         fi\n+149         read -r -p 'choice (name or n, blank for shell): ' choice\n+150         [ -n \"$choice\" ] || return 0\n 136     fi\n+152 \n+153     if [ \"$choice\" = '+ new session' ] || [ \"$choice\" = 'n' ]; then\n+154         read -r -p 'session name: ' name\n+155         name=${name//[^[:alnum:]_.-]/-}\n+156         [ -n \"$name\" ] || return 0\n+157         exec tmux new-session -A -s \"$name\"\n+158     fi\n+159 \n+160     if printf '%s\\n' \"$sessions\" | grep -Fxq \"$choice\"; then\n+161         exec tmux attach-session -t \"$choice\"\n+162     fi\n+163 \n+164     name=${choice//[^[:alnum:]_.-]/-}\n+165     [ -n \"$name\" ] || return 0\n+166     exec tmux new-session -A -s \"$name\"\n+167 }\n+168 \n+169 if [ -n \"$SSH_CONNECTION\" ] && [ -z \"$TMUX\" ]; then\n+170     tmux_pick\n 137 fi","firstChangedLine":121},"isError":false,"timestamp":1776635936925}}
{"type":"message","id":"d0ff9154","parentId":"392bd10a","timestamp":"2026-04-19T21:59:02.700Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_KDD9egBU7Mp4Bd0uWQuggSPN|fc_071e452a5a0ea02e0169e55022b67c819081a5b0f84344eb36","name":"write","arguments":{"path":"/home/sebas/.tmux.conf","content":"set -g mouse on\nset -g history-limit 100000\nset -g set-clipboard on\n\n# Better terminal support over SSH.\nset -g default-terminal \"tmux-256color\"\nset -as terminal-features \",xterm-256color:clipboard\"\nset -as terminal-features \",screen-256color:clipboard\"\nset -as terminal-features \",tmux-256color:clipboard\"\n\n# Vi-style copy/scroll mode.\nsetw -g mode-keys vi\nbind-key -T copy-mode-vi v send-keys -X begin-selection\nbind-key -T copy-mode-vi y send-keys -X copy-selection-and-cancel\nbind-key PageUp copy-mode -u\n\n# Easier reload.\nbind r source-file ~/.tmux.conf \\; display-message \"tmux.conf reloaded\"\n"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":106,"output":213,"cacheRead":28288,"cacheWrite":0,"totalTokens":28607,"cost":{"input":0.00026500000000000004,"output":0.003195,"cacheRead":0.007071999999999999,"cacheWrite":0,"total":0.010532}},"stopReason":"toolUse","timestamp":1776635936928,"responseId":"resp_071e452a5a0ea02e0169e550218e84819080478720bce8e007"}}
{"type":"message","id":"bf576a5e","parentId":"d0ff9154","timestamp":"2026-04-19T21:59:02.714Z","message":{"role":"toolResult","toolCallId":"call_KDD9egBU7Mp4Bd0uWQuggSPN|fc_071e452a5a0ea02e0169e55022b67c819081a5b0f84344eb36","toolName":"write","content":[{"type":"text","text":"Successfully wrote 599 bytes to /home/sebas/.tmux.conf"}],"isError":false,"timestamp":1776635942713}}
{"type":"message","id":"cf80f1fc","parentId":"bf576a5e","timestamp":"2026-04-19T21:59:06.154Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_u9T5Ln6lnPAr4lJDltEQXjbx|fc_071e452a5a0ea02e0169e5502813d08190bd70d940c19ef789","name":"bash","arguments":{"command":"set -euo pipefail\nif tmux info >/dev/null 2>&1; then\n  tmux source-file /home/sebas/.tmux.conf || true\n  tmux show -g mouse\n  tmux show -g history-limit\n  tmux show -g default-terminal\nfi\nbash -n /home/sebas/.bashrc\nprintf 'bashrc ok\\n'","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":215,"output":105,"cacheRead":28416,"cacheWrite":0,"totalTokens":28736,"cost":{"input":0.0005375,"output":0.001575,"cacheRead":0.007104,"cacheWrite":0,"total":0.009216499999999999}},"stopReason":"toolUse","timestamp":1776635942716,"responseId":"resp_071e452a5a0ea02e0169e550273d348190a59715647daf5f90"}}
{"type":"message","id":"d7413a32","parentId":"cf80f1fc","timestamp":"2026-04-19T21:59:06.209Z","message":{"role":"toolResult","toolCallId":"call_u9T5Ln6lnPAr4lJDltEQXjbx|fc_071e452a5a0ea02e0169e5502813d08190bd70d940c19ef789","toolName":"bash","content":[{"type":"text","text":"mouse on\nhistory-limit 100000\ndefault-terminal tmux-256color\nbashrc ok\n"}],"isError":false,"timestamp":1776635946209}}
{"type":"message","id":"4b45f0ab","parentId":"d7413a32","timestamp":"2026-04-19T21:59:10.492Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_H0QBC72kq5J48NKwWVb3lTPK|fc_071e452a5a0ea02e0169e5502b96e481909144e05df9e4b876","name":"bash","arguments":{"command":"set -euo pipefail\n~/.agents/skills/memory-write/memory-write \\\n  --type profile \\\n  --subtype working_preference \\\n  --scope global \\\n  --title \"SSH tmux picker and scroll preference\" \\\n  --content \"Sebas wants new SSH logins to open a tmux session picker with an option to create a new session, instead of forcing attach to one default session. Also wants tmux scrolling enabled and working by default.\" \\\n  --source-ref \"conversation:2026-04-19\" \\\n  --origin-agent personal-agent","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":224,"output":154,"cacheRead":28544,"cacheWrite":0,"totalTokens":28922,"cost":{"input":0.0005600000000000001,"output":0.00231,"cacheRead":0.007136,"cacheWrite":0,"total":0.010006000000000001}},"stopReason":"toolUse","timestamp":1776635946211,"responseId":"resp_071e452a5a0ea02e0169e5502ab3088190ac062661153aca68"}}
{"type":"message","id":"2656ec9a","parentId":"4b45f0ab","timestamp":"2026-04-19T21:59:10.642Z","message":{"role":"toolResult","toolCallId":"call_H0QBC72kq5J48NKwWVb3lTPK|fc_071e452a5a0ea02e0169e5502b96e481909144e05df9e4b876","toolName":"bash","content":[{"type":"text","text":"Traceback (most recent call last):\n  File \"/home/sebas/.agents/skills/memory-write/memory-write\", line 86, in <module>\n    main()\n    ~~~~^^\n  File \"/home/sebas/.agents/skills/memory-write/memory-write\", line 80, in main\n    with urllib.request.urlopen(req, timeout=30) as r:\n         ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 189, in urlopen\n    return opener.open(url, data, timeout)\n           ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 489, in open\n    response = self._open(req, data)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 506, in _open\n    result = self._call_chain(self.handle_open, protocol, protocol +\n                              '_open', req)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 466, in _call_chain\n    result = func(*args)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 1348, in http_open\n    return self.do_open(http.client.HTTPConnection, req)\n           ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 1323, in do_open\n    r = h.getresponse()\n  File \"/usr/lib/python3.13/http/client.py\", line 1430, in getresponse\n    response.begin()\n    ~~~~~~~~~~~~~~^^\n  File \"/usr/lib/python3.13/http/client.py\", line 331, in begin\n    version, status, reason = self._read_status()\n                              ~~~~~~~~~~~~~~~~~^^\n  File \"/usr/lib/python3.13/http/client.py\", line 300, in _read_status\n    raise RemoteDisconnected(\"Remote end closed connection without\"\n                             \" response\")\nhttp.client.RemoteDisconnected: Remote end closed connection without response\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776635950642}}
{"type":"message","id":"6c468f4e","parentId":"2656ec9a","timestamp":"2026-04-19T21:59:20.470Z","message":{"role":"assistant","content":[{"type":"text","text":"Done.\n\nWhat changed\n\n- SSH login now opens a tmux picker instead of forcing `main`\n  - existing sessions show up\n  - top option: `+ new session`\n  - cancel -> plain shell\n  - if `fzf` is missing, it falls back to a text prompt\n- tmux scroll support enabled\n  - mouse scrolling on\n  - bigger history\n  - vi copy mode enabled\n  - `PageUp` enters scrollback\n\nFiles changed\n\n- `~/.bashrc`\n  - replaced forced `exec tmux new-session -A -s main`\n  - added `tmux_pick()` and SSH auto-picker\n- `~/.tmux.conf`\n  - enabled:\n    - `set -g mouse on`\n    - `set -g history-limit 100000`\n    - `setw -g mode-keys vi`\n    - `bind-key PageUp copy-mode -u`\n\nApplied live\n- reloaded tmux config in current server\n- validated bash syntax\n\nHow to use\n\n- New SSH login:\n  - picker opens\n  - choose a session or `+ new session`\n- Scroll:\n  - mouse wheel should now work in tmux\n  - or press `PageUp`\n  - in copy mode:\n    - `q` exits\n    - vi keys work: `j k / g G`\n    - `v` begin select\n    - `y` copy\n\nNotes\n\n- If mouse scroll still doesn’t behave well, the issue may be terminal-side scroll event handling. Usually this config fixes it.\n- I tried to save this preference to agents-database, but memory write failed because the DB API is still only partially healthy. Status works; ingest likely still hits damaged DB paths.\n\nOn the service side\n- I already backed up the SQLite file:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3`\n\nStill pending from your previous request\n- proper root `personal-agent.service` cleanup\n- real SQLite repair/rebuild\n- remove degraded workaround after DB is sound\n\nI can continue with those next.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e550303270819084f68a3fced91031\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":565,"output":448,"cacheRead":28800,"cacheWrite":0,"totalTokens":29813,"cost":{"input":0.0014125000000000001,"output":0.00672,"cacheRead":0.0072,"cacheWrite":0,"total":0.0153325}},"stopReason":"stop","timestamp":1776635950644,"responseId":"resp_071e452a5a0ea02e0169e5502ef31081908824a41768d87181"}}
{"type":"message","id":"b354ac3d","parentId":"6c468f4e","timestamp":"2026-04-19T22:01:51.430Z","message":{"role":"user","content":[{"type":"text","text":"continue"}],"timestamp":1776636111425}}
{"type":"message","id":"684faa44","parentId":"b354ac3d","timestamp":"2026-04-19T22:01:58.629Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_mASr1UJyvCX0TLWOOFZqRrpg|fc_071e452a5a0ea02e0169e550d66424819083ad9d2fd8dd5f51","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/schema.py","offset":1,"limit":260}},{"type":"toolCall","id":"call_jhTdIALWhzTqhtiZGv1p1FGM|fc_071e452a5a0ea02e0169e550d664348190b679883e14e3bce5","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3\np='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(p)\ncur=con.cursor()\nfor q in [\n    'PRAGMA quick_check;',\n    'PRAGMA freelist_count;',\n    'PRAGMA page_count;',\n    'PRAGMA journal_mode;',\n    'PRAGMA auto_vacuum;',\n]:\n    try:\n        print('---', q)\n        for row in cur.execute(q).fetchmany(20):\n            print(row)\n    except Exception as e:\n        print('ERR', q, repr(e))\nPY","timeout":120}},{"type":"toolCall","id":"call_V6IGqQpcJsLkGzMyEwXNmvfG|fc_071e452a5a0ea02e0169e550d6643c8190847d8831d854bce9","name":"bash","arguments":{"command":"set -euo pipefail\nfind /mnt/rpi/agents-database -maxdepth 3 \\( -name '*.sqlite3*' -o -name '*.db*' -o -path '*/data/*' \\) -ls | sed -n '1,200p'","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":124,"output":308,"cacheRead":29696,"cacheWrite":0,"totalTokens":30128,"cost":{"input":0.00031,"output":0.00462,"cacheRead":0.007424,"cacheWrite":0,"total":0.012354}},"stopReason":"toolUse","timestamp":1776636111434,"responseId":"resp_071e452a5a0ea02e0169e550cfc32081909c2a3d779b587e8c"}}
{"type":"message","id":"bb6d9592","parentId":"684faa44","timestamp":"2026-04-19T22:01:58.730Z","message":{"role":"toolResult","toolCallId":"call_mASr1UJyvCX0TLWOOFZqRrpg|fc_071e452a5a0ea02e0169e550d66424819083ad9d2fd8dd5f51","toolName":"read","content":[{"type":"text","text":"SCHEMA_VERSION = \"shared-agent-memory-v2\"\n\nSCHEMA_SQL = f\"\"\"\nPRAGMA foreign_keys = ON;\n\nCREATE TABLE IF NOT EXISTS projects (\n    id TEXT PRIMARY KEY,\n    name TEXT NOT NULL,\n    description TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS repos (\n    id TEXT PRIMARY KEY,\n    project_id TEXT,\n    name TEXT NOT NULL,\n    path TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    FOREIGN KEY(project_id) REFERENCES projects(id)\n);\n\nCREATE TABLE IF NOT EXISTS sources (\n    id TEXT PRIMARY KEY,\n    source_kind TEXT NOT NULL,\n    title TEXT,\n    content TEXT NOT NULL,\n    source_ref TEXT,\n    metadata_json TEXT NOT NULL,\n    created_at TEXT NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS ingestion_events (\n    id TEXT PRIMARY KEY,\n    trigger_type TEXT NOT NULL,\n    source_id TEXT NOT NULL,\n    requested_scope TEXT NOT NULL,\n    job_state TEXT NOT NULL,\n    processor_outcome TEXT,\n    retry_count INTEGER NOT NULL DEFAULT 0,\n    error_message TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    processed_at TEXT,\n    FOREIGN KEY(source_id) REFERENCES sources(id)\n);\n\nCREATE TABLE IF NOT EXISTS memories (\n    id TEXT PRIMARY KEY,\n    schema_version TEXT NOT NULL DEFAULT '{SCHEMA_VERSION}',\n    type TEXT NOT NULL,\n    subtype TEXT,\n    scope TEXT NOT NULL,\n    status TEXT NOT NULL,\n    project_id TEXT,\n    repo_id TEXT,\n    agent_id TEXT,\n    origin_agent TEXT,\n    run_id TEXT,\n    task_id TEXT,\n    url TEXT,\n    domain TEXT,\n    source_kind TEXT NOT NULL,\n    title TEXT NOT NULL,\n    content TEXT NOT NULL,\n    summary TEXT NOT NULL,\n    confidence REAL NOT NULL,\n    freshness REAL NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    observed_at TEXT NOT NULL,\n    source_ref TEXT,\n    evidence_ref TEXT,\n    embedding_json TEXT,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(project_id) REFERENCES projects(id),\n    FOREIGN KEY(repo_id) REFERENCES repos(id)\n);\n\nCREATE TABLE IF NOT EXISTS memory_links (\n    id TEXT PRIMARY KEY,\n    from_memory_id TEXT NOT NULL,\n    to_memory_id TEXT NOT NULL,\n    relation TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(from_memory_id) REFERENCES memories(id),\n    FOREIGN KEY(to_memory_id) REFERENCES memories(id)\n);\n\nCREATE TABLE IF NOT EXISTS retrieval_logs (\n    id TEXT PRIMARY KEY,\n    query_text TEXT NOT NULL,\n    filters_json TEXT NOT NULL,\n    results_json TEXT NOT NULL,\n    created_at TEXT NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS maintenance_jobs (\n    id TEXT PRIMARY KEY,\n    job_type TEXT NOT NULL,\n    cadence TEXT NOT NULL,\n    interval_minutes INTEGER,\n    window_start TEXT,\n    window_end TEXT,\n    next_due_at TEXT NOT NULL,\n    last_run_at TEXT,\n    last_status TEXT,\n    last_summary TEXT,\n    enabled INTEGER NOT NULL DEFAULT 1,\n    metadata_json TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS maintenance_runs (\n    id TEXT PRIMARY KEY,\n    job_id TEXT NOT NULL,\n    status TEXT NOT NULL,\n    started_at TEXT NOT NULL,\n    completed_at TEXT,\n    summary TEXT,\n    stats_json TEXT NOT NULL,\n    error_message TEXT,\n    FOREIGN KEY(job_id) REFERENCES maintenance_jobs(id)\n);\n\nCREATE TABLE IF NOT EXISTS memory_conflicts (\n    id TEXT PRIMARY KEY,\n    memory_id TEXT NOT NULL,\n    conflicting_memory_id TEXT NOT NULL,\n    reason TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(memory_id) REFERENCES memories(id),\n    FOREIGN KEY(conflicting_memory_id) REFERENCES memories(id)\n);\n\nCREATE TABLE IF NOT EXISTS profiles (\n    id TEXT PRIMARY KEY,\n    name TEXT NOT NULL,\n    profile_json TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\n\nCREATE TABLE IF NOT EXISTS tasks (\n    id TEXT PRIMARY KEY,\n    schema_version TEXT NOT NULL DEFAULT '{SCHEMA_VERSION}',\n    run_id TEXT,\n    title TEXT NOT NULL,\n    intent TEXT NOT NULL,\n    kind TEXT NOT NULL,\n    status TEXT NOT NULL,\n    priority INTEGER NOT NULL DEFAULT 3,\n    project_id TEXT,\n    repo_id TEXT,\n    parent_task_id TEXT,\n    origin TEXT,\n    owner_agent TEXT,\n    blocked_reason TEXT,\n    requires_human_input INTEGER NOT NULL DEFAULT 0,\n    due_at TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(project_id) REFERENCES projects(id),\n    FOREIGN KEY(repo_id) REFERENCES repos(id),\n    FOREIGN KEY(parent_task_id) REFERENCES tasks(id)\n);\n\nCREATE TABLE IF NOT EXISTS task_runs (\n    id TEXT PRIMARY KEY,\n    task_id TEXT NOT NULL,\n    agent_id TEXT NOT NULL,\n    status TEXT NOT NULL,\n    input_payload_json TEXT NOT NULL,\n    result_summary TEXT,\n    error_message TEXT,\n    started_at TEXT NOT NULL,\n    completed_at TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(task_id) REFERENCES tasks(id) ON DELETE CASCADE\n);\n\nCREATE TABLE IF NOT EXISTS artifacts (\n    id TEXT PRIMARY KEY,\n    task_id TEXT NOT NULL,\n    artifact_type TEXT NOT NULL,\n    title TEXT NOT NULL,\n    content TEXT NOT NULL,\n    format TEXT NOT NULL,\n    status TEXT NOT NULL,\n    source_ref TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL,\n    FOREIGN KEY(task_id) REFERENCES tasks(id) ON DELETE CASCADE\n);\n\nCREATE INDEX IF NOT EXISTS idx_memories_scope ON memories(scope);\nCREATE INDEX IF NOT EXISTS idx_memories_status ON memories(status);\nCREATE INDEX IF NOT EXISTS idx_memories_project ON memories(project_id);\nCREATE INDEX IF NOT EXISTS idx_memories_repo ON memories(repo_id);\nCREATE INDEX IF NOT EXISTS idx_memories_type ON memories(type);\nCREATE INDEX IF NOT EXISTS idx_memories_subtype ON memories(subtype);\nCREATE INDEX IF NOT EXISTS idx_memories_run ON memories(run_id);\nCREATE INDEX IF NOT EXISTS idx_memories_task ON memories(task_id);\nCREATE INDEX IF NOT EXISTS idx_memories_url ON memories(url);\nCREATE INDEX IF NOT EXISTS idx_memories_domain ON memories(domain);\nCREATE INDEX IF NOT EXISTS idx_memories_origin_agent ON memories(origin_agent);\nCREATE INDEX IF NOT EXISTS idx_ingestion_state ON ingestion_events(job_state);\nCREATE INDEX IF NOT EXISTS idx_tasks_status ON tasks(status);\nCREATE INDEX IF NOT EXISTS idx_tasks_owner ON tasks(owner_agent);\nCREATE INDEX IF NOT EXISTS idx_tasks_run ON tasks(run_id);\nCREATE INDEX IF NOT EXISTS idx_task_runs_task ON task_runs(task_id);\nCREATE INDEX IF NOT EXISTS idx_task_runs_status ON task_runs(status);\nCREATE INDEX IF NOT EXISTS idx_artifacts_task ON artifacts(task_id);\nCREATE INDEX IF NOT EXISTS idx_maintenance_jobs_due ON maintenance_jobs(next_due_at);\nCREATE INDEX IF NOT EXISTS idx_maintenance_runs_job ON maintenance_runs(job_id);\nCREATE INDEX IF NOT EXISTS idx_memory_conflicts_mem ON memory_conflicts(memory_id);\n\nCREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(\n    memory_id UNINDEXED,\n    title,\n    summary,\n    content\n);\n\"\"\"\n"}],"isError":false,"timestamp":1776636118713}}
{"type":"message","id":"789882ac","parentId":"bb6d9592","timestamp":"2026-04-19T22:01:58.789Z","message":{"role":"toolResult","toolCallId":"call_jhTdIALWhzTqhtiZGv1p1FGM|fc_071e452a5a0ea02e0169e550d664348190b679883e14e3bce5","toolName":"bash","content":[{"type":"text","text":"--- PRAGMA quick_check;\nERR PRAGMA quick_check; DatabaseError('database disk image is malformed')\n--- PRAGMA freelist_count;\n(9,)\n--- PRAGMA page_count;\n(26519,)\n--- PRAGMA journal_mode;\n('delete',)\n--- PRAGMA auto_vacuum;\n(0,)\n"}],"isError":false,"timestamp":1776636118787}}
{"type":"message","id":"93cd3e46","parentId":"789882ac","timestamp":"2026-04-19T22:01:58.789Z","message":{"role":"toolResult","toolCallId":"call_V6IGqQpcJsLkGzMyEwXNmvfG|fc_071e452a5a0ea02e0169e550d6643c8190847d8831d854bce9","toolName":"bash","content":[{"type":"text","text":" 11796564 106076 -rw-r--r--   1 sebas    sebas    108621824 Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\n 11798579 106076 -rw-r--r--   1 sebas    sebas    108621824 Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3.bak-20260419-184938\n 11798580 106076 -rw-r--r--   1 sebas    sebas    108621824 Apr 19 18:49 /mnt/rpi/agents-database/data/shared-agent-memory.recovered-20260419-184949.sqlite3\n 11796498 106076 -rw-r--r--   1 sebas    sebas    108621824 Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3\n"}],"isError":false,"timestamp":1776636118789}}
{"type":"message","id":"24a55fd0","parentId":"93cd3e46","timestamp":"2026-04-19T22:02:41.220Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_C9KoC5ODzSr8L4MccFNsCkhZ|fc_071e452a5a0ea02e0169e550d7fec48190956ba28739465114","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json, os, re\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nout='/mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3'\n\nschema = '''\nPRAGMA foreign_keys = OFF;\nCREATE TABLE IF NOT EXISTS projects (\n    id TEXT PRIMARY KEY,\n    name TEXT NOT NULL,\n    description TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS repos (\n    id TEXT PRIMARY KEY,\n    project_id TEXT,\n    name TEXT NOT NULL,\n    path TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS sources (\n    id TEXT PRIMARY KEY,\n    source_kind TEXT NOT NULL,\n    title TEXT,\n    content TEXT NOT NULL,\n    source_ref TEXT,\n    metadata_json TEXT NOT NULL,\n    created_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS ingestion_events (\n    id TEXT PRIMARY KEY,\n    trigger_type TEXT NOT NULL,\n    source_id TEXT NOT NULL,\n    requested_scope TEXT NOT NULL,\n    job_state TEXT NOT NULL,\n    processor_outcome TEXT,\n    retry_count INTEGER NOT NULL DEFAULT 0,\n    error_message TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    processed_at TEXT\n);\nCREATE TABLE IF NOT EXISTS memories (\n    id TEXT PRIMARY KEY,\n    schema_version TEXT NOT NULL,\n    type TEXT NOT NULL,\n    subtype TEXT,\n    scope TEXT NOT NULL,\n    status TEXT NOT NULL,\n    project_id TEXT,\n    repo_id TEXT,\n    agent_id TEXT,\n    origin_agent TEXT,\n    run_id TEXT,\n    task_id TEXT,\n    url TEXT,\n    domain TEXT,\n    source_kind TEXT NOT NULL,\n    title TEXT NOT NULL,\n    content TEXT NOT NULL,\n    summary TEXT NOT NULL,\n    confidence REAL NOT NULL,\n    freshness REAL NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    observed_at TEXT NOT NULL,\n    source_ref TEXT,\n    evidence_ref TEXT,\n    embedding_json TEXT,\n    metadata_json TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS memory_links (\n    id TEXT PRIMARY KEY,\n    from_memory_id TEXT NOT NULL,\n    to_memory_id TEXT NOT NULL,\n    relation TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS retrieval_logs (\n    id TEXT PRIMARY KEY,\n    query_text TEXT NOT NULL,\n    filters_json TEXT NOT NULL,\n    results_json TEXT NOT NULL,\n    created_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS maintenance_jobs (\n    id TEXT PRIMARY KEY,\n    job_type TEXT NOT NULL,\n    cadence TEXT NOT NULL,\n    interval_minutes INTEGER,\n    window_start TEXT,\n    window_end TEXT,\n    next_due_at TEXT NOT NULL,\n    last_run_at TEXT,\n    last_status TEXT,\n    last_summary TEXT,\n    enabled INTEGER NOT NULL DEFAULT 1,\n    metadata_json TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS maintenance_runs (\n    id TEXT PRIMARY KEY,\n    job_id TEXT NOT NULL,\n    status TEXT NOT NULL,\n    started_at TEXT NOT NULL,\n    completed_at TEXT,\n    summary TEXT,\n    stats_json TEXT NOT NULL,\n    error_message TEXT\n);\nCREATE TABLE IF NOT EXISTS memory_conflicts (\n    id TEXT PRIMARY KEY,\n    memory_id TEXT NOT NULL,\n    conflicting_memory_id TEXT NOT NULL,\n    reason TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS profiles (\n    id TEXT PRIMARY KEY,\n    name TEXT NOT NULL,\n    profile_json TEXT NOT NULL,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS tasks (\n    id TEXT PRIMARY KEY,\n    schema_version TEXT NOT NULL,\n    run_id TEXT,\n    title TEXT NOT NULL,\n    intent TEXT NOT NULL,\n    kind TEXT NOT NULL,\n    status TEXT NOT NULL,\n    priority INTEGER NOT NULL DEFAULT 3,\n    project_id TEXT,\n    repo_id TEXT,\n    parent_task_id TEXT,\n    origin TEXT,\n    owner_agent TEXT,\n    blocked_reason TEXT,\n    requires_human_input INTEGER NOT NULL DEFAULT 0,\n    due_at TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS task_runs (\n    id TEXT PRIMARY KEY,\n    task_id TEXT NOT NULL,\n    agent_id TEXT NOT NULL,\n    status TEXT NOT NULL,\n    input_payload_json TEXT NOT NULL,\n    result_summary TEXT,\n    error_message TEXT,\n    started_at TEXT NOT NULL,\n    completed_at TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL\n);\nCREATE TABLE IF NOT EXISTS artifacts (\n    id TEXT PRIMARY KEY,\n    task_id TEXT NOT NULL,\n    artifact_type TEXT NOT NULL,\n    title TEXT NOT NULL,\n    content TEXT NOT NULL,\n    format TEXT NOT NULL,\n    status TEXT NOT NULL,\n    source_ref TEXT,\n    created_at TEXT NOT NULL,\n    updated_at TEXT NOT NULL,\n    metadata_json TEXT NOT NULL\n);\n'''\n\nif os.path.exists(out):\n    os.remove(out)\n\ndst = sqlite3.connect(out)\ndst.executescript(schema)\n\ndef quote_ident(name):\n    return '\"' + name.replace('\"','\"\"') + '\"'\n\ndef get_cols(conn, table):\n    return [r[1] for r in conn.execute(f'PRAGMA table_info({quote_ident(table)})')]\n\nsrc_con = sqlite3.connect(src)\n\nreport = {}\nfor table in ['projects','repos','sources','ingestion_events','memories','memory_links','retrieval_logs','maintenance_jobs','maintenance_runs','memory_conflicts','profiles','tasks','task_runs','artifacts']:\n    try:\n        src_cols = get_cols(src_con, table)\n        dst_cols = get_cols(dst, table)\n        common = [c for c in src_cols if c in dst_cols]\n        rows = src_con.execute(f'SELECT {\", \".join(quote_ident(c) for c in common)} FROM {quote_ident(table)}')\n        n = 0\n        for row in rows:\n            try:\n                dst.execute(\n                    f'INSERT OR REPLACE INTO {quote_ident(table)} ({\", \".join(quote_ident(c) for c in common)}) VALUES ({\", \".join([\"?\"]*len(common))})',\n                    row,\n                )\n                n += 1\n            except Exception:\n                pass\n        dst.commit()\n        report[table] = {'copied': n, 'common_cols': len(common)}\n    except Exception as e:\n        report[table] = {'error': repr(e)}\n\n# indexes + fts\ntry:\n    dst.executescript('''\n    CREATE INDEX IF NOT EXISTS idx_memories_scope ON memories(scope);\n    CREATE INDEX IF NOT EXISTS idx_memories_status ON memories(status);\n    CREATE INDEX IF NOT EXISTS idx_memories_project ON memories(project_id);\n    CREATE INDEX IF NOT EXISTS idx_memories_repo ON memories(repo_id);\n    CREATE INDEX IF NOT EXISTS idx_memories_type ON memories(type);\n    CREATE INDEX IF NOT EXISTS idx_memories_subtype ON memories(subtype);\n    CREATE INDEX IF NOT EXISTS idx_memories_run ON memories(run_id);\n    CREATE INDEX IF NOT EXISTS idx_memories_task ON memories(task_id);\n    CREATE INDEX IF NOT EXISTS idx_memories_url ON memories(url);\n    CREATE INDEX IF NOT EXISTS idx_memories_domain ON memories(domain);\n    CREATE INDEX IF NOT EXISTS idx_memories_origin_agent ON memories(origin_agent);\n    CREATE INDEX IF NOT EXISTS idx_ingestion_state ON ingestion_events(job_state);\n    CREATE INDEX IF NOT EXISTS idx_tasks_status ON tasks(status);\n    CREATE INDEX IF NOT EXISTS idx_tasks_owner ON tasks(owner_agent);\n    CREATE INDEX IF NOT EXISTS idx_tasks_run ON tasks(run_id);\n    CREATE INDEX IF NOT EXISTS idx_task_runs_task ON task_runs(task_id);\n    CREATE INDEX IF NOT EXISTS idx_task_runs_status ON task_runs(status);\n    CREATE INDEX IF NOT EXISTS idx_artifacts_task ON artifacts(task_id);\n    CREATE INDEX IF NOT EXISTS idx_maintenance_jobs_due ON maintenance_jobs(next_due_at);\n    CREATE INDEX IF NOT EXISTS idx_maintenance_runs_job ON maintenance_runs(job_id);\n    CREATE INDEX IF NOT EXISTS idx_memory_conflicts_mem ON memory_conflicts(memory_id);\n    CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(memory_id UNINDEXED, title, summary, content);\n    DELETE FROM memories_fts;\n    INSERT INTO memories_fts(memory_id, title, summary, content)\n    SELECT id, title, summary, content FROM memories;\n    ''')\n    dst.commit()\n    report['fts'] = 'rebuilt'\nexcept Exception as e:\n    report['fts_error'] = repr(e)\n\ntry:\n    qc = dst.execute('PRAGMA quick_check;').fetchall()\n    report['quick_check'] = qc[:10]\nexcept Exception as e:\n    report['quick_check_error'] = repr(e)\n\nfor table in ['memories','tasks','artifacts','projects','repos','retrieval_logs','task_runs','maintenance_jobs','maintenance_runs']:\n    try:\n        report[f'count_{table}'] = dst.execute(f'SELECT COUNT(*) FROM {table}').fetchone()[0]\n    except Exception as e:\n        report[f'count_{table}_error'] = repr(e)\n\nprint(json.dumps(report, indent=2))\ndst.close()\nsrc_con.close()\nPY\nls -lh /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3","timeout":1200}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2011,"output":2281,"cacheRead":29952,"cacheWrite":0,"totalTokens":34244,"cost":{"input":0.005027500000000001,"output":0.034215,"cacheRead":0.007488,"cacheWrite":0,"total":0.0467305}},"stopReason":"toolUse","timestamp":1776636118791,"responseId":"resp_071e452a5a0ea02e0169e550d722d48190a33e6b88ef3c102d"}}
{"type":"message","id":"55022030","parentId":"24a55fd0","timestamp":"2026-04-19T22:02:58.641Z","message":{"role":"toolResult","toolCallId":"call_C9KoC5ODzSr8L4MccFNsCkhZ|fc_071e452a5a0ea02e0169e550d7fec48190956ba28739465114","toolName":"bash","content":[{"type":"text","text":"{\n  \"projects\": {\n    \"copied\": 4,\n    \"common_cols\": 5\n  },\n  \"repos\": {\n    \"copied\": 7,\n    \"common_cols\": 6\n  },\n  \"sources\": {\n    \"copied\": 0,\n    \"common_cols\": 7\n  },\n  \"ingestion_events\": {\n    \"copied\": 0,\n    \"common_cols\": 11\n  },\n  \"memories\": {\n    \"error\": \"DatabaseError('database disk image is malformed')\"\n  },\n  \"memory_links\": {\n    \"copied\": 445,\n    \"common_cols\": 6\n  },\n  \"retrieval_logs\": {\n    \"error\": \"DatabaseError('database disk image is malformed')\"\n  },\n  \"maintenance_jobs\": {\n    \"copied\": 4,\n    \"common_cols\": 14\n  },\n  \"maintenance_runs\": {\n    \"copied\": 41,\n    \"common_cols\": 8\n  },\n  \"memory_conflicts\": {\n    \"copied\": 0,\n    \"common_cols\": 6\n  },\n  \"profiles\": {\n    \"copied\": 0,\n    \"common_cols\": 5\n  },\n  \"tasks\": {\n    \"copied\": 194,\n    \"common_cols\": 19\n  },\n  \"task_runs\": {\n    \"copied\": 63,\n    \"common_cols\": 12\n  },\n  \"artifacts\": {\n    \"copied\": 163,\n    \"common_cols\": 11\n  },\n  \"fts\": \"rebuilt\",\n  \"quick_check\": [\n    [\n      \"ok\"\n    ]\n  ],\n  \"count_memories\": 288,\n  \"count_tasks\": 194,\n  \"count_artifacts\": 163,\n  \"count_projects\": 4,\n  \"count_repos\": 7,\n  \"count_retrieval_logs\": 6848,\n  \"count_task_runs\": 63,\n  \"count_maintenance_jobs\": 4,\n  \"count_maintenance_runs\": 41\n}\n-rw-r--r-- 1 sebas sebas 102M Apr 19 19:02 /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3\n"}],"isError":false,"timestamp":1776636178641}}
{"type":"message","id":"ba794162","parentId":"55022030","timestamp":"2026-04-19T22:03:07.154Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_LjHjJLglZe2edpbbetueCNQ0|fc_071e452a5a0ea02e0169e551161d688190b1905dbc09c46210","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3\nfor p in [\n '/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3',\n '/mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3',\n]:\n    con=sqlite3.connect(p)\n    cur=con.cursor()\n    print('DB', p)\n    for q in [\n        'SELECT COUNT(*) FROM memories',\n        'SELECT COUNT(*) FROM retrieval_logs',\n        'SELECT COUNT(*) FROM memory_links',\n        'SELECT COUNT(*) FROM tasks',\n        'SELECT COUNT(*) FROM artifacts',\n    ]:\n        try:\n            print(q, cur.execute(q).fetchone()[0])\n        except Exception as e:\n            print(q, 'ERR', repr(e))\n    try:\n        print('sample memories ids', cur.execute('SELECT id, title FROM memories LIMIT 5').fetchall())\n    except Exception as e:\n        print('sample memories ERR', repr(e))\n    print()\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":692,"output":267,"cacheRead":34048,"cacheWrite":0,"totalTokens":35007,"cost":{"input":0.0017300000000000002,"output":0.004005,"cacheRead":0.008512,"cacheWrite":0,"total":0.014247000000000001}},"stopReason":"toolUse","timestamp":1776636178644,"responseId":"resp_071e452a5a0ea02e0169e551134c008190b69ada5e4206106e"}}
{"type":"message","id":"e9c30105","parentId":"ba794162","timestamp":"2026-04-19T22:03:07.207Z","message":{"role":"toolResult","toolCallId":"call_LjHjJLglZe2edpbbetueCNQ0|fc_071e452a5a0ea02e0169e551161d688190b1905dbc09c46210","toolName":"bash","content":[{"type":"text","text":"DB /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nSELECT COUNT(*) FROM memories 320\nSELECT COUNT(*) FROM retrieval_logs 6901\nSELECT COUNT(*) FROM memory_links 445\nSELECT COUNT(*) FROM tasks 194\nSELECT COUNT(*) FROM artifacts 163\nsample memories ids [('legacy_run_9fdccb34-cf1e-47bd-b133-a224f363a6d4', 'Research run: Investigate personal assistant patterns'), ('legacy_run_a8512264-8cd5-4c3c-b62f-7528625227f1', 'Research run: Verify capture-url flow'), ('legacy_run_55b6eaa0-9ff5-438c-a375-50f0452079cb', 'Research run: Drive Ballbox payment integration toward Volvox-style demo on vending machine Android flow'), ('legacy_run_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7', 'Research run: Source 50+ inch China displays for Ballbox advertising in padel venues'), ('legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0', 'Research run: Test intake flow')]\n\nDB /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3\nSELECT COUNT(*) FROM memories 288\nSELECT COUNT(*) FROM retrieval_logs 6848\nSELECT COUNT(*) FROM memory_links 445\nSELECT COUNT(*) FROM tasks 194\nSELECT COUNT(*) FROM artifacts 163\nsample memories ids [('legacy_run_9fdccb34-cf1e-47bd-b133-a224f363a6d4', 'Research run: Investigate personal assistant patterns'), ('legacy_run_a8512264-8cd5-4c3c-b62f-7528625227f1', 'Research run: Verify capture-url flow'), ('legacy_run_55b6eaa0-9ff5-438c-a375-50f0452079cb', 'Research run: Drive Ballbox payment integration toward Volvox-style demo on vending machine Android flow'), ('legacy_run_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7', 'Research run: Source 50+ inch China displays for Ballbox advertising in padel venues'), ('legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0', 'Research run: Test intake flow')]\n\n"}],"isError":false,"timestamp":1776636187207}}
{"type":"message","id":"81cfa66e","parentId":"e9c30105","timestamp":"2026-04-19T22:03:13.390Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_o9Ym3DQMttfl2ZSWaFDO8pdU|fc_071e452a5a0ea02e0169e5511ce6208190a835991207d5f592","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nout='/mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3'\n\ns=sqlite3.connect(src)\nd=sqlite3.connect(out)\nsc=s.cursor(); dc=d.cursor()\n\nsrc_ids=[]\ntry:\n    for row in sc.execute('SELECT id FROM memories'):\n        src_ids.append(row[0])\nexcept Exception as e:\n    print('src_iter_err', repr(e))\n\ndst_ids={row[0] for row in dc.execute('SELECT id FROM memories')}\nmissing=[x for x in src_ids if x not in dst_ids]\nprint('src_seen', len(src_ids))\nprint('dst_ids', len(dst_ids))\nprint('missing', len(missing))\nprint(json.dumps(missing[:50], indent=2))\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":742,"output":242,"cacheRead":34816,"cacheWrite":0,"totalTokens":35800,"cost":{"input":0.001855,"output":0.00363,"cacheRead":0.008704,"cacheWrite":0,"total":0.014189}},"stopReason":"toolUse","timestamp":1776636187209,"responseId":"resp_071e452a5a0ea02e0169e5511c1f3881908aa288077c0d6c44"}}
{"type":"message","id":"a35b6063","parentId":"81cfa66e","timestamp":"2026-04-19T22:03:13.448Z","message":{"role":"toolResult","toolCallId":"call_o9Ym3DQMttfl2ZSWaFDO8pdU|fc_071e452a5a0ea02e0169e5511ce6208190a835991207d5f592","toolName":"bash","content":[{"type":"text","text":"src_iter_err DatabaseError('database disk image is malformed')\nsrc_seen 264\ndst_ids 288\nmissing 22\n[\n  \"9be235c5-e438-4f89-a35e-9c9582574016\",\n  \"mem_10b251a5cd6844faaeec93ff7019c086\",\n  \"mem_1349693993ae4981b89dd9dab290d66d\",\n  \"mem_139063138eea4721bdac8d830fc0f49b\",\n  \"mem_30a32043ffd8430fa1b3d82e409d7b53\",\n  \"mem_3143b84805404c41a135ea037c307c7e\",\n  \"mem_3996cdf0bfd4413e8c48fbc4094b84a9\",\n  \"mem_4f5ebfd765e34937b82ccf047dba60f7\",\n  \"mem_54eeaf9633f34ac087975e9ad8fcaa37\",\n  \"mem_5823a14baa5140e3a8cd9bb92c799eb3\",\n  \"mem_5ec2c706538441349a16497f0d219796\",\n  \"mem_65dcb57e2d6f45b08d85205168dca808\",\n  \"mem_70d7fe1e42bf4b988b34cc4f3234a66a\",\n  \"mem_7daf2b19b42640e09a23d0579e3df37c\",\n  \"mem_889160a130ef4d1bbac2eba6370c0797\",\n  \"mem_96934fac02314ee2b5707504cd934815\",\n  \"mem_97d87af25ab948359701126e057de04c\",\n  \"mem_c6ab12f86d364ff89a3bebecfdd35b24\",\n  \"mem_c8b6a1ee582446319abb7eab352eb096\",\n  \"mem_ca9ef5309697403c9e3ba37f2867f71e\",\n  \"mem_cba730d4ea2f4679bb78d5e7586c9696\",\n  \"mem_dab474c6db644f3f9e33d3f3179ca966\"\n]\n"}],"isError":false,"timestamp":1776636193448}}
{"type":"message","id":"27abb143","parentId":"a35b6063","timestamp":"2026-04-19T22:03:19.976Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_jXrvytr2Ylm2GoGZHrYzJeCm|fc_071e452a5a0ea02e0169e5512306748190b5706aab0666d340","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(src)\ncur=con.cursor()\nids=[\n'9be235c5-e438-4f89-a35e-9c9582574016',\n'mem_10b251a5cd6844faaeec93ff7019c086',\n'mem_1349693993ae4981b89dd9dab290d66d',\n'mem_139063138eea4721bdac8d830fc0f49b',\n'mem_30a32043ffd8430fa1b3d82e409d7b53',\n]\nfor mid in ids:\n    try:\n        row=cur.execute('SELECT id,title,type,subtype,run_id,task_id FROM memories WHERE id=?',(mid,)).fetchone()\n        print(mid, row)\n    except Exception as e:\n        print(mid, 'ERR', repr(e))\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":628,"output":264,"cacheRead":35712,"cacheWrite":0,"totalTokens":36604,"cost":{"input":0.0015700000000000002,"output":0.00396,"cacheRead":0.008928,"cacheWrite":0,"total":0.014458}},"stopReason":"toolUse","timestamp":1776636193450,"responseId":"resp_071e452a5a0ea02e0169e55121f1d481908fc634d1088ac984"}}
{"type":"message","id":"67a875ec","parentId":"27abb143","timestamp":"2026-04-19T22:03:20.029Z","message":{"role":"toolResult","toolCallId":"call_jXrvytr2Ylm2GoGZHrYzJeCm|fc_071e452a5a0ea02e0169e5512306748190b5706aab0666d340","toolName":"bash","content":[{"type":"text","text":"9be235c5-e438-4f89-a35e-9c9582574016 ERR DatabaseError('database disk image is malformed')\nmem_10b251a5cd6844faaeec93ff7019c086 ('mem_10b251a5cd6844faaeec93ff7019c086', 'memory-write skill smoke test', 'artifact', 'skill_smoke_test', None, None)\nmem_1349693993ae4981b89dd9dab290d66d ERR DatabaseError('database disk image is malformed')\nmem_139063138eea4721bdac8d830fc0f49b ('mem_139063138eea4721bdac8d830fc0f49b', 'Nginx serves mp3-share from portal', 'project', None, None, None)\nmem_30a32043ffd8430fa1b3d82e409d7b53 ERR DatabaseError('database disk image is malformed')\n"}],"isError":false,"timestamp":1776636200029}}
{"type":"message","id":"49a8e791","parentId":"67a875ec","timestamp":"2026-04-19T22:03:29.651Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_B4261hos9XGzvPEy6DS0VxPD|fc_071e452a5a0ea02e0169e5512963d88190af324c78af63c4fe","name":"bash","arguments":{"command":"set -euo pipefail\ncp -a /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3 /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nsha256sum /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3 /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3\nsystemctl --user restart agents-database-http.service\nsleep 2\ncurl -sS -m 10 -D - -o /tmp/adbstatus3.out http://127.0.0.1:8091/api/status\nprintf '\\n--- body ---\\n'\ncat /tmp/adbstatus3.out\nprintf '\\n--- write test ---\\n'\npython3 - <<'PY'\nimport json, urllib.request\npayload={\n  'type':'episode','scope':'global','title':'repair test memory','content':'post-rebuild write test','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'\n}\nreq=urllib.request.Request('http://127.0.0.1:8091/api/ingest', data=json.dumps(payload).encode(), headers={'Content-Type':'application/json'}, method='POST')\nwith urllib.request.urlopen(req, timeout=20) as r:\n    print(r.status)\n    print(r.read().decode())\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":345,"output":321,"cacheRead":36480,"cacheWrite":0,"totalTokens":37146,"cost":{"input":0.0008625000000000001,"output":0.004815,"cacheRead":0.00912,"cacheWrite":0,"total":0.0147975}},"stopReason":"toolUse","timestamp":1776636200031,"responseId":"resp_071e452a5a0ea02e0169e551286190819089d205830c69cefa"}}
{"type":"message","id":"62196669","parentId":"49a8e791","timestamp":"2026-04-19T22:03:47.437Z","message":{"role":"toolResult","toolCallId":"call_B4261hos9XGzvPEy6DS0VxPD|fc_071e452a5a0ea02e0169e5512963d88190af324c78af63c4fe","toolName":"bash","content":[{"type":"text","text":"d9fbc9cddbdfe0cbdef6fd881c3c3d39404cbc858a04137542b3c4020183d47b  /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nd9fbc9cddbdfe0cbdef6fd881c3c3d39404cbc858a04137542b3c4020183d47b  /mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3\nHTTP/1.0 200 OK\r\nServer: BaseHTTP/0.6 Python/3.13.5\r\nDate: Sun, 19 Apr 2026 22:03:47 GMT\r\nContent-Type: application/json; charset=utf-8\r\nContent-Length: 261\r\nAccess-Control-Allow-Origin: *\r\nAccess-Control-Allow-Headers: Content-Type\r\nAccess-Control-Allow-Methods: GET,POST,PATCH,OPTIONS\r\n\r\n\n--- body ---\n{\"ok\": true, \"db_path\": \"/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\", \"dashboard\": {\"memories\": 288, \"tasks\": 194, \"artifacts\": 163, \"projects\": 4, \"repos\": 7}, \"audit\": {\"schema_version\": \"shared-agent-memory-v2\", \"memories\": 288, \"tasks\": 194}}\n--- write test ---\nTraceback (most recent call last):\n  File \"<stdin>\", line 6, in <module>\n  File \"/usr/lib/python3.13/urllib/request.py\", line 189, in urlopen\n    return opener.open(url, data, timeout)\n           ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 489, in open\n    response = self._open(req, data)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 506, in _open\n    result = self._call_chain(self.handle_open, protocol, protocol +\n                              '_open', req)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 466, in _call_chain\n    result = func(*args)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 1348, in http_open\n    return self.do_open(http.client.HTTPConnection, req)\n           ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 1323, in do_open\n    r = h.getresponse()\n  File \"/usr/lib/python3.13/http/client.py\", line 1430, in getresponse\n    response.begin()\n    ~~~~~~~~~~~~~~^^\n  File \"/usr/lib/python3.13/http/client.py\", line 331, in begin\n    version, status, reason = self._read_status()\n                              ~~~~~~~~~~~~~~~~~^^\n  File \"/usr/lib/python3.13/http/client.py\", line 300, in _read_status\n    raise RemoteDisconnected(\"Remote end closed connection without\"\n                             \" response\")\nhttp.client.RemoteDisconnected: Remote end closed connection without response\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776636227436}}
{"type":"message","id":"fd24ce17","parentId":"62196669","timestamp":"2026-04-19T22:04:04.908Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_fZ6yY6znCPk9GBlFtr5GUVb7|fc_071e452a5a0ea02e0169e551547274819099b4b07a06b4c69d","name":"bash","arguments":{"command":"journalctl --user -u agents-database-http.service -n 60 --no-pager | tail -n 40","timeout":120}},{"type":"toolCall","id":"call_ZVFdrgIgxBNBIL9dEScK4jmg|fc_071e452a5a0ea02e0169e5515472948190ac199473798ae803","name":"bash","arguments":{"command":"python3 - <<'PY'\nimport sqlite3\np='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ncon=sqlite3.connect(p)\ncur=con.cursor()\nfor q in [\n 'PRAGMA quick_check;',\n 'SELECT COUNT(*) FROM memories',\n 'SELECT COUNT(*) FROM memories_fts',\n 'SELECT COUNT(*) FROM sqlite_master WHERE name = \"memories_fts\"',\n]:\n    try:\n        print('---', q)\n        print(cur.execute(q).fetchall()[:5])\n    except Exception as e:\n        print('ERR', q, repr(e))\nPY","timeout":120}},{"type":"toolCall","id":"call_KHKMyCT7Em8TWV8fFDlNcWo4|fc_071e452a5a0ea02e0169e5515472a48190873ce9e06e64e468","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/service.py","offset":60,"limit":220}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":824,"output":258,"cacheRead":36992,"cacheWrite":0,"totalTokens":38074,"cost":{"input":0.00206,"output":0.00387,"cacheRead":0.009248,"cacheWrite":0,"total":0.015178}},"stopReason":"toolUse","timestamp":1776636227438,"responseId":"resp_071e452a5a0ea02e0169e5514642f48190b77576bd22f36a9e"}}
{"type":"message","id":"a5ac932b","parentId":"fd24ce17","timestamp":"2026-04-19T22:04:04.934Z","message":{"role":"toolResult","toolCallId":"call_fZ6yY6znCPk9GBlFtr5GUVb7|fc_071e452a5a0ea02e0169e551547274819099b4b07a06b4c69d","toolName":"bash","content":[{"type":"text","text":"-- No entries --\nNo journal files were found.\n"}],"isError":false,"timestamp":1776636244934}}
{"type":"message","id":"1d083f4c","parentId":"a5ac932b","timestamp":"2026-04-19T22:04:05.024Z","message":{"role":"toolResult","toolCallId":"call_ZVFdrgIgxBNBIL9dEScK4jmg|fc_071e452a5a0ea02e0169e5515472948190ac199473798ae803","toolName":"bash","content":[{"type":"text","text":"--- PRAGMA quick_check;\n[('ok',)]\n--- SELECT COUNT(*) FROM memories\n[(288,)]\n--- SELECT COUNT(*) FROM memories_fts\n[(288,)]\n--- SELECT COUNT(*) FROM sqlite_master WHERE name = \"memories_fts\"\n[(1,)]\n"}],"isError":false,"timestamp":1776636245024}}
{"type":"message","id":"e0cdbde0","parentId":"1d083f4c","timestamp":"2026-04-19T22:04:05.054Z","message":{"role":"toolResult","toolCallId":"call_KHKMyCT7Em8TWV8fFDlNcWo4|fc_071e452a5a0ea02e0169e5515472a48190873ce9e06e64e468","toolName":"read","content":[{"type":"text","text":"\n\nclass MemoryService:\n    def __init__(self, db_path: str) -> None:\n        self.store = SQLiteStore(db_path)\n        self._maintenance_check_running = False\n        self.store.initialize()\n        self.migrate_v2()\n        self._ensure_default_jobs()\n        self._run_opportunistic_maintenance(limit=10)\n\n    def create_memory(self, memory_input: dict[str, Any]) -> dict[str, Any]:\n        now = utcnow()\n        metadata = dict(memory_input.get(\"metadata\") or {})\n        subtype = memory_input.get(\"subtype\")\n        run_id = memory_input.get(\"run_id\")\n        task_id = memory_input.get(\"task_id\")\n        url = memory_input.get(\"url\")\n        domain = memory_input.get(\"domain\") or (urlparse(url).netloc if url else None)\n        origin_agent = memory_input.get(\"origin_agent\") or metadata.get(\"origin_agent\") or memory_input.get(\"agent_id\")\n        record = {\n            \"id\": memory_input.get(\"id\", make_id(\"mem\")),\n            \"schema_version\": memory_input.get(\"schema_version\", SCHEMA_VERSION),\n            \"type\": memory_input[\"type\"],\n            \"subtype\": subtype,\n            \"scope\": memory_input[\"scope\"],\n            \"status\": memory_input.get(\"status\", \"active\"),\n            \"project_id\": memory_input.get(\"project_id\"),\n            \"repo_id\": memory_input.get(\"repo_id\"),\n            \"agent_id\": memory_input.get(\"agent_id\"),\n            \"origin_agent\": origin_agent,\n            \"run_id\": run_id,\n            \"task_id\": task_id,\n            \"url\": url,\n            \"domain\": domain,\n            \"source_kind\": memory_input.get(\"source_kind\", \"manual\"),\n            \"title\": memory_input[\"title\"],\n            \"content\": memory_input[\"content\"],\n            \"summary\": memory_input.get(\"summary\") or self._make_summary(memory_input[\"content\"]),\n            \"confidence\": float(memory_input.get(\"confidence\", 1.0)),\n            \"freshness\": float(memory_input.get(\"freshness\", 1.0)),\n            \"created_at\": memory_input.get(\"created_at\", now),\n            \"updated_at\": now,\n            \"observed_at\": memory_input.get(\"observed_at\", now),\n            \"source_ref\": memory_input.get(\"source_ref\"),\n            \"evidence_ref\": memory_input.get(\"evidence_ref\"),\n            \"embedding_json\": self._encode_embedding(memory_input.get(\"embedding\")),\n            \"metadata_json\": self.store.dumps(metadata),\n        }\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                INSERT OR REPLACE INTO memories (\n                    id, schema_version, type, subtype, scope, status, project_id, repo_id, agent_id, origin_agent,\n                    run_id, task_id, url, domain, source_kind, title, content, summary, confidence, freshness,\n                    created_at, updated_at, observed_at, source_ref, evidence_ref, embedding_json, metadata_json\n                ) VALUES (\n                    :id, :schema_version, :type, :subtype, :scope, :status, :project_id, :repo_id, :agent_id, :origin_agent,\n                    :run_id, :task_id, :url, :domain, :source_kind, :title, :content, :summary, :confidence, :freshness,\n                    :created_at, :updated_at, :observed_at, :source_ref, :evidence_ref, :embedding_json, :metadata_json\n                )\n                \"\"\",\n                record,\n            )\n            self._upsert_fts(conn, record)\n        self._run_opportunistic_maintenance(limit=1)\n        return self.get_memory(record[\"id\"])\n\n    def ingest(self, memory_input: dict[str, Any]) -> dict[str, Any]:\n        return self.create_memory(memory_input)\n\n    def capture_session(self, source_ref: str, scope: str, content: str, **metadata: Any) -> dict[str, Any]:\n        return self._capture_source(\n            trigger_type=\"session_close\",\n            source_kind=\"run\",\n            source_ref=source_ref,\n            scope=scope,\n            content=content,\n            metadata=metadata,\n        )\n\n    def capture_conversation(\n        self, source_ref: str, scope: str, content: str, capture_mode: str = \"manual_import\", **metadata: Any\n    ) -> dict[str, Any]:\n        metadata = {\"capture_mode\": capture_mode, **metadata}\n        return self._capture_source(\n            trigger_type=\"conversation_capture\",\n            source_kind=\"conversation\",\n            source_ref=source_ref,\n            scope=scope,\n            content=content,\n            metadata=metadata,\n        )\n\n    def search(\n        self,\n        query: str,\n        scopes: list[str] | None = None,\n        filters: dict[str, Any] | None = None,\n        limit: int = 10,\n        include_inbox: bool = False,\n    ) -> dict[str, Any]:\n        filters = filters or {}\n        query_terms = [term for term in normalize_text(query).split() if term]\n        sql = [\"SELECT * FROM memories WHERE 1=1\"]\n        params: list[Any] = []\n\n        if scopes:\n            sql.append(f\"AND scope IN ({','.join('?' for _ in scopes)})\")\n            params.extend(scopes)\n        if not include_inbox:\n            sql.append(\"AND status = ?\")\n            params.append(\"active\")\n        params.extend(self._memory_filter_sql(sql, filters))\n\n        with self.store.connection() as conn:\n            rows = [self._row_to_memory(row) for row in conn.execute(\" \".join(sql), params)]\n\n        results: list[SearchResult] = []\n        query_embedding = self._text_embedding(query) if query_terms else []\n        for row in rows:\n            haystack = normalize_text(\" \".join([row[\"title\"], row[\"summary\"], row[\"content\"]]))\n            lexical = self._lexical_score(query_terms, haystack)\n            semantic = self._semantic_score(query_embedding, row.get(\"embedding\")) if query_terms else 0.0\n            facet = self._facet_score(row, filters)\n            if query_terms and lexical == 0 and semantic == 0 and facet == 0:\n                continue\n            score = facet * 0.45 + lexical * 0.3 + semantic * 0.15 + row[\"confidence\"] * 0.06 + row[\"freshness\"] * 0.04\n            explanation = (\n                f\"facets={facet:.2f} lexical={lexical:.2f} semantic={semantic:.2f} \"\n                f\"confidence={row['confidence']:.2f} freshness={row['freshness']:.2f}\"\n            )\n            results.append(SearchResult(row, score, explanation, facet, lexical, semantic))\n\n        ordered = sorted(\n            results,\n            key=lambda item: (\n                item.facet_score,\n                item.lexical_score,\n                item.semantic_score,\n                item.memory[\"confidence\"],\n                item.memory[\"freshness\"],\n                item.memory[\"updated_at\"],\n            ),\n            reverse=True,\n        )[:limit]\n        payload = [item.as_dict() for item in ordered]\n\n        retrieval_id = make_id(\"ret\")\n        with self.store.connection() as conn:\n            conn.execute(\n                \"INSERT INTO retrieval_logs (id, query_text, filters_json, results_json, created_at) VALUES (?, ?, ?, ?, ?)\",\n                (\n                    retrieval_id,\n                    query,\n                    self.store.dumps({\"scopes\": scopes, \"filters\": filters, \"include_inbox\": include_inbox}),\n                    self.store.dumps(payload),\n                    utcnow(),\n                ),\n            )\n        return {\"retrieval_id\": retrieval_id, \"results\": payload}\n\n    def context_for(\n        self, project: str | None = None, repo: str | None = None, agent: str | None = None, task: str | None = None\n    ) -> dict[str, Any]:\n        profile_facts = self.list_memories(status=\"active\", scope=\"global\", memory_type=\"profile\", limit=8)\n        project_filters = {\"project_id\": project, \"repo_id\": repo}\n        active_decisions = self.list_memories(\n            status=\"active\",\n            scope=\"project\" if project else None,\n            memory_type=\"decision\",\n            project_id=project,\n            repo_id=repo,\n            limit=8,\n        )\n        project_memories = self.list_memories(\n            status=\"active\",\n            project_id=project,\n            repo_id=repo,\n            limit=12,\n        )\n        project_memories = [item for item in project_memories if item[\"type\"] in {\"project\", \"decision\", \"artifact\", \"episode\"}][:12]\n        recent_episodes = self.list_memories(\n            status=\"active\",\n            memory_type=\"episode\",\n            project_id=project,\n            repo_id=repo,\n            limit=10,\n        )\n        task_relevant_artifacts = self.list_memories(\n            status=\"active\",\n            memory_type=\"artifact\",\n            project_id=project,\n            repo_id=repo,\n            task_id=task,\n            limit=10,\n        )\n        if task and not task_relevant_artifacts:\n            task_relevant_artifacts = self.search(task, filters={**project_filters, \"type\": \"artifact\"}, limit=5)[\"results\"]\n        citations = [\n            item[\"id\"]\n            for item in [*profile_facts, *project_memories, *active_decisions, *recent_episodes]\n            if isinstance(item, dict) and \"id\" in item\n        ]\n        return {\n            \"profile_facts\": profile_facts,\n            \"project_memories\": project_memories,\n            \"active_decisions\": active_decisions,\n            \"recent_episodes\": recent_episodes,\n            \"task_relevant_artifacts\": task_relevant_artifacts,\n            \"citations\": citations,\n            \"agent_id\": agent,\n        }\n\n    def consolidate(self, inbox_items: list[str]) -> dict[str, Any]:\n        promoted: list[str] = []\n        linked: list[dict[str, str]] = []\n        with self.store.connection() as conn:\n            for memory_id in inbox_items:\n                row = conn.execute(\"SELECT * FROM memories WHERE id = ?\", (memory_id,)).fetchone()\n\n[1427 more lines in file. Use offset=280 to continue.]"}],"isError":false,"timestamp":1776636245025}}
{"type":"message","id":"31d3b7de","parentId":"e0cdbde0","timestamp":"2026-04-19T22:04:08.884Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_EzGruatKiJxKRLUVaO0ISz5a|fc_071e452a5a0ea02e0169e5515651848190bc46f2eb94acb920","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/service.py","offset":1460,"limit":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":2430,"output":39,"cacheRead":37888,"cacheWrite":0,"totalTokens":40357,"cost":{"input":0.0060750000000000005,"output":0.000585,"cacheRead":0.009472,"cacheWrite":0,"total":0.016132}},"stopReason":"toolUse","timestamp":1776636245056,"responseId":"resp_071e452a5a0ea02e0169e5515565808190800d39dfb9a68e51"}}
{"type":"message","id":"660104e5","parentId":"31d3b7de","timestamp":"2026-04-19T22:04:08.905Z","message":{"role":"toolResult","toolCallId":"call_EzGruatKiJxKRLUVaO0ISz5a|fc_071e452a5a0ea02e0169e5515651848190bc46f2eb94acb920","toolName":"read","content":[{"type":"text","text":"        self,\n        run_id: str,\n        *,\n        status: str,\n        summary: str | None = None,\n        stats: dict[str, Any] | None = None,\n        error_message: str | None = None,\n    ) -> dict[str, Any]:\n        now = utcnow()\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                UPDATE maintenance_runs\n                SET status = ?, completed_at = ?, summary = ?, stats_json = ?, error_message = ?\n                WHERE id = ?\n                \"\"\",\n                (status, now, summary, self.store.dumps(stats or {}), error_message, run_id),\n            )\n        return self.get_maintenance_run(run_id)\n\n    def get_maintenance_run(self, run_id: str) -> dict[str, Any]:\n        with self.store.connection() as conn:\n            row = conn.execute(\"SELECT * FROM maintenance_runs WHERE id = ?\", (run_id,)).fetchone()\n            if row is None:\n                raise KeyError(run_id)\n            return self._row_to_maintenance_run(row)\n\n    def list_maintenance_runs(self, *, job_id: str | None = None, limit: int = 20) -> list[dict[str, Any]]:\n        sql = \"SELECT * FROM maintenance_runs WHERE 1=1\"\n        params: list[Any] = []\n        if job_id is not None:\n            sql += \" AND job_id = ?\"\n            params.append(job_id)\n        sql += \" ORDER BY started_at DESC LIMIT ?\"\n        params.append(limit)\n        with self.store.connection() as conn:\n            rows = conn.execute(sql, params).fetchall()\n            return [self._row_to_maintenance_run(row) for row in rows]\n\n    def _memory_subtype(self, metadata: dict[str, Any]) -> str | None:\n        record_kind = metadata.get(\"record_kind\") or metadata.get(\"legacy_kind\") or metadata.get(\"subtype\")\n        mapping = {\n            \"research_run\": \"research_run\",\n            \"research_step\": \"research_step\",\n            \"source\": \"research_source\",\n            \"research_source\": \"research_source\",\n            \"claim\": \"research_claim\",\n            \"research_claim\": \"research_claim\",\n            \"artifact\": \"research_artifact\",\n            \"research_artifact\": \"research_artifact\",\n            \"leisure_item\": \"leisure_item\",\n            \"router_handoff\": \"router_handoff\",\n        }\n        return mapping.get(record_kind, record_kind)\n\n    def _infer_run_id(self, row: dict[str, Any], subtype: str | None) -> str | None:\n        source_ref = row.get(\"source_ref\") or \"\"\n        if source_ref.startswith(\"personal-agent:run:\"):\n            return source_ref.rsplit(\":\", 1)[-1]\n        if subtype == \"research_run\":\n            return row[\"id\"]\n        return None\n\n    def _infer_url(self, row: dict[str, Any], subtype: str | None) -> str | None:\n        if subtype in {\"research_source\", \"research_claim\", \"research_artifact\"}:\n            evidence_ref = row.get(\"evidence_ref\")\n            if isinstance(evidence_ref, str) and evidence_ref.startswith((\"http://\", \"https://\")):\n                return evidence_ref\n        return None\n\n    def _upsert_fts(self, conn: Any, record: dict[str, Any]) -> None:\n        conn.execute(\"DELETE FROM memories_fts WHERE memory_id = ?\", (record[\"id\"],))\n        conn.execute(\n            \"INSERT INTO memories_fts (memory_id, title, summary, content) VALUES (?, ?, ?, ?)\",\n            (record[\"id\"], record[\"title\"], record[\"summary\"], record[\"content\"]),\n        )\n\n    def _row_to_memory(self, row: Any) -> dict[str, Any]:\n        memory = dict(row)\n        memory[\"metadata\"] = self.store.loads(memory.pop(\"metadata_json\")) or {}\n        memory[\"embedding\"] = self._decode_embedding(memory.pop(\"embedding_json\"))\n        return memory\n\n    def _row_to_task(self, row: Any) -> dict[str, Any]:\n        task = dict(row)\n        task[\"metadata\"] = self.store.loads(task.pop(\"metadata_json\")) or {}\n        task[\"requires_human_input\"] = bool(task[\"requires_human_input\"])\n        return task\n\n    def _row_to_task_run(self, row: Any) -> dict[str, Any]:\n        run = dict(row)\n        run[\"input_payload\"] = self.store.loads(run.pop(\"input_payload_json\")) or {}\n        run[\"metadata\"] = self.store.loads(run.pop(\"metadata_json\")) or {}\n        return run\n\n    def _row_to_artifact(self, row: Any) -> dict[str, Any]:\n        artifact = dict(row)\n        artifact[\"metadata\"] = self.store.loads(artifact.pop(\"metadata_json\")) or {}\n        return artifact\n\n    def _row_to_maintenance_job(self, row: Any) -> dict[str, Any]:\n        job = dict(row)\n        job[\"metadata\"] = self.store.loads(job.pop(\"metadata_json\")) or {}\n        job[\"enabled\"] = bool(job[\"enabled\"])\n        return job\n\n    def _row_to_maintenance_run(self, row: Any) -> dict[str, Any]:\n        run = dict(row)\n        run[\"stats\"] = self.store.loads(run.pop(\"stats_json\")) or {}\n        return run\n\n    def _make_summary(self, content: str, max_len: int = 180) -> str:\n        compact = \" \".join(content.split())\n        return compact[: max_len - 1] + \"…\" if len(compact) > max_len else compact\n\n    def _encode_embedding(self, embedding: list[float] | None) -> str | None:\n        if embedding is None:\n            return None\n        return json.dumps(embedding)\n\n\n[127 more lines in file. Use offset=1580 to continue.]"}],"isError":false,"timestamp":1776636248892}}
{"type":"message","id":"62f12576","parentId":"660104e5","timestamp":"2026-04-19T22:04:13.997Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Z6UREPAfKIxPRNuUuBwvu351|fc_071e452a5a0ea02e0169e5515a11208190ab3e24541340dc9d","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json, traceback\nfrom pathlib import Path\nimport sys\nsys.path.insert(0, '/mnt/rpi/agents-database/src')\nfrom shared_agent_memory.service import MemoryService\n\np='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\ntry:\n    svc=MemoryService(p)\n    print('service_init_ok')\n    rec=svc.create_memory({\n      'type':'episode','scope':'global','title':'repair test memory 2','content':'post-rebuild direct service write test','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'\n    })\n    print(json.dumps(rec, indent=2))\nexcept Exception as e:\n    print('ERR', repr(e))\n    traceback.print_exc()\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1387,"output":212,"cacheRead":40192,"cacheWrite":0,"totalTokens":41791,"cost":{"input":0.0034675,"output":0.00318,"cacheRead":0.010048,"cacheWrite":0,"total":0.016695500000000002}},"stopReason":"toolUse","timestamp":1776636248907,"responseId":"resp_071e452a5a0ea02e0169e551592f308190863e9b40a912d98c"}}
{"type":"message","id":"462df25a","parentId":"62f12576","timestamp":"2026-04-19T22:04:15.040Z","message":{"role":"toolResult","toolCallId":"call_Z6UREPAfKIxPRNuUuBwvu351|fc_071e452a5a0ea02e0169e5515a11208190ab3e24541340dc9d","toolName":"bash","content":[{"type":"text","text":"service_init_ok\n{\n  \"id\": \"mem_439c4a878d4643f289354ad85c607af5\",\n  \"schema_version\": \"shared-agent-memory-v2\",\n  \"type\": \"episode\",\n  \"subtype\": null,\n  \"scope\": \"global\",\n  \"status\": \"active\",\n  \"project_id\": null,\n  \"repo_id\": null,\n  \"agent_id\": null,\n  \"origin_agent\": \"personal-agent\",\n  \"run_id\": null,\n  \"task_id\": null,\n  \"url\": null,\n  \"domain\": null,\n  \"source_kind\": \"manual\",\n  \"title\": \"repair test memory 2\",\n  \"content\": \"post-rebuild direct service write test\",\n  \"summary\": \"post-rebuild direct service write test\",\n  \"confidence\": 1.0,\n  \"freshness\": 1.0,\n  \"created_at\": \"2026-04-19T22:04:14.941832+00:00\",\n  \"updated_at\": \"2026-04-19T22:04:14.941832+00:00\",\n  \"observed_at\": \"2026-04-19T22:04:14.941832+00:00\",\n  \"source_ref\": \"conversation:2026-04-19\",\n  \"evidence_ref\": null,\n  \"metadata\": {},\n  \"embedding\": null\n}\n"}],"isError":false,"timestamp":1776636255040}}
{"type":"message","id":"b583a3a1","parentId":"462df25a","timestamp":"2026-04-19T22:04:22.336Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_wC9PqdsD4tS0saEmdtHR4Yu3|fc_071e452a5a0ea02e0169e55164b3b08190a251d1f23154b983","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","offset":160,"limit":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":506,"output":39,"cacheRead":41600,"cacheWrite":0,"totalTokens":42145,"cost":{"input":0.001265,"output":0.000585,"cacheRead":0.0104,"cacheWrite":0,"total":0.01225}},"stopReason":"toolUse","timestamp":1776636255042,"responseId":"resp_071e452a5a0ea02e0169e5515ff7708190ae13a324740a2320"}}
{"type":"message","id":"369c7887","parentId":"b583a3a1","timestamp":"2026-04-19T22:04:22.359Z","message":{"role":"toolResult","toolCallId":"call_wC9PqdsD4tS0saEmdtHR4Yu3|fc_071e452a5a0ea02e0169e55164b3b08190a251d1f23154b983","toolName":"read","content":[{"type":"text","text":"                    self._send_json(service.get_task(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path == \"/api/task-runs\":\n                    self._send_json(\n                        {\n                            \"items\": service.list_task_runs(\n                                task_id=_first(query, \"task_id\"),\n                                status=_first(query, \"status\"),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/task-runs/\"):\n                    self._send_json(service.get_task_run(parsed.path.split(\"/\")[3]))\n                    return\n                if parsed.path == \"/api/artifacts\":\n                    self._send_json(\n                        {\n                            \"items\": service.list_artifacts(\n                                task_id=_first(query, \"task_id\"),\n                                limit=_first_int(query, \"limit\", 50),\n                            )\n                        }\n                    )\n                    return\n                if parsed.path.startswith(\"/api/artifacts/\"):\n                    self._send_json(service.get_artifact(parsed.path.split(\"/\")[3]))\n                    return\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n\n        def do_POST(self) -> None:  # noqa: N802\n            parsed = urlparse(self.path)\n            try:\n                payload = self._json_body()\n            except (UnicodeDecodeError, json.JSONDecodeError, ValueError):\n                self.send_error(HTTPStatus.BAD_REQUEST, \"Invalid JSON body\")\n                return\n\n            try:\n                if parsed.path == \"/api/ingest\":\n                    self._send_json(service.ingest(payload), status=HTTPStatus.CREATED)\n                    return\n                if parsed.path == \"/api/tasks\":\n                    self._send_json(\n                        service.create_task(\n                            title=payload[\"title\"],\n                            intent=payload[\"intent\"],\n                            kind=payload.get(\"kind\", \"task\"),\n                            status=payload.get(\"status\", \"open\"),\n                            priority=payload.get(\"priority\", 3),\n                            project_id=payload.get(\"project_id\"),\n                            repo_id=payload.get(\"repo_id\"),\n                            parent_task_id=payload.get(\"parent_task_id\"),\n                            origin=payload.get(\"origin\"),\n                            owner_agent=payload.get(\"owner_agent\"),\n                            blocked_reason=payload.get(\"blocked_reason\"),\n                            requires_human_input=bool(payload.get(\"requires_human_input\", False)),\n                            due_at=payload.get(\"due_at\"),\n                            metadata=payload.get(\"metadata\"),\n                            task_id=payload.get(\"task_id\"),\n                            run_id=payload.get(\"run_id\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n                if parsed.path == \"/api/task-runs\":\n                    task_id = payload.get(\"task_id\")\n                    agent_id = payload.get(\"agent_id\")\n                    if not isinstance(task_id, str) or not task_id.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'task_id'\")\n                        return\n                    if not isinstance(agent_id, str) or not agent_id.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'agent_id'\")\n                        return\n                    self._send_json(\n                        service.start_task_run(\n                            task_id,\n                            agent_id,\n                            input_payload=payload.get(\"input_payload\"),\n                            metadata=payload.get(\"metadata\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n                if parsed.path.startswith(\"/api/task-runs/\") and parsed.path.endswith(\"/finish\"):\n                    run_id = parsed.path.split(\"/\")[3]\n                    status = payload.get(\"status\")\n                    if not isinstance(status, str) or not status.strip():\n                        self.send_error(HTTPStatus.BAD_REQUEST, \"Missing or invalid 'status'\")\n                        return\n                    self._send_json(\n                        service.finish_task_run(\n                            run_id,\n                            status=status,\n                            result_summary=payload.get(\"result_summary\"),\n                            error_message=payload.get(\"error_message\"),\n                        )\n                    )\n                    return\n                if parsed.path == \"/api/artifacts\":\n                    task_id = payload.get(\"task_id\")\n                    artifact_type = payload.get(\"artifact_type\")\n                    title = payload.get(\"title\")\n                    content = payload.get(\"content\")\n                    if not all(isinstance(value, str) and value.strip() for value in (task_id, artifact_type, title, content)):\n                        self.send_error(\n                            HTTPStatus.BAD_REQUEST,\n                            \"Missing or invalid required artifact fields\",\n                        )\n                        return\n                    self._send_json(\n                        service.create_artifact(\n\n[77 more lines in file. Use offset=280 to continue.]"}],"isError":false,"timestamp":1776636262352}}
{"type":"message","id":"a05bc419","parentId":"369c7887","timestamp":"2026-04-19T22:04:24.709Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_al3dMjxANfFx8AmYm7F8H09A|fc_071e452a5a0ea02e0169e55167dd108190bab71c966acc9da8","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","offset":280,"limit":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1131,"output":39,"cacheRead":41984,"cacheWrite":0,"totalTokens":43154,"cost":{"input":0.0028275,"output":0.000585,"cacheRead":0.010496,"cacheWrite":0,"total":0.0139085}},"stopReason":"toolUse","timestamp":1776636262361,"responseId":"resp_071e452a5a0ea02e0169e55166c04c8190a7585d031f1d8b08"}}
{"type":"message","id":"b51bfbd4","parentId":"a05bc419","timestamp":"2026-04-19T22:04:24.720Z","message":{"role":"toolResult","toolCallId":"call_al3dMjxANfFx8AmYm7F8H09A|fc_071e452a5a0ea02e0169e55167dd108190bab71c966acc9da8","toolName":"read","content":[{"type":"text","text":"                            task_id=task_id,\n                            artifact_type=artifact_type,\n                            title=title,\n                            content=content,\n                            metadata=payload.get(\"metadata\"),\n                            source_ref=payload.get(\"source_ref\"),\n                        ),\n                        status=HTTPStatus.CREATED,\n                    )\n                    return\n            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n\n        def do_PATCH(self) -> None:  # noqa: N802\n            parsed = urlparse(self.path)\n            if not parsed.path.startswith(\"/api/tasks/\"):\n                self.send_error(HTTPStatus.NOT_FOUND)\n                return\n            try:\n                payload = self._json_body()\n            except (UnicodeDecodeError, json.JSONDecodeError, ValueError):\n                self.send_error(HTTPStatus.BAD_REQUEST, \"Invalid JSON body\")\n                return\n            try:\n                self._send_json(\n                    service.update_task(\n                        parsed.path.split(\"/\")[3],\n                        status=payload.get(\"status\"),\n                        owner_agent=payload.get(\"owner_agent\"),\n                        blocked_reason=payload.get(\"blocked_reason\"),\n                        requires_human_input=payload.get(\"requires_human_input\"),\n                        metadata=payload.get(\"metadata\"),\n                        run_id=payload.get(\"run_id\"),\n                    )\n                )\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n\n        def log_message(self, fmt: str, *args: Any) -> None:\n            return\n\n        def _json_body(self) -> dict[str, Any]:\n            length = int(self.headers.get(\"Content-Length\", \"0\"))\n            raw = self.rfile.read(length) if length else b\"{}\"\n            payload = json.loads(raw.decode(\"utf-8\"))\n            if not isinstance(payload, dict):\n                raise ValueError(\"JSON body must be an object\")\n            return payload\n\n        def _send_common_headers(self, *, content_type: str, content_length: int) -> None:\n            self.send_header(\"Content-Type\", content_type)\n            self.send_header(\"Content-Length\", str(content_length))\n            self.send_header(\"Access-Control-Allow-Origin\", \"*\")\n            self.send_header(\"Access-Control-Allow-Headers\", \"Content-Type\")\n            self.send_header(\"Access-Control-Allow-Methods\", \"GET,POST,PATCH,OPTIONS\")\n\n        def _send_json(self, payload: dict[str, Any], *, status: HTTPStatus = HTTPStatus.OK) -> None:\n            body = json.dumps(payload, ensure_ascii=True).encode(\"utf-8\")\n            self.send_response(status)\n            self._send_common_headers(content_type=\"application/json; charset=utf-8\", content_length=len(body))\n            self.end_headers()\n            self.wfile.write(body)\n\n    return MemoryAPIHandler\n\n\ndef run_http_server(*, db_path: str, host: str = \"127.0.0.1\", port: int = 8091) -> None:\n    service = MemoryService(db_path)\n    server = ThreadingHTTPServer((host, port), build_handler(service))\n    try:\n        server.serve_forever()\n    finally:\n        server.server_close()\n"}],"isError":false,"timestamp":1776636264712}}
{"type":"message","id":"1456369e","parentId":"b51bfbd4","timestamp":"2026-04-19T22:04:32.337Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_2TY02jFDtzuYwpPyDik8CCWG|fc_071e452a5a0ea02e0169e55169efa08190ba098da50066a942","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","edits":[{"oldText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n","newText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n                return\n"},{"oldText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n","newText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n                return\n"},{"oldText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n","newText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":806,"output":349,"cacheRead":43008,"cacheWrite":0,"totalTokens":44163,"cost":{"input":0.0020150000000000003,"output":0.005235,"cacheRead":0.010752,"cacheWrite":0,"total":0.018002}},"stopReason":"toolUse","timestamp":1776636264723,"responseId":"resp_071e452a5a0ea02e0169e5516914b0819096ade06ccdff6de9"}}
{"type":"message","id":"a583af89","parentId":"1456369e","timestamp":"2026-04-19T22:04:32.364Z","message":{"role":"toolResult","toolCallId":"call_2TY02jFDtzuYwpPyDik8CCWG|fc_071e452a5a0ea02e0169e55169efa08190ba098da50066a942","toolName":"edit","content":[{"type":"text","text":"Found 2 occurrences of edits[2] in /mnt/rpi/agents-database/src/shared_agent_memory/http_api.py. Each oldText must be unique. Please provide more context to make it unique."}],"details":{},"isError":true,"timestamp":1776636272364}}
{"type":"message","id":"fca57b28","parentId":"a583af89","timestamp":"2026-04-19T22:04:47.252Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_ExB5sJPrcCT5nS8W1jPK7dOI|fc_071e452a5a0ea02e0169e55172482c81908cb38592b44bad1d","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/http_api.py","edits":[{"oldText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n","newText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n                return\n            except ValueError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n                return\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n                return\n"},{"oldText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n","newText":"            except KeyError as exc:\n                self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n                return\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n                return\n\n            self.send_error(HTTPStatus.NOT_FOUND)\n"},{"oldText":"            try:\n                self._send_json(\n                    service.update_task(\n                        parsed.path.split(\"/\")[3],\n                        status=payload.get(\"status\"),\n                        owner_agent=payload.get(\"owner_agent\"),\n                        blocked_reason=payload.get(\"blocked_reason\"),\n                        requires_human_input=payload.get(\"requires_human_input\"),\n                        metadata=payload.get(\"metadata\"),\n                        run_id=payload.get(\"run_id\"),\n                    )\n                )\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n","newText":"            try:\n                self._send_json(\n                    service.update_task(\n                        parsed.path.split(\"/\")[3],\n                        status=payload.get(\"status\"),\n                        owner_agent=payload.get(\"owner_agent\"),\n                        blocked_reason=payload.get(\"blocked_reason\"),\n                        requires_human_input=payload.get(\"requires_human_input\"),\n                        metadata=payload.get(\"metadata\"),\n                        run_id=payload.get(\"run_id\"),\n                    )\n                )\n            except KeyError as exc:\n                self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n            except Exception as exc:\n                self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":183,"output":601,"cacheRead":44032,"cacheWrite":0,"totalTokens":44816,"cost":{"input":0.00045750000000000006,"output":0.009015,"cacheRead":0.011007999999999999,"cacheWrite":0,"total":0.0204805}},"stopReason":"toolUse","timestamp":1776636272366,"responseId":"resp_071e452a5a0ea02e0169e55170adc08190b779d9650c4fb47a"}}
{"type":"message","id":"543b2034","parentId":"fca57b28","timestamp":"2026-04-19T22:04:47.270Z","message":{"role":"toolResult","toolCallId":"call_ExB5sJPrcCT5nS8W1jPK7dOI|fc_071e452a5a0ea02e0169e55172482c81908cb38592b44bad1d","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 3 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/http_api.py."}],"details":{"diff":"     ...\n 191                 return\n 192             except ValueError as exc:\n 193                 self.send_error(HTTPStatus.BAD_REQUEST, str(exc))\n 194                 return\n+195             except Exception as exc:\n+196                 self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n+197                 return\n 195 \n 196             self.send_error(HTTPStatus.NOT_FOUND)\n 197 \n 198         def do_POST(self) -> None:  # noqa: N802\n     ...\n 289                     return\n 290             except KeyError as exc:\n 291                 self.send_error(HTTPStatus.BAD_REQUEST, f\"Missing field: {exc}\")\n 292                 return\n+296             except Exception as exc:\n+297                 self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n+298                 return\n 293 \n 294             self.send_error(HTTPStatus.NOT_FOUND)\n 295 \n 296         def do_PATCH(self) -> None:  # noqa: N802\n     ...\n 316                     )\n 317                 )\n 318             except KeyError as exc:\n 319                 self.send_error(HTTPStatus.NOT_FOUND, str(exc))\n+326             except Exception as exc:\n+327                 self.send_error(HTTPStatus.INTERNAL_SERVER_ERROR, str(exc))\n 320 \n 321         def log_message(self, fmt: str, *args: Any) -> None:\n 322             return\n 323 \n     ...","firstChangedLine":195},"isError":false,"timestamp":1776636287270}}
{"type":"message","id":"59b19039","parentId":"543b2034","timestamp":"2026-04-19T22:04:53.167Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_wUDe2Y50EeMG0BmP1F7WgEEh|fc_071e452a5a0ea02e0169e55181460c81909662a07d72eebd8a","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user restart agents-database-http.service\nsleep 2\npython3 - <<'PY'\nimport json, urllib.request, urllib.error\npayload={\n  'type':'episode','scope':'global','title':'repair test memory 3','content':'post-rebuild http write test','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'\n}\nreq=urllib.request.Request('http://127.0.0.1:8091/api/ingest', data=json.dumps(payload).encode(), headers={'Content-Type':'application/json'}, method='POST')\ntry:\n    with urllib.request.urlopen(req, timeout=20) as r:\n        print('status', r.status)\n        print(r.read().decode())\nexcept urllib.error.HTTPError as e:\n    print('http_error', e.code)\n    print(e.read().decode())\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":178,"output":221,"cacheRead":44672,"cacheWrite":0,"totalTokens":45071,"cost":{"input":0.00044500000000000003,"output":0.0033150000000000002,"cacheRead":0.011167999999999999,"cacheWrite":0,"total":0.014928}},"stopReason":"toolUse","timestamp":1776636287272,"responseId":"resp_071e452a5a0ea02e0169e5517fc18481909a7051312556392f"}}
{"type":"message","id":"ab030fb1","parentId":"59b19039","timestamp":"2026-04-19T22:04:55.279Z","message":{"role":"toolResult","toolCallId":"call_wUDe2Y50EeMG0BmP1F7WgEEh|fc_071e452a5a0ea02e0169e55181460c81909662a07d72eebd8a","toolName":"bash","content":[{"type":"text","text":"http_error 500\n<!DOCTYPE HTML>\n<html lang=\"en\">\n    <head>\n        <meta charset=\"utf-8\">\n        <title>Error response</title>\n    </head>\n    <body>\n        <h1>Error response</h1>\n        <p>Error code: 500</p>\n        <p>Message: 'StatusOnlyService' object has no attribute 'ingest'.</p>\n        <p>Error code explanation: 500 - Server got itself in trouble.</p>\n    </body>\n</html>\n\n"}],"isError":false,"timestamp":1776636295279}}
{"type":"message","id":"ce245cf0","parentId":"ab030fb1","timestamp":"2026-04-19T22:04:58.026Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_sCmMrxmJWtlr5hFmVXIYueLJ|fc_071e452a5a0ea02e0169e551891b148190874a581b13729c43","name":"read","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","offset":130,"limit":80}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":265,"output":39,"cacheRead":44928,"cacheWrite":0,"totalTokens":45232,"cost":{"input":0.0006625,"output":0.000585,"cacheRead":0.011231999999999999,"cacheWrite":0,"total":0.0124795}},"stopReason":"toolUse","timestamp":1776636295281,"responseId":"resp_071e452a5a0ea02e0169e55187e6448190aa4e592ddb2ce715"}}
{"type":"message","id":"7e7ce863","parentId":"ce245cf0","timestamp":"2026-04-19T22:04:58.040Z","message":{"role":"toolResult","toolCallId":"call_sCmMrxmJWtlr5hFmVXIYueLJ|fc_071e452a5a0ea02e0169e551891b148190874a581b13729c43","toolName":"read","content":[{"type":"text","text":"\n    return parser\n\n\ndef main() -> None:\n    parser = build_parser()\n    args = parser.parse_args()\n\n    if args.command == \"serve-http\":\n        from .store import SQLiteStore\n        from .service import SCHEMA_VERSION\n\n        class StatusOnlyService:\n            def __init__(self, db_path: str) -> None:\n                self.store = SQLiteStore(db_path)\n                self.store.initialize()\n\n            def dashboard_snapshot(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                        \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n                        \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n                        \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n                    }\n\n            def audit_v2(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"schema_version\": SCHEMA_VERSION,\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                    }\n\n        service = StatusOnlyService(args.db)\n        from .http_api import build_handler\n        from http.server import ThreadingHTTPServer\n\n        server = ThreadingHTTPServer((args.host, args.port), build_handler(service))\n        try:\n            server.serve_forever()\n        finally:\n            server.server_close()\n        return\n\n    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n\n    if args.command == \"init-db\":\n        print(json.dumps({\"db\": str(Path(args.db).resolve()), \"status\": \"initialized\"}, indent=2))\n    elif args.command == \"create-project\":\n        service.create_project(args.project_id, args.name, args.description)\n        print(json.dumps({\"project_id\": args.project_id}, indent=2))\n    elif args.command == \"create-repo\":\n        service.create_repo(args.repo_id, args.name, args.project_id, args.path)\n        print(json.dumps({\"repo_id\": args.repo_id}, indent=2))\n    elif args.command == \"upsert-profile-fact\":\n        print(\n            json.dumps(\n                service.upsert_profile_fact(args.title, args.content, args.evidence_ref, args.source_ref),\n                indent=2,\n            )\n        )\n    elif args.command == \"ingest\":\n        print(json.dumps(service.ingest(json.loads(args.payload_json)), indent=2))\n    elif args.command == \"capture-conversation\":\n        print(\n            json.dumps(\n                service.capture_conversation(args.source_ref, args.scope, args.content, capture_mode=args.capture_mode),\n                indent=2,\n            )\n        )\n    elif args.command == \"capture-session\":\n        print(json.dumps(service.capture_session(args.source_ref, args.scope, args.content), indent=2))\n    elif args.command == \"process-pending\":\n        print(json.dumps(engine.process_pending(args.limit), indent=2))\n    elif args.command == \"maintenance-tick\":\n        print(json.dumps(engine.run_due_maintenance(limit=args.limit, job_id=args.job_id), indent=2))\n    elif args.command == \"maintenance-status\":\n\n[117 more lines in file. Use offset=210 to continue.]"}],"isError":false,"timestamp":1776636298034}}
{"type":"message","id":"4dcdc694","parentId":"7e7ce863","timestamp":"2026-04-19T22:05:07.423Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_l4ECxAxuvMAGE6vhgjruzdvj|fc_071e452a5a0ea02e0169e5518b6a9c81908d4b6e672f309cb0","name":"edit","arguments":{"path":"/mnt/rpi/agents-database/src/shared_agent_memory/cli.py","edits":[{"oldText":"    if args.command == \"serve-http\":\n        from .store import SQLiteStore\n        from .service import SCHEMA_VERSION\n\n        class StatusOnlyService:\n            def __init__(self, db_path: str) -> None:\n                self.store = SQLiteStore(db_path)\n                self.store.initialize()\n\n            def dashboard_snapshot(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                        \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n                        \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n                        \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n                    }\n\n            def audit_v2(self):\n                with self.store.connection() as conn:\n                    return {\n                        \"schema_version\": SCHEMA_VERSION,\n                        \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n                        \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n                    }\n\n        service = StatusOnlyService(args.db)\n        from .http_api import build_handler\n        from http.server import ThreadingHTTPServer\n\n        server = ThreadingHTTPServer((args.host, args.port), build_handler(service))\n        try:\n            server.serve_forever()\n        finally:\n            server.server_close()\n        return\n\n    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n","newText":"    service = MemoryService(args.db)\n    engine = MemoryEngine(service)\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":880,"output":436,"cacheRead":45056,"cacheWrite":0,"totalTokens":46372,"cost":{"input":0.0022,"output":0.00654,"cacheRead":0.011264,"cacheWrite":0,"total":0.020004}},"stopReason":"toolUse","timestamp":1776636298041,"responseId":"resp_071e452a5a0ea02e0169e5518a7860819082ff96dea055bda0"}}
{"type":"message","id":"0ebbde07","parentId":"4dcdc694","timestamp":"2026-04-19T22:05:07.430Z","message":{"role":"toolResult","toolCallId":"call_l4ECxAxuvMAGE6vhgjruzdvj|fc_071e452a5a0ea02e0169e5518b6a9c81908d4b6e672f309cb0","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /mnt/rpi/agents-database/src/shared_agent_memory/cli.py."}],"details":{"diff":"     ...\n 134 def main() -> None:\n 135     parser = build_parser()\n 136     args = parser.parse_args()\n 137 \n-138     if args.command == \"serve-http\":\n-139         from .store import SQLiteStore\n-140         from .service import SCHEMA_VERSION\n-141 \n-142         class StatusOnlyService:\n-143             def __init__(self, db_path: str) -> None:\n-144                 self.store = SQLiteStore(db_path)\n-145                 self.store.initialize()\n-146 \n-147             def dashboard_snapshot(self):\n-148                 with self.store.connection() as conn:\n-149                     return {\n-150                         \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n-151                         \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n-152                         \"artifacts\": conn.execute(\"SELECT COUNT(*) FROM artifacts\").fetchone()[0],\n-153                         \"projects\": conn.execute(\"SELECT COUNT(*) FROM projects\").fetchone()[0],\n-154                         \"repos\": conn.execute(\"SELECT COUNT(*) FROM repos\").fetchone()[0],\n-155                     }\n-156 \n-157             def audit_v2(self):\n-158                 with self.store.connection() as conn:\n-159                     return {\n-160                         \"schema_version\": SCHEMA_VERSION,\n-161                         \"memories\": conn.execute(\"SELECT COUNT(*) FROM memories\").fetchone()[0],\n-162                         \"tasks\": conn.execute(\"SELECT COUNT(*) FROM tasks\").fetchone()[0],\n-163                     }\n-164 \n-165         service = StatusOnlyService(args.db)\n-166         from .http_api import build_handler\n-167         from http.server import ThreadingHTTPServer\n-168 \n-169         server = ThreadingHTTPServer((args.host, args.port), build_handler(service))\n-170         try:\n-171             server.serve_forever()\n-172         finally:\n-173             server.server_close()\n-174         return\n-175 \n 176     service = MemoryService(args.db)\n 177     engine = MemoryEngine(service)\n 178 \n 179     if args.command == \"init-db\":\n     ...","firstChangedLine":138},"isError":false,"timestamp":1776636307429}}
{"type":"message","id":"7658a5c1","parentId":"0ebbde07","timestamp":"2026-04-19T22:05:15.847Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_os4zNaUTaG4Hxpk2FbRfV5LJ|fc_071e452a5a0ea02e0169e55196f5f08190a87d37c1d58107ac","name":"bash","arguments":{"command":"set -euo pipefail\ncd /mnt/rpi/agents-database\nPYTHONPATH=src python3 -m py_compile src/shared_agent_memory/cli.py src/shared_agent_memory/http_api.py src/shared_agent_memory/service.py\nsystemctl --user restart agents-database-http.service\nsleep 2\ncurl -sS -m 10 http://127.0.0.1:8091/api/status\nprintf '\\n--- ingest ---\\n'\npython3 - <<'PY'\nimport json, urllib.request, urllib.error\npayload={\n  'type':'episode','scope':'global','title':'repair test memory 4','content':'post-rebuild http write test ok','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'\n}\nreq=urllib.request.Request('http://127.0.0.1:8091/api/ingest', data=json.dumps(payload).encode(), headers={'Content-Type':'application/json'}, method='POST')\nwith urllib.request.urlopen(req, timeout=20) as r:\n    print('status', r.status)\n    print(r.read().decode())\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":198,"output":265,"cacheRead":46208,"cacheWrite":0,"totalTokens":46671,"cost":{"input":0.000495,"output":0.003975,"cacheRead":0.011552,"cacheWrite":0,"total":0.016022}},"stopReason":"toolUse","timestamp":1776636307431,"responseId":"resp_071e452a5a0ea02e0169e5519418e88190a7e2d526413ddfcd"}}
{"type":"message","id":"724c0424","parentId":"7658a5c1","timestamp":"2026-04-19T22:05:18.151Z","message":{"role":"toolResult","toolCallId":"call_os4zNaUTaG4Hxpk2FbRfV5LJ|fc_071e452a5a0ea02e0169e55196f5f08190a87d37c1d58107ac","toolName":"bash","content":[{"type":"text","text":"--- ingest ---\nstatus 201\n{\"id\": \"mem_19bd7a3500da47918e71fbc59cf356ce\", \"schema_version\": \"shared-agent-memory-v2\", \"type\": \"episode\", \"subtype\": null, \"scope\": \"global\", \"status\": \"active\", \"project_id\": null, \"repo_id\": null, \"agent_id\": null, \"origin_agent\": \"personal-agent\", \"run_id\": null, \"task_id\": null, \"url\": null, \"domain\": null, \"source_kind\": \"manual\", \"title\": \"repair test memory 4\", \"content\": \"post-rebuild http write test ok\", \"summary\": \"post-rebuild http write test ok\", \"confidence\": 1.0, \"freshness\": 1.0, \"created_at\": \"2026-04-19T22:05:18.051429+00:00\", \"updated_at\": \"2026-04-19T22:05:18.051429+00:00\", \"observed_at\": \"2026-04-19T22:05:18.051429+00:00\", \"source_ref\": \"conversation:2026-04-19\", \"evidence_ref\": null, \"metadata\": {}, \"embedding\": null}\n\n\n[Showing lines 2-5 of 5 (50.0KB limit). Full output: /tmp/pi-bash-4f6ee6d2604e299f.log]"}],"details":{"truncation":{"content":"--- ingest ---\nstatus 201\n{\"id\": \"mem_19bd7a3500da47918e71fbc59cf356ce\", \"schema_version\": \"shared-agent-memory-v2\", \"type\": \"episode\", \"subtype\": null, \"scope\": \"global\", \"status\": \"active\", \"project_id\": null, \"repo_id\": null, \"agent_id\": null, \"origin_agent\": \"personal-agent\", \"run_id\": null, \"task_id\": null, \"url\": null, \"domain\": null, \"source_kind\": \"manual\", \"title\": \"repair test memory 4\", \"content\": \"post-rebuild http write test ok\", \"summary\": \"post-rebuild http write test ok\", \"confidence\": 1.0, \"freshness\": 1.0, \"created_at\": \"2026-04-19T22:05:18.051429+00:00\", \"updated_at\": \"2026-04-19T22:05:18.051429+00:00\", \"observed_at\": \"2026-04-19T22:05:18.051429+00:00\", \"source_ref\": \"conversation:2026-04-19\", \"evidence_ref\": null, \"metadata\": {}, \"embedding\": null}\n","truncated":true,"truncatedBy":"bytes","totalLines":5,"totalBytes":97084,"outputLines":4,"outputBytes":779,"lastLinePartial":false,"firstLineExceedsLimit":false,"maxLines":2000,"maxBytes":51200},"fullOutputPath":"/tmp/pi-bash-4f6ee6d2604e299f.log"},"isError":false,"timestamp":1776636318151}}
{"type":"message","id":"d54990e1","parentId":"724c0424","timestamp":"2026-04-19T22:05:22.433Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_8cmU62eWgrRObYHS8XpaWzh1|fc_071e452a5a0ea02e0169e551a0365881909e5227e453abaa27","name":"bash","arguments":{"command":"set -euo pipefail\nmkdir -p /mnt/rpi/service-backups/systemd-disabled\nmv /etc/systemd/system/personal-agent.service /mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-$(date +%Y%m%d-%H%M%S)\nsystemctl daemon-reload\nsystemctl reset-failed personal-agent.service || true\nsystemctl status personal-agent.service --no-pager -n 20 || true","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":407,"output":116,"cacheRead":46592,"cacheWrite":0,"totalTokens":47115,"cost":{"input":0.0010175000000000002,"output":0.00174,"cacheRead":0.011647999999999999,"cacheWrite":0,"total":0.014405499999999998}},"stopReason":"toolUse","timestamp":1776636318154,"responseId":"resp_071e452a5a0ea02e0169e5519f21fc81909ec2e8b3070f8494"}}
{"type":"message","id":"15ee688d","parentId":"d54990e1","timestamp":"2026-04-19T22:05:22.452Z","message":{"role":"toolResult","toolCallId":"call_8cmU62eWgrRObYHS8XpaWzh1|fc_071e452a5a0ea02e0169e551a0365881909e5227e453abaa27","toolName":"bash","content":[{"type":"text","text":"mv: cannot remove '/etc/systemd/system/personal-agent.service': Permission denied\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776636322452}}
{"type":"message","id":"7ae83668","parentId":"15ee688d","timestamp":"2026-04-19T22:05:35.669Z","message":{"role":"assistant","content":[{"type":"text","text":"Done, mostly.\n\nWhat I completed\n\n1. Backed up SQLite first\n- Created:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3`\n\n2. Rebuilt the malformed DB into a clean file\n- New rebuilt DB:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.rebuild-20260419.sqlite3`\n- Replaced live DB with rebuilt copy:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3`\n\n3. Restored agents-database to normal HTTP behavior\n- Removed the degraded status-only workaround\n- Added safer HTTP error handling so bad endpoints return `500` instead of empty reply\n- Restarted service\n- Verified write path works again:\n  - `POST /api/ingest` returned `201`\n\nCurrent `agents-database` state\n- service up on `:8091`\n- `/api/status` works\n- `/api/ingest` works\n- DB `quick_check` on rebuilt DB: `ok`\n\nImportant caveat\n- Rebuild recovered most, not all, rows.\n- Before:\n  - memories: `320`\n  - retrieval_logs: `6901`\n- After rebuild:\n  - memories: `288` + new test writes\n  - retrieval_logs: `6848`\n- So some damaged rows were lost during rebuild. This is the tradeoff that got the service healthy again.\n\nRoot `personal-agent.service`\n- I confirmed the broken root unit is still the stale one in:\n  - `/etc/systemd/system/personal-agent.service`\n- I tried to remove/disable it properly, but file operations on `/etc/systemd/system` need elevated rights.\n- The healthy user unit is still serving `:8082`.\n\nBlocked item\n- I cannot finish cleanup of the root unit without privilege.\n\nYou should run:\n```bash\nsudo mkdir -p /mnt/rpi/service-backups/systemd-disabled\nsudo mv /etc/systemd/system/personal-agent.service /mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-$(date +%Y%m%d-%H%M%S)\nsudo systemctl daemon-reload\nsudo systemctl reset-failed personal-agent.service || true\nsystemctl status personal-agent.service --no-pager -n 20 || true\n```\n\nBusiness outcome\n- Shared memory service is working again for normal API use.\n- Personal agent remains available.\n- Only remaining cleanup is the stale root systemd unit.\n\nIf you want, next I can:\n- diff old vs rebuilt DB counts in more detail\n- save a repair summary into agents-database\n- inspect whether any key memory types were among the lost rows","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e551a3999c8190abae122cd32fd8ed\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":173,"output":566,"cacheRead":46976,"cacheWrite":0,"totalTokens":47715,"cost":{"input":0.00043250000000000005,"output":0.008490000000000001,"cacheRead":0.011744,"cacheWrite":0,"total":0.0206665}},"stopReason":"stop","timestamp":1776636322453,"responseId":"resp_071e452a5a0ea02e0169e551a2dd68819085a062b9659bb870"}}
{"type":"message","id":"9cc77b30","parentId":"7ae83668","timestamp":"2026-04-19T22:19:28.312Z","message":{"role":"user","content":[{"type":"text","text":"ran the command, confirm success?"}],"timestamp":1776637168280}}
{"type":"message","id":"a5098527","parentId":"9cc77b30","timestamp":"2026-04-19T22:19:33.472Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_PY3ZF7MhzW80mSMeCbpsqN2X|fc_071e452a5a0ea02e0169e554f530708190848d6fc5ff7d5949","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl status personal-agent.service --no-pager -n 20 || true\nsystemctl is-enabled personal-agent.service || true\nls -l /etc/systemd/system/personal-agent.service 2>/dev/null || true\nls -1t /mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-* 2>/dev/null | head -n 3","timeout":60}},{"type":"toolCall","id":"call_e8q7AJ0DsxqQuvNfWnhCA2Ad|fc_071e452a5a0ea02e0169e554f530808190bfc880ede754d83a","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user status personal-agent.service --no-pager -n 20 || true\ncurl -fsS -m 10 http://127.0.0.1:8082/api/status | sed -n '1,80p'","timeout":60}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":112,"output":197,"cacheRead":47616,"cacheWrite":0,"totalTokens":47925,"cost":{"input":0.00028000000000000003,"output":0.002955,"cacheRead":0.011904,"cacheWrite":0,"total":0.015139}},"stopReason":"toolUse","timestamp":1776637168328,"responseId":"resp_071e452a5a0ea02e0169e554f0b6f48190a6cba37bd2366137"}}
{"type":"message","id":"a288eab7","parentId":"a5098527","timestamp":"2026-04-19T22:19:33.569Z","message":{"role":"toolResult","toolCallId":"call_PY3ZF7MhzW80mSMeCbpsqN2X|fc_071e452a5a0ea02e0169e554f530708190848d6fc5ff7d5949","toolName":"bash","content":[{"type":"text","text":"Unit personal-agent.service could not be found.\nnot-found\n/mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-20260419-190522\n/mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-20260419-191859\n"}],"isError":false,"timestamp":1776637173569}}
{"type":"message","id":"9a5632de","parentId":"a288eab7","timestamp":"2026-04-19T22:19:33.864Z","message":{"role":"toolResult","toolCallId":"call_e8q7AJ0DsxqQuvNfWnhCA2Ad|fc_071e452a5a0ea02e0169e554f530808190bfc880ede754d83a","toolName":"bash","content":[{"type":"text","text":"agos, bookings y clientes. [S2](#ref-s2)[S3](#ref-s3)[S8](#ref-s8)[S9](#ref-s9)[S10](#ref-s10)\\n- Operador multi-sede: administra multiples venues y managers desde el mismo manager; sincroniza operaciones con sistemas externos. [S2](#ref-s2)[S3](#ref-s3)\\n- Clubes de raqueta con sistema propio: mantienen MATCHi/Matchpoint/KNLTB/etc. como system of record de courts y usan Matchable como capa comercial/academy automation. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16) Abajo se detalla c\\u00f3mo Ballbox podr\\u00eda implementar una integraci\\u00f3n similar con ATC para el mercado LATAM. [\\u2192 Ballbox \\u00d7 ATC](#ballbox-atc-spec-de-integraci-n)\\n\\n## Superficies clave\\n\\n- Discovery marketplace: `explore`, `activities`, perfiles de trainer/venue. [S1](#ref-s1)[S6](#ref-s6)\\n- Booking flow: seleccion de servicio, attendees, duracion, package, planning, login/signup, pago. [S6](#ref-s6)\\n- Storefront: home publica de cada negocio con toda la oferta activa. [S10](#ref-s10)\\n- Manager: schedule, bookings, trainers, clients, services, promotions, settings, payment method. [S8](#ref-s8)[S9](#ref-s9)[S11](#ref-s11)\\n- Trainer App: home, weekly schedule, create training, availability, holidays, profile. [S11](#ref-s11)\\n- Client App: discovery, booked sessions, services, locations, booking/pago. [S7](#ref-s7)[S17](#ref-s17)\\n- Integrations hub: calendars, video, courts, nutrition, tournaments. [S4](#ref-s4)[S12](#ref-s12)[S13](#ref-s13)[S14](#ref-s14)[S15](#ref-s15)[S16](#ref-s16)\\n\\n## Mapa exhaustivo de features\\n\\n### 1. Discovery / marketplace cliente\\n\\n**Features confirmadas**\\n- Buscar trainer, venue o deporte desde la web/app. [S1](#ref-s1)[S6](#ref-s6)[S17](#ref-s17)\\n- Navegar categorias/top categories y distintos deportes; homepage cita fitness, yoga, padel y \\\"everything in between\\\"; app stores mencionan padel, tennis, yoga, fitness y boxing. [S1](#ref-s1)[S17](#ref-s17)[S18](#ref-s18)\\n- Ver perfiles publicos de trainer con idiomas, ubicacion, reviews y servicios. [S1](#ref-s1)[S19](#ref-s19)\\n- Ver venue/storefront con nombre, descripcion, fotos, ubicacion, reviews y toda la oferta activa. [S10](#ref-s10)\\n- Filtrar/ordenar oferta desde storefront/app; release notes del client app documentan nuevos filtros y organized overview. [S17](#ref-s17)\\n\\n**Use cases soportados**\\n- Encontrar entrenador o actividad cercana/adecuada sin depender del sitio propio de cada club.\\n- Comparar private sessions, classes, courses y events en una sola experiencia.\\n- Descubrir negocios via marketplace y luego convertir por link directo/storefront.\\n\\n**Justificacion**\\n- Directa por homepage, client app copy, help de booking y help de storefront. [S1](#ref-s1)[S6](#ref-s6)[S10](#ref-s10)[S17](#ref-s17)\\n\\n### 2. Profiles / trust layer\\n\\n**Features confirmadas**\\n- Trainer profile con foto, banner, bio, specializations, languages, contact details y socials. [S8](#ref-s8)[S11](#ref-s11)[S19](#ref-s19)\\n- Venue profile con logo, banner, bio, location, contact info, socials y amenities. [S8](#ref-s8)\\n- Reviews en trainer/storefront; FAQ dice que el usuario recibe email post-sesion para dejar review. [S1](#ref-s1)[S7](#ref-s7)[S10](#ref-s10)[S19](#ref-s19)\\n- Visibility toggles para marketplace y venue page. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Elegir coach por fit, idioma, especialidad o reputacion.\\n- Mejorar conversion del negocio con trust signals y contenido visual.\\n- Ocultar o publicar trainers/servicios segun estrategia comercial.\\n\\n### 3. Booking / checkout core\\n\\n**Features confirmadas**\\n- Elegir tipo de training (ej. group lesson vs private 1-to-1). [S6](#ref-s6)\\n- Elegir numero de attendees. [S6](#ref-s6)\\n- Elegir duracion. [S6](#ref-s6)\\n- Elegir package / bundle con descuento por multiples clases. [S6](#ref-s6)\\n- Aplicar discount o voucher code. [S6](#ref-s6)\\n- Planear la sesion en checkout o dejarla unplanned para despues. [S5](#ref-s5)[S6](#ref-s6)\\n- Crear cuenta/log in y pagar online. [S6](#ref-s6)\\n- Sin fee de plataforma para cliente segun copy publica. [S1](#ref-s1)[S3](#ref-s3)[S7](#ref-s7)[S17](#ref-s17)\\n\\n**Use cases soportados**\\n- Reservar un 1:1, una small group session o una compra futura de varias sesiones.\\n- Comprar ahora y coordinar agenda despues.\\n- Ejecutar campa\\u00f1as con vouchers/codigos.\\n\\n### 4. Session planning / post-booking lifecycle\\n\\n**Features confirmadas**\\n- Trainings pueden quedar unplanned y luego programarse desde la cuenta del cliente. [S5](#ref-s5)\\n- Reagendar o cancelar desde el perfil, sujeto a cancellation policy del provider. [S5](#ref-s5)[S7](#ref-s7)\\n- Cambiar trainer en ciertos flujos de reschedule. [S5](#ref-s5)\\n- Booking statuses Planned / Unplanned. [S9](#ref-s9)\\n- Businesses pueden marcar bookings como Redeemed/completados. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Vender packs antes de definir agenda exacta.\\n- Reacomodar sesiones por clima, disponibilidad o lesion.\\n- Cerrar operativamente una sesion como consumida.\\n\\n### 5. Offer types / catalog model\\n\\n**A. Private training / private service**\\n- Crear private training con descripcion, VAT, cancellation policy, booking buffer y advance booking limit. [S8](#ref-s8)\\n- Definir pricing categories, capacidad, trainer asignado, duracion, precio por sesion y packages. [S8](#ref-s8)\\n- Publicar/ocultar servicio. [S8](#ref-s8)\\n- Marketplace y pricing lo posicionan como pilar central. [S2](#ref-s2)[S3](#ref-s3)\\n\\n**Use cases**\\n- Coach de tennis/padel/personal training que vende 1:1 o small group.\\n- Academia que diferencia peak/off-peak, duraciones y capacidad.\\n\\n**B. Classes**\\n- Clases recurrentes con set schedules y capacity limits. [S2](#ref-s2)\\n- Clientes compran spots individuales en group sessions. [S2](#ref-s2)\\n- Se muestran spots restantes en storefront. [S10](#ref-s10)\\n\\n**Use cases**\\n- Weekly yoga/fitness/padel clinics.\\n- Llenar horas valle con group sessions abiertas.\\n\\n**C. Events**\\n- Crear event page con banner, descripcion, tickets, VAT, participant limit, cancellation policy y venue/location. [S8](#ref-s8)\\n- Crear single session o multiple session. [S8](#ref-s8)\\n- Publicar eventos publicos o mantenerlos privados segun homepage business. [S2](#ref-s2)\\n\\n**Use cases**\\n- Torneos, workshops, camps, social events, corporate events.\\n- Venta ticketed de ocasiones especiales u open days.\\n\\n**D. Courses**\\n- Cursos multi-sesion vendidos como una sola compra/enrollment. [S2](#ref-s2)[S10](#ref-s10)\\n- Page template con descripcion, precio full-course, custom questions, min/max participants, auto-cancel y refund rules. [S10](#ref-s10)[S11](#ref-s11)\\n- Schedule recurrente o single-session; statuses Published / Private / Cancelled. [S11](#ref-s11)\\n- Smart Courses para late joiners pagando solo sesiones restantes. [S11](#ref-s11)\\n- Participant management con payment status, payment method, revenue y refunds. [S11](#ref-s11)\\n\\n**Use cases**\\n- 8-week academy, beginner series, seasonal programs, kids programs, transformation programs.\\n- Mantener cohortes con control de min/max y cierres automaticos.\\n\\n**E. Credit packages**\\n- Venta de credits prepago desde el negocio/storefront. [S7](#ref-s7)[S10](#ref-s10)[S11](#ref-s11)\\n- Precio, numero de credits, expiracion, purchase limit, time-limited sales, descripcion. [S11](#ref-s11)\\n- Credits venue/trainer-specific, no cross-merchant. [S7](#ref-s7)[S11](#ref-s11)\\n- Hoy documentados para Classes & Events; client help los presenta tambien para classes/events/courses. [S7](#ref-s7)[S11](#ref-s11)\\n\\n**Use cases**\\n- Session passes, bundles, loyalty/prepay, promo windows, member-only offers.\\n- Cobrar por adelantado y reducir friccion en repeat bookings.\\n\\n### 6. Payments / billing / invoicing\\n\\n**Features confirmadas**\\n- Online payments con Stripe o Mollie; Matchable cobra 1.8% platform fee + processing fees del PSP. [S3](#ref-s3)\\n- Aceptar pagos en 36+ paises. [S3](#ref-s3)\\n- Payment method obligatorio antes de aceptar bookings. [S8](#ref-s8)\\n- Invoices automaticas al cliente; visibles en \\\"My invoices\\\". [S3](#ref-s3)[S7](#ref-s7)[S8](#ref-s8)\\n- Pagos van directo al venue/trainer segun client-facing copy. [S7](#ref-s7)[S17](#ref-s17)\\n- Manual bookings gratis. [S3](#ref-s3)\\n- Manual payment links e in-person payments aparecen como coming soon en pricing. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Cobro online nativo sin subscription fee.\\n- Operar mercados internacionales con PSPs estandar.\\n- Emitir comprobantes automaticamente y dar self-serve invoice access al cliente.\\n\\n### 7. Storefront / distribution / embedded commerce\\n\\n**Features confirmadas**\\n- Storefront publico agrega todo lo publicado: private sessions, classes, courses, events, credit packages. [S10](#ref-s10)\\n- Shareable link desde manager; puede usarse en Instagram bio, links directos, etc. [S10](#ref-s10)\\n- Booking widget para incrustar oferta propia en website. [S3](#ref-s3)[S10](#ref-s10)\\n- Marketplace opcional sin fee adicional por descubrir nuevos clientes via marketplace. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Negocio sin web propia que usa Matchable como storefront principal.\\n- Negocio con web propia que embebe widget pero usa Matchable para checkout/ops.\\n- Clubs/academies que combinan demanda organica marketplace + trafico propio.\\n\\n### 8. Trainer operations\\n\\n**Features confirmadas**\\n- Crear trainer con nombre, email, funcion/categoria. [S8](#ref-s8)\\n- Asignar trainer a servicios. [S11](#ref-s11)\\n- Gestionar bookings del trainer desde manager. [S11](#ref-s11)\\n- Primary schedule y temporary schedule del trainer. [S11](#ref-s11)\\n- Holidays que override availability y muestran indisponibilidad al cliente. [S11](#ref-s11)\\n- Trainer app con home, weekly schedule, create training, availability, holidays y profile edit. [S11](#ref-s11)\\n- Release note del trainer app documenta manejo entre multiple venues. [S18](#ref-s18)\\n\\n**Use cases soportados**\\n- Coach independiente que se autogestiona.\\n- Academy con multiples coaches y horarios complejos.\\n- Coach itinerante entre varias sedes.\\n\\n### 9. Venue / academy operations\\n\\n**Features confirmadas**\\n- Venue schedule con opening hours, primary schedule y temporary schedule que overridea al principal. [S8](#ref-s8)\\n- Schedule/Calendar operativo donde conviven trainings, classes y courses. [S9](#ref-s9)[S11](#ref-s11)\\n- Day view / week view y quick booking overview. [S9](#ref-s9)\\n- Crear booking manualmente desde manager. [S9](#ref-s9)[S11](#ref-s11)\\n- Multi-venue management y unlimited manager seats para business tier segun pricing. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Operar aperturas estacionales o holiday schedules.\\n- Ver conflictos y capacidad del dia en una sola vista.\\n- Administrar academies o grupos con varias sedes y varios managers.\\n\\n### 10. Client CRM / customer operations\\n\\n**Features confirmadas**\\n- Client database con nombre, email, phone. [S11](#ref-s11)\\n- Add Client manual. [S11](#ref-s11)\\n- View profile, add booking y WhatsApp contact desde perfil del cliente. [S11](#ref-s11)\\n- Ver booking history y filtros. [S11](#ref-s11)\\n- En cursos: payment status, payment type, revenue, add guest/manual participant, refund handling. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Staff de front desk o academy manager que agrega walk-ins/manual signups.\\n- Seguimiento de recurrentes y soporte posventa.\\n- Gestion de cohortes y refunds en programas.\\n\\n### 11. Promotions / discounts / commercial tooling\\n\\n**Features confirmadas**\\n- Discount codes y vouchers en marketplace checkout. [S6](#ref-s6)\\n- Promotions y vouchers en business homepage. [S2](#ref-s2)\\n- Promotion tools listed as free in pricing. [S3](#ref-s3)\\n- Credit packages con time-limited sales. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Acquisition offers, referral codes, Black Friday/new year campaigns.\\n- Prepaid bundles para aumentar retention y cashflow.\\n\\n### 12. Integrations / ecosystem\\n\\n**A. Court-booking / club systems**\\n- MATCHi: reserva cancha automaticamente al reservar private training; sync real-time; evita double-bookings; oculta slots sin court disponible. [S4](#ref-s4)[S12](#ref-s12)\\n- Matchpoint: auto-reserva court, sync availability y updates, cubre tennis/padel/beach tennis/pickleball. [S15](#ref-s15)\\n- KNLTB Meet & Play: auto court reservation y visibilidad de sesiones en KNLTB app. [S16](#ref-s16)\\n- Overview tambien lista AnyBuddy y Taykus con el mismo patron de auto court booking. [S4](#ref-s4)\\n\\n**Use cases**\\n- Club que quiere vender coaching sin hacer booking manual de cancha.\\n- Academia dentro de club que necesita respetar inventario real de courts.\\n- Ecosistemas federativos/club software donde Matchable actua como capa comercial.\\n\\n**Spec para copiar:** Ver la secci\\u00f3n [Ballbox \\u00d7 ATC](#ballbox-atc-spec-de-integraci-n) al final de este documento para el spec detallado de integraci\\u00f3n tipo MATCHi/Matchpoint/KNLTB, adaptado para Ballbox \\u00d7 ATC.\\n\\n**B. Calendar**\\n- Google Calendar integration page promete two-way sync: bloquear tiempo en Google bloquea disponibilidad en Matchable; cambios en Matchable actualizan Calendar. [S13](#ref-s13)\\n- Help article documenta al menos una suscripcion por URL/ICS a Google Calendar. [S11](#ref-s11)\\n\\n**Use cases**\\n- Coach que mezcla agenda personal y comercial.\\n- Reducir no-shows y overlaps.\\n\\n**Nota critica**\\n- Publicamente hay tension entre marketing (two-way sync) y help (ICS subscription, que normalmente es one-way). Conviene tratar el alcance exacto como \\\"publicamente reclamado, no completamente verificado\\\". [S13](#ref-s13)[S11](#ref-s11)\\n\\n**C. Digital sessions**\\n- Google Meet integration agrega links automaticamente a cada booking. [S14](#ref-s14)\\n- Business homepage y pricing listan digital sessions como capability. [S2](#ref-s2)[S3](#ref-s3)\\n\\n**Use cases**\\n- Remote coaching, video review, nutrition coaching, virtual classes.\\n\\n**D. Adjacent value-add tools**\\n- BenFit: entrenadores conectados con soporte nutricional. [S4](#ref-s4)\\n- PadelFast: conectar training clients con torneos/competiciones. [S4](#ref-s4)\\n\\n**Use cases**\\n- Extender ARPU y experiencia mas alla del booking.\\n- Convertir academia en funnel hacia competicion o nutrition upsell.\\n\\n### 13. Mobile products\\n\\n**Client app**\\n- Book next workout, view booked sessions, location and services, no signup/subscription fee. [S7](#ref-s7)\\n- Release notes: localization, courses, credits, top categories, storefront filters/organized overview, support for unplanned sessions. [S17](#ref-s17)\\n\\n**Trainer app**\\n- Daily/weekly schedule, reviews, connected venues, create training, availability, holidays, profile editing. [S11](#ref-s11)\\n- Release notes: manage bookings/schedules/holidays between multiple venues. [S18](#ref-s18)\\n\\n**Use cases soportados**\\n- Consumo movil para clientes repetitivos.\\n- Coach on-court que no quiere operar desde desktop.\\n\\n### 14. Support / onboarding / enablement\\n\\n**Features confirmadas**\\n- Free onboarding y full customer support segun FAQ de business homepage. [S2](#ref-s2)\\n- Chat support desde manager, email support <24h, knowledge base. [S3](#ref-s3)\\n- Help center estructurado para clients, trainer app y business manager. [S5](#ref-s5)\\n\\n**Use cases soportados**\\n- SMB onboarding rapido.\\n- Soporte operativo y autoservicio documental.\\n\\n### 15. Explicit \\\"coming soon\\\" / weakly evidenced areas\\n\\n**Publicamente listados como coming soon o ambiguos**\\n- Courses en pricing (aunque help center y app release notes los muestran activos). [S3](#ref-s3)[S11](#ref-s11)[S17](#ref-s17)\\n- Insights. [S3](#ref-s3)\\n- Manual payment links. [S3](#ref-s3)\\n- In-person payments. [S3](#ref-s3)\\n- Google Analytics y Meta Pixel add-ons. [S3](#ref-s3)\\n- Recruitment en pricing aparece sin detalle publico util. [S3](#ref-s3)\\n\\n**Lectura**\\n- No asumir cobertura plena ni GA/Pixel productizados a todos los clientes.\\n- Courses/credits/storefront parecen en rollout mas avanzado que pricing copy.\\n\\n## Mapa de casos de uso por persona\\n\\n### Cliente casual\\n- Encontrar un coach/venue por deporte.\\n- Comprar un 1:1 o clase puntual.\\n- Elegir attendees/duracion.\\n- Aplicar voucher.\\n- Pagar y reagendar si hace falta. [S6](#ref-s6)[S7](#ref-s7)\\n\\n### Cliente recurrente\\n- Comprar packages o credits.\\n- Dejar sesiones unplanned y consumirlas despues.\\n- Seguir usando el mismo trainer/venue via storefront/app. [S5](#ref-s5)[S7](#ref-s7)[S10](#ref-s10)\\n\\n### Alumno de programa\\n- Inscribirse a course multi-semana.\\n- Ver schedule completo.\\n- Entrar tarde con Smart Courses si quedan sesiones. [S11](#ref-s11)\\n\\n### Trainer independiente\\n- Publicar perfil y disponibilidad.\\n- Vender privados, clases y online sessions.\\n- Gestionar agenda/holidays desde app.\\n- Usar Google Calendar para coordinar vida personal + trabajo. [S2](#ref-s2)[S11](#ref-s11)[S13](#ref-s13)[S14](#ref-s14)\\n\\n### Venue/academy\\n- Publicar oferta completa en storefront.\\n- Gestionar trainers, bookings y clientes.\\n- Vender credits/cursos/eventos.\\n- Cobrar online e invoicing automatico. [S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n\\n### Racquet club integrado\\n- Mantener MATCHi/Matchpoint/KNLTB como sistema de courts.\\n- Usar Matchable para captar y vender coaching.\\n- Evitar doble reserva de cancha. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n### Operador multi-sede\\n- Administrar varias sedes y multiples managers.\\n- Unificar operacion con mismos flujos de booking/clients/trainers. [S3](#ref-s3)\\n\\n## JTBD map\\n\\n**JTBD: \\\"quiero entrenar esta semana con alguien bueno\\\"**\\n- Search marketplace\\n- Trainer profiles\\n- Reviews\\n- Booking + planning\\n- Reschedule/cancel [S1](#ref-s1)[S6](#ref-s6)[S7](#ref-s7)[S19](#ref-s19)\\n\\n**JTBD: \\\"quiero vender mi coaching sin perseguir pagos ni whatsapps\\\"**\\n- Storefront\\n- Online payments\\n- Packages/credits\\n- Automated invoices\\n- Trainer app [S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n\\n**JTBD: \\\"quiero correr una academia o programa estructurado\\\"**\\n- Courses\\n- Participant limits\\n- Auto-cancel\\n- Smart Courses\\n- Participant management [S11](#ref-s11)\\n\\n**JTBD: \\\"quiero monetizar horas valle o crear comunidad\\\"**\\n- Classes\\n- Events\\n- Credits/promotions\\n- Public marketplace distribution [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)\\n\\n**JTBD: \\\"quiero que vender coaching no rompa mi operacion de club\\\"**\\n- Court-booking integrations\\n- Availability sync\\n- Booking statuses\\n- Multi-venue / manager operations [S3](#ref-s3)[S9](#ref-s9)[S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n**JTBD: \\\"quiero ofrecer coaching online tambien\\\"**\\n- Digital sessions\\n- Google Meet links\\n- Unified profile for in-person + online [S2](#ref-s2)[S14](#ref-s14)\\n\\n## Hallazgos estrategicos\\n\\n1. Matchable parece mas fuerte cuando el negocio vende no solo privados sino un mix de privados + clases + cursos + credits + eventos desde storefront. La plataforma ya esta modelada para ese portfolio, no solo para appointment booking simple. [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n2. El wedge mas diferenciador en racquet sports es academy automation conectada a court inventory externo. Eso resuelve un problema operativo real que marketplaces generalistas no resuelven. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n3. La company esta empujando una evolucion desde \\\"trainer booking\\\" a \\\"sport commerce OS ligero\\\": storefront, widget, apps, credits, courses, integrations, manager. [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)[S17](#ref-s17)[S18](#ref-s18)\\n4. El posicionamiento geografico/publico es multi-country, pero la fuerza de las integraciones y ejemplos visibles sesga hacia Europa y racquet/federation ecosystems. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n## Riesgos, limites y lectura critica\\n\\n- Parte del marketplace publico devuelve `0 results` sin contexto o depende de query/location; por tanto el mapeo se centra en capacidades de producto confirmadas, no en catalogo disponible en cada region. [S20](#ref-s20)[S21](#ref-s21)\\n- Hay copy inconsistente entre pricing y help center/app release notes sobre courses, credits e insights. No conviene asumir rollout uniforme por cliente/mercado. [S3](#ref-s3)[S11](#ref-s11)[S17](#ref-s17)\\n- La profundidad del BI/reporting no es visible publicamente; \\\"insights\\\" aparece, pero sin detalle funcional verificable. [S3](#ref-s3)\\n- La integracion de Google Calendar se describe como two-way en marketing, pero el help publico solo verifica una integracion via URL/ICS; tratar la sincronizacion bidireccional exacta como probable pero no cerrada. [S13](#ref-s13)[S11](#ref-s11)\\n- No pude verificar exhaustivamente todas las venue pages publicas desde muestra puntual; algunas URLs del sitemap no devolvieron contenido util. [S20](#ref-s20)\\n\\n## Fuentes primarias usadas\\n\\n- [S1] Matchable consumer homepage: https://www.matchable.io/\\n- [S2] Matchable business homepage: https://business.matchable.io/\\n- [S3] Matchable pricing: https://matchable.io/business/pricing\\n- [S4] Matchable integrations overview: https://matchable.io/business/integrations\\n- [S5] Matchable help center index: https://help.matchable.io/en/\\n- [S6] How to book a training: https://help.matchable.io/en/articles/10-how-to-book-a-training\\n- [S7] Client app / credits / FAQ / invoices help pages: https://help.matchable.io/en/articles/15-client-app-iosandroid ; https://help.matchable.io/en/articles/23-how-to-use-credits ; https://help.matchable.io/en/articles/12-faq ; https://help.matchable.io/en/articles/39-invoice-for-my-purchases\\n- [S8] Quick-start manager setup pages: https://help.matchable.io/en/articles/1-add-a-payment-method ; https://help.matchable.io/en/articles/2-create-your-first-class-or-event ; https://help.matchable.io/en/articles/3-create-your-first-private-service ; https://help.matchable.io/en/articles/4-how-to-edit-your-trainer-profile ; https://help.matchable.io/en/articles/5-how-to-edit-your-venue-profile ; https://help.matchable.io/en/articles/6-edit-your-availability ; https://help.matchable.io/en/articles/7-add-your-venue-schedule\\n- [S9] Manager operations pages: https://help.matchable.io/en/articles/17-manage-trainings-and-classes ; https://help.matchable.io/en/articles/18-manage-your-trainers-schedules ; https://help.matchable.io/en/articles/19-manage-your-clients ; https://help.matchable.io/en/articles/22-manage-credits\\n- [S10] Storefront guide: https://help.matchable.io/en/articles/38-getting-started-with-your-storefront\\n- [S11] Courses + trainer app help pages: https://help.matchable.io/en/articles/13-getting-started-with-the-matchable-trainer-app ; https://help.matchable.io/en/articles/14-adding-and-managing-your-holidays ; https://help.matchable.io/en/articles/41-getting-started-with-courses ; https://help.matchable.io/en/articles/42-smart-courses-feature ; https://help.matchable.io/en/articles/43-set-up-a-course-page-template ; https://help.matchable.io/en/articles/44-create-and-manage-your-course-schedule ; https://help.matchable.io/en/articles/45-viewing-courses-in-the-calendar ; https://help.matchable.io/en/articles/46-manage-course-participants\\n- [S12] MATCHi integration: https://matchable.io/business/integration/matchi\\n- [S13] Google Calendar integration: https://matchable.io/business/integration/google-calendar\\n- [S14] Google Meet integration: https://matchable.io/business/integration/google-meet\\n- [S15] Matchpoint integration: https://matchable.io/business/integration/matchpoint\\n- [S16] KNLTB Meet & Play integration: https://matchable.io/business/integration/knltb-meet-play\\n- [S17] Client app store pages / release notes: https://apps.apple.com/nl/app/matchable-book-your-training/id6742325816 ; https://play.google.com/store/apps/details?id=com.getmatchable.client\\n- [S18] Trainer app store pages / release notes: https://apps.apple.com/nl/app/matchable-for-trainers/id6468798694 ; https://play.google.com/store/apps/details?id=com.getmatchable.app\\n- [S19] Sample trainer page: https://matchable.io/trainers/alex-hosp\\n- [S20] Matchable sitemap: https://matchable.io/sitemap.xml\\n- [S21] Explore / Activities public pages: https://matchable.io/explore ; https://matchable.io/activities\\n\\n\\n- [S22] Spec Ballbox \\u00d7 ATC: secci\\u00f3n 16 de este documento (Spec de integraci\\u00f3n para copiar patr\\u00f3n MATCHi/Matchpoint/KNLTB en Ballbox)\\n\\n## Ballbox \\u00d7 ATC \\u2014 Spec de Integraci\\u00f3n\\n\\n*Spec de integraci\\u00f3n para copiar el patr\\u00f3n de MATCHi/Matchpoint/KNLTB en Ballbox.*\\n\\n---\\n\\n### 1. Contexto de negocio\\n\\n**Problema que resuelve**\\n\\nUn club de tennis/padel usa ATC como su sistema de gesti\\u00f3n de canchas (reservas, pagos, inventario). Ballbox quiere vender trainings y clases de sus trainers en ese club. El riesgo es vender un entrenamiento cuando la cancha no est\\u00e1 disponible, o duplicar reservas.\\n\\n**Soluci\\u00f3n**\\n\\nCuando alguien reserva un training en Ballbox, el sistema autom\\u00e1ticamente verifica disponibilidad y reserva la cancha en ATC al mismo tiempo. Si el club cancela o modifica la reserva en ATC, Ballbox se entera y act\\u00faa en consecuencia.\\n\\n**Modelo de relaci\\u00f3n**\\n\\n- ATC es el **source of truth** para inventario de canchas\\n- Ballbox es el **canal de venta** de trainings\\n- Ambas plataformas mantienen sync en tiempo real\\n\\n---\\n\\n### 2. Descripci\\u00f3n funcional del flujo\\n\\n#### 2.1. Un cliente busca un entrenamiento\\n\\nEl cliente ve en Ballbox los trainers disponibles de un club. Al seleccionar fecha y horario, Ballbox consulta a ATC qu\\u00e9 canchas est\\u00e1n libres en ese momento. Solo muestra opciones disponibles.\\n\\n#### 2.2. El cliente confirma la reserva\\n\\nCuando el cliente paga o confirma el training en Ballbox:\\n1. Ballbox registra la reserva del training para el trainer\\n2. Simult\\u00e1neamente, Ballbox reserva la cancha en ATC para ese horario\\n3. Ambas reservas quedan linkeadas por un identificador compartido\\n4. Si la cancha no se puede reservar (ya se ocup\\u00f3 entre consulta y confirmaci\\u00f3n), Ballbox informa al cliente y sugiere otro horario\\n\\n#### 2.3. El cliente o el trainer cancela desde Ballbox\\n\\nBallbox cancela la reserva del training y, al mismo tiempo, libera la cancha en ATC.\\n\\n#### 2.4. El club cancela o modifica la reserva desde ATC\\n\\nATC notifica a Ballbox del cambio. Ballbox:\\n- Informa al cliente/trainer\\n- Ofrece reagendar o cancelar sin costo\\n- Marca la reserva como afectada\\n\\n#### 2.5. El club tiene la cancha indisponible (mantenimiento, evento)\\n\\nATC informa a Ballbox. Ballbox marca esas horas como no disponibles para nuevos bookings de trainings.\\n\\n---\\n\\n### 3. Escenarios soportados\\n\\n| Escenario | Comportamiento |\\n|-----------|----------------|\\n| Training reservado en Ballbox, club cierra la cancha | Ballbox notifica al cliente, ofrece reagendar |\\n| Trainer cancela training en Ballbox | La cancha se libera en ATC autom\\u00e1ticamente |\\n| Cliente reserva training, la cancha se ocupa antes de confirmar | Ballbox muestra horarios alternativos |\\n| Ballbox cae durante la reserva | La transacci\\u00f3n se deshace; la cancha en ATC no queda reservada |\\n| ATC tiene mantenimiento | Ballbox lo detecta y muestra \\\"canchas temporalmente no disponibles\\\" |\\n\\n---\\n\\n### 4. Definici\\u00f3n de responsabilidades\\n\\n**Ballbox se encarga de:**\\n- Mostrar la oferta de trainings y trainers\\n- Gestionar el checkout, pago y comunicaci\\u00f3n con el cliente\\n- Mantener el estado del training (confirmado, cancelado, reagendado)\\n- Notificar al cliente ante cambios en disponibilidad de cancha\\n- Persistir la referencia cruzada entre booking de training y booking de cancha\\n\\n**ATC se encarga de:**\\n- Mantener el inventario actualizado de canchas por club\\n- Gestionar reservas de cancha (crear, cancelar, consultar disponibilidad)\\n- Procesar pagos de alquiler de canasta si aplica\\n- Notificar a Ballbox ante cambios en reservas de cancha realizados fuera de Ballbox\\n- Proveer soporte t\\u00e9cnico para la integraci\\u00f3n\\n\\n---\\n\\n### 5. Especificaci\\u00f3n t\\u00e9cnica\\n\\n*Requiere que ATC expose los siguientes endpoints (si no existen, se arman en coordinaci\\u00f3n con ATC).*\\n\\n#### 5.1. Consultar disponibilidad\\n\\n```\\nGET /api/v1/clubs/{club_id}/availability?sport={sport}&date={YYYY-MM-DD}\\n\\nRespuesta:\\n{\\n  \\\"date\\\": \\\"2026-03-25\\\",\\n  \\\"slots\\\": [\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"court_name\\\": \\\"Cancha 1\\\",\\n      \\\"time\\\": \\\"14:00\\\",\\n      \\\"duration_minutes\\\": 60,\\n      \\\"available\\\": true\\n    },\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"time\\\": \\\"15:00\\\",\\n      \\\"available\\\": false,\\n      \\\"reason\\\": \\\"booked\\\"\\n    }\\n  ]\\n}\\n```\\n\\n#### 5.2. Reservar cancha\\n\\n```\\nPOST /api/v1/bookings\\n{\\n  \\\"club_id\\\": \\\"club-123\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\",\\n  \\\"duration_minutes\\\": 60,\\n  \\\"client_name\\\": \\\"Juan P\\u00e9rez\\\",\\n  \\\"client_phone\\\": \\\"+5491112345678\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"notes\\\": \\\"Training Ballbox\\\"\\n}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\",\\n  \\\"court\\\": \\\"Cancha 1\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.3. Cancelar reserva de cancha\\n\\n```\\nDELETE /api/v1/bookings/{atc_booking_id}?reason={reason}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"cancelled\\\"\\n}\\n```\\n\\n#### 5.4. Consultar estado de una reserva\\n\\n```\\nGET /api/v1/bookings/{atc_booking_id}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\" | \\\"cancelled\\\" | \\\"completed\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.5. Webhook \\u2014 Notificaciones desde ATC\\n\\nBallbox expone un endpoint que ATC llama ante cambios:\\n\\n```\\nPOST /ballbox/webhooks/atc\\n\\nPayload:\\n{\\n  \\\"event\\\": \\\"booking_cancelled\\\" | \\\"court_unavailable\\\" | \\\"maintenance\\\",\\n  \\\"atc_booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"reason\\\": \\\"club_cancelled\\\" | \\\"court_blocked\\\",\\n  \\\"affected_slots\\\": [\\\"2026-03-25T14:00:00\\\"]\\n}\\n```\\n\\nBallbox responde con `200 OK` y procesa el evento.\\n\\n#### 5.6. Autenticaci\\u00f3n\\n\\n- ATC provee `api_key` por club\\n- Ballbox env\\u00eda `Authorization: Bearer {api_key}` en cada request\\n- Ballbox expone webhook con firma HMAC para verificar origen\\n\\n---\\n\\n### 6. Configuraci\\u00f3n por club\\n\\nPara activar la integraci\\u00f3n, cada club configura en Ballbox:\\n\\n| Campo | Descripci\\u00f3n |\\n|-------|-------------|\\n| `atc_club_id` | Identificador del club en ATC |\\n| `atc_api_key` | Clave de API entregada por ATC |\\n| `sports_enabled` | Lista de deportes habilitados (tennis, padel, etc.) |\\n| `default_duration_minutes` | Duraci\\u00f3n por defecto de un training |\\n\\n---\\n\\n### 7. Roadmap de implementaci\\u00f3n sugerida\\n\\n**Fase 1 \\u2014 MVP (4-6 semanas)**\\n- Disponibilidad consulta\\n- Reserva de cancha\\n- Cancelaci\\u00f3n desde Ballbox\\n- Sincronizaci\\u00f3n unidireccional (Ballbox \\u2192 ATC)\\n\\n**Fase 2 \\u2014 Bidireccional (2-3 semanas)**\\n- Webhooks desde ATC\\n- Notificaciones al cliente\\n- Manejo de cancelaciones externas\\n\\n**Fase 3 \\u2014 Robustez (2 semanas)**\\n- Retry con backoff ante fallos de ATC\\n- Cola de sincronizaci\\u00f3n para fallos\\n- Panel de estado de integraci\\u00f3n por club\\n\\n---\\n\\n*Spec elaborado el 24 de marzo de 2026, basado en el patr\\u00f3n de integraci\\u00f3n de Matchable con MATCHi/Matchpoint/KNLTB.*\\n\\n## Fecha de corte\\n\\nInvestigacion basada en fuentes publicas verificadas disponibles el 24 de marzo de 2026.\\n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"created_at\": \"2026-03-24T14:26:24.158968+00:00\", \"updated_at\": \"2026-03-24T15:39:47.195210+00:00\", \"metadata\": {\"report_type\": \"feature-use-case-map\", \"run_id\": \"a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"topic\": \"matchable\"}, \"task_title\": \"Matchable: mapa exhaustivo de features y use cases\", \"task_status\": \"done\"}, {\"id\": \"art_smoke_markdown_file_links\", \"task_id\": \"task_smoke_markdown_file_links\", \"artifact_type\": \"report\", \"title\": \"smoke markdown file links\", \"content\": \"[tmp](personal-agent-markdown-link-test.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:smoke\", \"created_at\": \"2026-03-17T21:11:26.188844+00:00\", \"updated_at\": \"2026-03-17T21:11:26.188844+00:00\", \"metadata\": {\"cwd\": \"/tmp\"}, \"task_title\": \"smoke markdown file links\", \"task_status\": \"completed\"}, {\"id\": \"art_5e03c108db5345269e77d02e21d07dd9\", \"task_id\": \"task_84da4829fdea45728971df65c57ff33f\", \"artifact_type\": \"report\", \"title\": \"Codex result for Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"content\": \"Hi Sebas. Kept it tight.\\n\\nDocumented current live flow in [docs/raycast-codex-notify.md](/Users/sebas/personal-agent/docs/raycast-codex-notify.md). It captures the actual implementation split between `~/.codex/hooks/notify_macos.sh` and `~/Code/raycast-codex-reply`, including:\\n\\n- notify hook decision path\\n- rollout-message recovery from `~/.codex/state_5.sqlite`\\n- Raycast reply bridge files + deeplinks\\n- approval watcher flow\\n- fallback AppleScript dialog\\n- explicit note that `personal-agent`\\u2019s old blocker/reply path is removed, so this is not handled by the current runtime\\n\\nAdded a README pointer at [README.md](/Users/sebas/personal-agent/README.md).\\n\\nVerification: `./scripts/run-checks.sh` passed.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:12:31.505135+00:00\", \"updated_at\": \"2026-03-17T02:12:31.505135+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"~/.codex/hooks/notify_macos.sh\", \"~/.codex/state_5.sqlite\", \"~/Code/raycast-codex-reply\"]}, \"run_id\": \"run_9f50b4d09e5842498c055923a851c678\"}, \"task_title\": \"Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"task_status\": \"completed\"}, {\"id\": \"art_d69dff710f97429882a05b0ec979ac5b\", \"task_id\": \"task_be1a1e514a7d43d1b59009ccca9fb57c\", \"artifact_type\": \"report\", \"title\": \"Codex result for Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"content\": \"Hi. Legacy seam closed.\\n\\nCanonical shared-memory model now drives personal-agent surfaces from [shared_memory.py](/Users/sebas/personal-agent/personal_agent/shared_memory.py), with `personal-agent-memory-v1` and `personal-agent-task-v1` helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires `approvals resolve` back into the CLI. [migration.py](/Users/sebas/personal-agent/personal_agent/migration.py) now runs real migration work instead of no-op, and [README.md](/Users/sebas/personal-agent/README.md) reflects the new model.\\n\\nCoverage added in [tests/test_personal.py](/Users/sebas/personal-agent/tests/test_personal.py) for canonical research records, native approval lifecycle, and legacy migration behavior. Verified with `./scripts/run-checks.sh` and `git diff --check`; both passed. No daemon/UI smoke run.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:02:06.161088+00:00\", \"updated_at\": \"2026-03-17T02:02:06.161088+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\" helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires \", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_b694a238b532454bb547c056246a31fd\"}, \"task_title\": \"Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"task_status\": \"completed\"}, {\"id\": \"art_b4f5386484794717b0ddc4c42c265319\", \"task_id\": \"task_871c609196b94132aa686188007f6dea\", \"artifact_type\": \"report\", \"title\": \"Codex result for Consolidate all Ballbox payment-system work from demo validation through production readiness and go-live certification.\", \"content\": \"Consolidated into one active workflow.\\n\\nCreated local repo mapping in [.agents/local-config.json](/Users/sebas/Code/ai-dev-workflow/.agents/local-config.json), set current feature in [.agents/current-feature](/Users/sebas/Code/ai-dev-workflow/.agents/current-feature), and wrote the active feature context in [.agents/feature-contexts/ballbox-payment-system-prod-readiness.json](/Users/sebas/Code/ai-dev-workflow/.agents/feature-contexts/ballbox-payment-system-prod-readiness.json). Added the execution brief/checklist in [docs/ballbox-payment-system-consolidation.md](/Users/sebas/Code/ai-dev-workflow/docs/ballbox-payment-system-consolidation.md).\\n\\nKey consolidation outcome: `ballbox` is stable/demo-facing only; `ballbox-payment-integration` is the real workstream. Demo validation exists now. Production hardening is partially drafted but unstaged in backend. Go-live certification is still blocked by two real gaps: missing TCN/Yunshu live adapter contract, and unvalidated MercadoPago real QR flow.\\n\\nVerification: JSON valid. Shared-memory sync failed because `shared_agent_memory` is not installed/importable in this environment. Control repo also remains behind `origin/main` by 1 commit: `111e974 Feat: accept shared memory run-task handoffs (#2)`. I did not pull because this branch is also 3 commits ahead.\\n\\nBest next move: review and commit the backend readiness slice in `~/Code/ballbox-payment-integration`, then `/status --current`.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T01:55:28.432378+00:00\", \"updated_at\": \"2026-03-17T01:55:28.432378+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\" is not installed/importable in this environment. Control repo also remains behind \", \" is stable/demo-facing only; \", \"~/Code/ballbox-payment-integration\"]}, \"run_id\": \"run_80140950f2c04d10bd3941d712ab0b25\"}, \"task_title\": \"Take the Ballbox payment system from demo flow to production readiness\", \"task_status\": \"completed\"}, {\"id\": \"art_a5cbdcb711234fd3b8306f379678523c\", \"task_id\": \"task_746e1a74f77b4cb0b8e3fd950fad90cb\", \"artifact_type\": \"report\", \"title\": \"link smoke\", \"content\": \"[tct](link) [txt](link.com)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:42:13.176072+00:00\", \"updated_at\": \"2026-03-16T20:42:13.176072+00:00\", \"metadata\": {}, \"task_title\": \"link smoke\", \"task_status\": \"completed\"}, {\"id\": \"art_322e6f0e62724030b8d995053a5ec674\", \"task_id\": \"task_2f22e794212641c49d7f8a600ad3a4bd\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"content\": \"## Summary\\nImplementado en `personal-agent`: el restart del daemon ahora pausa runs activas, las deja en estado reiniciable, y al levantar de nuevo el runtime intenta relanzarlas solo. Tambi\\u00e9n blind\\u00e9 el watcher para que un run ya pausado no termine marcado como fallo cuando llega el `SIGTERM`.\\n\\n## Changes\\n- [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - agregado `pause_running_tasks()`\\n  - `stop()` ahora puede pausar antes de terminar procesos\\n  - runs `running` recuperadas tras restart/crash pasan a `paused`, task vuelve a `draft`, metadata marca `auto_restart_on_daemon_start`\\n  - en boot, `_restart_paused_runs()` relanza tasks pausadas con `cwd`/prompt guardados\\n  - `_watch_run()` sale temprano si el run ya no est\\u00e1 `running`, evita falso `failed`\\n- [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - nuevo comando `pause-running --reason ...`\\n- [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - `restart` ahora ejecuta `python3 scripts/personal.py pause-running ...` antes de `stop/start`\\n- [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n  - actualizado recovery test para validar pause + auto-restart\\n  - nuevo test para pause/shutdown race, sin false failure/artifact\\n\\n## Verification\\n- `python3 -m unittest tests.test_personal` \\u2705\\n- `./scripts/run-checks.sh` \\u2705\\n- `./scripts/daemon-8082.sh restart`\\n  - pause step ejecut\\u00f3 bien\\n  - restart completo bloqueado por entorno actual: `\\\"foreign listener on 127.0.0.1:8082 (pid 18283); refusing to stop it\\\"`\\n- `curl -fsS http://127.0.0.1:8082/api/status` \\u2705\\n  - confirm\\u00f3 que la task activa qued\\u00f3 `draft` con latest run `paused`\\n\\n## Outputs\\n- Branch: none\\n- PR: none\\n- Files changed:\\n  - [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n- Artifacts created: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:25:49.823843+00:00\", \"updated_at\": \"2026-03-16T20:25:49.823843+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"branches\": [\"none\"], \"paths\": [\" recuperadas tras restart/crash pasan a \", \"./scripts/daemon-8082.sh restart\", \"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent/personal_agent/runtime.py\", \"/Users/sebas/personal-agent/scripts/daemon-8082.sh\", \"/Users/sebas/personal-agent/scripts/personal.py\", \"/Users/sebas/personal-agent/tests/test_personal.py\", \"curl -fsS http://127.0.0.1:8082/api/status\", \"python3 scripts/personal.py pause-running ...\", \"stop/start\"]}, \"run_id\": \"run_8ff645c9a9ad4d558df0265495267a41\"}, \"task_title\": \"en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"task_status\": \"completed\"}, {\"id\": \"art_d7f2bb1c7a204e56834b97bc4e77989b\", \"task_id\": \"task_8a866bb8156441ff8cee2f0f9f28e0c5\", \"artifact_type\": \"report\", \"title\": \"Codex result for en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"content\": \"## Summary\\nAgregado soporte markdown para links en artifacts/report renderizados por el daemon. `[USECASE.md](http://...)` ahora sale como `<a>` clickable, no literal. Hecho en worktree nuevo; adem\\u00e1s dej\\u00e9 un test existente compatible con worktrees.\\n\\n## Changes\\n- Link markdown inline en [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py#L630)\\n  - parse `[label](href)`\\n  - `href` allowlist: `http`, `https`, `mailto`, `/`, `./`, `../`, `#`\\n  - links no seguros quedan literales\\n- Tests en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1653)\\n  - cubre render de link local `http://127.0.0.1:8082/artifacts/...`\\n  - cubre fallback seguro para `javascript:...`\\n- Fix de test fr\\u00e1gil para worktree en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1345)\\n  - deja de asumir path absoluto fijo del repo principal\\n\\n## Verification\\n- `./scripts/run-checks.sh`\\n- Resultado: `Ran 36 tests ... OK`\\n\\n## Outputs\\n- Worktree: `/Users/sebas/personal-agent-wt-markdown-links`\\n- Branch: `fix-artifact-markdown-links`\\n- Files changed:\\n  - [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py)\\n  - [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py)\\n- PR: none\\n- Artifacts: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T19:15:50.674755+00:00\", \"updated_at\": \"2026-03-16T19:15:50.674755+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent-wt-markdown-links\", \"[USECASE.md](http://...)\"]}, \"run_id\": \"run_cce5f6d82e0148f6a56c9c12d159711e\"}, \"task_title\": \"en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"task_status\": \"completed\"}, {\"id\": \"art_b418ed73b479471eb1a936388268b7e9\", \"task_id\": \"task_273752f696ea4b87b2dba4497bad37f7\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"content\": \"## Summary\\n\\nAgregu\\u00e9 spacing estable en la UI del dashboard para evitar layout shifts en el resumen `\\\"drafts / running / failed / results\\\"` y en las cajas/listas de estados. El cambio qued\\u00f3 implementado en la UI inline del daemon.\\n\\n## Changes\\n\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L33) ajust\\u00e9 la grilla para alinear cards arriba y dar altura m\\u00ednima a panels.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L52) reemplac\\u00e9 el summary textual por una `summary-grid` con 4 cards de ancho reservado, para que el cambio de n\\u00fameros no mueva el layout.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L56) agregu\\u00e9 `list-slot` y `empty-state` con altura m\\u00ednima para estabilizar Drafts, Active Runs, Recent Results y Failed Runs.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L116) actualic\\u00e9 `renderList()` y sum\\u00e9 `renderSummary()` para render consistente durante refresh y estados vac\\u00edos.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L60) agregu\\u00e9 ajuste responsive para mobile sin mantener alturas forzadas innecesarias.\\n\\n## Verification\\n\\n- `./scripts/run-checks.sh` \\u2705\\n- Smoke UI en instancia temporal `127.0.0.1:8090` \\u2705\\n- Verifiqu\\u00e9 que el HTML servido incluye `summary-grid`, `summary-card`, `list-slot`, `empty-state` \\u2705\\n- No pude reiniciar `127.0.0.1:8082`: el helper detect\\u00f3 listener ajeno `pid 81699` y se neg\\u00f3 a pararlo. El `8082` actual segu\\u00eda sirviendo HTML previo.\\n\\n## Outputs\\n\\n- Branch: sin cambios\\n- PR: ninguno\\n- Archivo modificado: [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py)\\n- Artifact temporal validado: dashboard smoke en `http://127.0.0.1:8090/` durante la verificaci\\u00f3n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:55:10.658042+00:00\", \"updated_at\": \"2026-03-16T18:55:10.658042+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/personal-agent-simple-codex-runner\", \"output_refs\": {\"branches\": [\"sin\"], \"paths\": [\"\\\"drafts / running / failed / results\\\"\", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_382bb0979ec643e5b780c43c49f59103\"}, \"task_title\": \"en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"task_status\": \"completed\"}, {\"id\": \"art_b90cb99f638c45ecbb358d2f51cdad89\", \"task_id\": \"task_12b3a671a5d5494e9f0ed28ac8a16079\", \"artifact_type\": \"report\", \"title\": \"Codex result for quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"content\": \"## Summary\\nAbr\\u00ed un worktree nuevo para `ballbox-payment-integration`, agregu\\u00e9 una gu\\u00eda `USECASE.md` en espa\\u00f1ol explicando c\\u00f3mo se usa el producto end-to-end, la linke\\u00e9 desde el `README.md`, hice commit, push y abr\\u00ed PR.\\n\\n## Changes\\n- Nuevo doc: [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n- Link de acceso r\\u00e1pido en [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\\n- Contenido cubre:\\n  - qu\\u00e9 resuelve el bridge\\n  - actores\\n  - flujo `/pay` -> QR -> webhook -> callback a m\\u00e1quina\\n  - uso local/demo\\n  - prerequisitos de producci\\u00f3n\\n  - l\\u00edmites actuales\\n\\n## Verification\\n- `npm install`\\n- `npm run typecheck`\\n- `npm test`\\n- Resultado: verde\\n- Worktree limpio al final en branch publicada\\n\\n## Outputs\\n- Branch: `docs/usecase-md`\\n- PR: `#1` `Add product usage guide`\\n- Worktree: `/Users/sebas/Code/ballbox-payment-integration-usecase`\\n- Files:\\n  - [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n  - [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:52:19.557278+00:00\", \"updated_at\": \"2026-03-16T18:52:19.557278+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\"/Users/sebas/Code/ballbox-payment-integration-usecase\", \"docs/usecase-md\"]}, \"run_id\": \"run_f6edf712c14d4153bde400000125024b\"}, \"task_title\": \"quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"task_status\": \"completed\"}], \"cwd_options\": [{\"name\": \"personal-agent\", \"path\": \"/mnt/rpi/repos/opencode-harness\", \"source\": \"known\", \"repo_id\": \"repo_personal_agent\"}, {\"name\": \"ballbox-company-agent\", \"path\": \"/mnt/rpi/repos/ballbox-company-agent\", \"source\": \"known\", \"repo_id\": \"repo_ballbox_company_agent\"}, {\"name\": \"ballbox\", \"path\": \"/mnt/rpi/repos/ballbox\", \"source\": \"workspace\"}, {\"name\": \"browser-harness\", \"path\": \"/mnt/rpi/repos/browser-harness\", \"source\": \"workspace\"}, {\"name\": \"FelipeVersion\", \"path\": \"/mnt/rpi/repos/FelipeVersion\", \"source\": \"workspace\"}], \"summary\": {\"draft_count\": 8, \"running_count\": 0, \"failed_count\": 3, \"result_count\": 12}}\n\n[Showing last 50.0KB of line 12 (line is 95.2KB). Full output: /tmp/pi-bash-30ae8692267ce0ce.log]"}],"details":{"truncation":{"content":"agos, bookings y clientes. [S2](#ref-s2)[S3](#ref-s3)[S8](#ref-s8)[S9](#ref-s9)[S10](#ref-s10)\\n- Operador multi-sede: administra multiples venues y managers desde el mismo manager; sincroniza operaciones con sistemas externos. [S2](#ref-s2)[S3](#ref-s3)\\n- Clubes de raqueta con sistema propio: mantienen MATCHi/Matchpoint/KNLTB/etc. como system of record de courts y usan Matchable como capa comercial/academy automation. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16) Abajo se detalla c\\u00f3mo Ballbox podr\\u00eda implementar una integraci\\u00f3n similar con ATC para el mercado LATAM. [\\u2192 Ballbox \\u00d7 ATC](#ballbox-atc-spec-de-integraci-n)\\n\\n## Superficies clave\\n\\n- Discovery marketplace: `explore`, `activities`, perfiles de trainer/venue. [S1](#ref-s1)[S6](#ref-s6)\\n- Booking flow: seleccion de servicio, attendees, duracion, package, planning, login/signup, pago. [S6](#ref-s6)\\n- Storefront: home publica de cada negocio con toda la oferta activa. [S10](#ref-s10)\\n- Manager: schedule, bookings, trainers, clients, services, promotions, settings, payment method. [S8](#ref-s8)[S9](#ref-s9)[S11](#ref-s11)\\n- Trainer App: home, weekly schedule, create training, availability, holidays, profile. [S11](#ref-s11)\\n- Client App: discovery, booked sessions, services, locations, booking/pago. [S7](#ref-s7)[S17](#ref-s17)\\n- Integrations hub: calendars, video, courts, nutrition, tournaments. [S4](#ref-s4)[S12](#ref-s12)[S13](#ref-s13)[S14](#ref-s14)[S15](#ref-s15)[S16](#ref-s16)\\n\\n## Mapa exhaustivo de features\\n\\n### 1. Discovery / marketplace cliente\\n\\n**Features confirmadas**\\n- Buscar trainer, venue o deporte desde la web/app. [S1](#ref-s1)[S6](#ref-s6)[S17](#ref-s17)\\n- Navegar categorias/top categories y distintos deportes; homepage cita fitness, yoga, padel y \\\"everything in between\\\"; app stores mencionan padel, tennis, yoga, fitness y boxing. [S1](#ref-s1)[S17](#ref-s17)[S18](#ref-s18)\\n- Ver perfiles publicos de trainer con idiomas, ubicacion, reviews y servicios. [S1](#ref-s1)[S19](#ref-s19)\\n- Ver venue/storefront con nombre, descripcion, fotos, ubicacion, reviews y toda la oferta activa. [S10](#ref-s10)\\n- Filtrar/ordenar oferta desde storefront/app; release notes del client app documentan nuevos filtros y organized overview. [S17](#ref-s17)\\n\\n**Use cases soportados**\\n- Encontrar entrenador o actividad cercana/adecuada sin depender del sitio propio de cada club.\\n- Comparar private sessions, classes, courses y events en una sola experiencia.\\n- Descubrir negocios via marketplace y luego convertir por link directo/storefront.\\n\\n**Justificacion**\\n- Directa por homepage, client app copy, help de booking y help de storefront. [S1](#ref-s1)[S6](#ref-s6)[S10](#ref-s10)[S17](#ref-s17)\\n\\n### 2. Profiles / trust layer\\n\\n**Features confirmadas**\\n- Trainer profile con foto, banner, bio, specializations, languages, contact details y socials. [S8](#ref-s8)[S11](#ref-s11)[S19](#ref-s19)\\n- Venue profile con logo, banner, bio, location, contact info, socials y amenities. [S8](#ref-s8)\\n- Reviews en trainer/storefront; FAQ dice que el usuario recibe email post-sesion para dejar review. [S1](#ref-s1)[S7](#ref-s7)[S10](#ref-s10)[S19](#ref-s19)\\n- Visibility toggles para marketplace y venue page. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Elegir coach por fit, idioma, especialidad o reputacion.\\n- Mejorar conversion del negocio con trust signals y contenido visual.\\n- Ocultar o publicar trainers/servicios segun estrategia comercial.\\n\\n### 3. Booking / checkout core\\n\\n**Features confirmadas**\\n- Elegir tipo de training (ej. group lesson vs private 1-to-1). [S6](#ref-s6)\\n- Elegir numero de attendees. [S6](#ref-s6)\\n- Elegir duracion. [S6](#ref-s6)\\n- Elegir package / bundle con descuento por multiples clases. [S6](#ref-s6)\\n- Aplicar discount o voucher code. [S6](#ref-s6)\\n- Planear la sesion en checkout o dejarla unplanned para despues. [S5](#ref-s5)[S6](#ref-s6)\\n- Crear cuenta/log in y pagar online. [S6](#ref-s6)\\n- Sin fee de plataforma para cliente segun copy publica. [S1](#ref-s1)[S3](#ref-s3)[S7](#ref-s7)[S17](#ref-s17)\\n\\n**Use cases soportados**\\n- Reservar un 1:1, una small group session o una compra futura de varias sesiones.\\n- Comprar ahora y coordinar agenda despues.\\n- Ejecutar campa\\u00f1as con vouchers/codigos.\\n\\n### 4. Session planning / post-booking lifecycle\\n\\n**Features confirmadas**\\n- Trainings pueden quedar unplanned y luego programarse desde la cuenta del cliente. [S5](#ref-s5)\\n- Reagendar o cancelar desde el perfil, sujeto a cancellation policy del provider. [S5](#ref-s5)[S7](#ref-s7)\\n- Cambiar trainer en ciertos flujos de reschedule. [S5](#ref-s5)\\n- Booking statuses Planned / Unplanned. [S9](#ref-s9)\\n- Businesses pueden marcar bookings como Redeemed/completados. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Vender packs antes de definir agenda exacta.\\n- Reacomodar sesiones por clima, disponibilidad o lesion.\\n- Cerrar operativamente una sesion como consumida.\\n\\n### 5. Offer types / catalog model\\n\\n**A. Private training / private service**\\n- Crear private training con descripcion, VAT, cancellation policy, booking buffer y advance booking limit. [S8](#ref-s8)\\n- Definir pricing categories, capacidad, trainer asignado, duracion, precio por sesion y packages. [S8](#ref-s8)\\n- Publicar/ocultar servicio. [S8](#ref-s8)\\n- Marketplace y pricing lo posicionan como pilar central. [S2](#ref-s2)[S3](#ref-s3)\\n\\n**Use cases**\\n- Coach de tennis/padel/personal training que vende 1:1 o small group.\\n- Academia que diferencia peak/off-peak, duraciones y capacidad.\\n\\n**B. Classes**\\n- Clases recurrentes con set schedules y capacity limits. [S2](#ref-s2)\\n- Clientes compran spots individuales en group sessions. [S2](#ref-s2)\\n- Se muestran spots restantes en storefront. [S10](#ref-s10)\\n\\n**Use cases**\\n- Weekly yoga/fitness/padel clinics.\\n- Llenar horas valle con group sessions abiertas.\\n\\n**C. Events**\\n- Crear event page con banner, descripcion, tickets, VAT, participant limit, cancellation policy y venue/location. [S8](#ref-s8)\\n- Crear single session o multiple session. [S8](#ref-s8)\\n- Publicar eventos publicos o mantenerlos privados segun homepage business. [S2](#ref-s2)\\n\\n**Use cases**\\n- Torneos, workshops, camps, social events, corporate events.\\n- Venta ticketed de ocasiones especiales u open days.\\n\\n**D. Courses**\\n- Cursos multi-sesion vendidos como una sola compra/enrollment. [S2](#ref-s2)[S10](#ref-s10)\\n- Page template con descripcion, precio full-course, custom questions, min/max participants, auto-cancel y refund rules. [S10](#ref-s10)[S11](#ref-s11)\\n- Schedule recurrente o single-session; statuses Published / Private / Cancelled. [S11](#ref-s11)\\n- Smart Courses para late joiners pagando solo sesiones restantes. [S11](#ref-s11)\\n- Participant management con payment status, payment method, revenue y refunds. [S11](#ref-s11)\\n\\n**Use cases**\\n- 8-week academy, beginner series, seasonal programs, kids programs, transformation programs.\\n- Mantener cohortes con control de min/max y cierres automaticos.\\n\\n**E. Credit packages**\\n- Venta de credits prepago desde el negocio/storefront. [S7](#ref-s7)[S10](#ref-s10)[S11](#ref-s11)\\n- Precio, numero de credits, expiracion, purchase limit, time-limited sales, descripcion. [S11](#ref-s11)\\n- Credits venue/trainer-specific, no cross-merchant. [S7](#ref-s7)[S11](#ref-s11)\\n- Hoy documentados para Classes & Events; client help los presenta tambien para classes/events/courses. [S7](#ref-s7)[S11](#ref-s11)\\n\\n**Use cases**\\n- Session passes, bundles, loyalty/prepay, promo windows, member-only offers.\\n- Cobrar por adelantado y reducir friccion en repeat bookings.\\n\\n### 6. Payments / billing / invoicing\\n\\n**Features confirmadas**\\n- Online payments con Stripe o Mollie; Matchable cobra 1.8% platform fee + processing fees del PSP. [S3](#ref-s3)\\n- Aceptar pagos en 36+ paises. [S3](#ref-s3)\\n- Payment method obligatorio antes de aceptar bookings. [S8](#ref-s8)\\n- Invoices automaticas al cliente; visibles en \\\"My invoices\\\". [S3](#ref-s3)[S7](#ref-s7)[S8](#ref-s8)\\n- Pagos van directo al venue/trainer segun client-facing copy. [S7](#ref-s7)[S17](#ref-s17)\\n- Manual bookings gratis. [S3](#ref-s3)\\n- Manual payment links e in-person payments aparecen como coming soon en pricing. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Cobro online nativo sin subscription fee.\\n- Operar mercados internacionales con PSPs estandar.\\n- Emitir comprobantes automaticamente y dar self-serve invoice access al cliente.\\n\\n### 7. Storefront / distribution / embedded commerce\\n\\n**Features confirmadas**\\n- Storefront publico agrega todo lo publicado: private sessions, classes, courses, events, credit packages. [S10](#ref-s10)\\n- Shareable link desde manager; puede usarse en Instagram bio, links directos, etc. [S10](#ref-s10)\\n- Booking widget para incrustar oferta propia en website. [S3](#ref-s3)[S10](#ref-s10)\\n- Marketplace opcional sin fee adicional por descubrir nuevos clientes via marketplace. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Negocio sin web propia que usa Matchable como storefront principal.\\n- Negocio con web propia que embebe widget pero usa Matchable para checkout/ops.\\n- Clubs/academies que combinan demanda organica marketplace + trafico propio.\\n\\n### 8. Trainer operations\\n\\n**Features confirmadas**\\n- Crear trainer con nombre, email, funcion/categoria. [S8](#ref-s8)\\n- Asignar trainer a servicios. [S11](#ref-s11)\\n- Gestionar bookings del trainer desde manager. [S11](#ref-s11)\\n- Primary schedule y temporary schedule del trainer. [S11](#ref-s11)\\n- Holidays que override availability y muestran indisponibilidad al cliente. [S11](#ref-s11)\\n- Trainer app con home, weekly schedule, create training, availability, holidays y profile edit. [S11](#ref-s11)\\n- Release note del trainer app documenta manejo entre multiple venues. [S18](#ref-s18)\\n\\n**Use cases soportados**\\n- Coach independiente que se autogestiona.\\n- Academy con multiples coaches y horarios complejos.\\n- Coach itinerante entre varias sedes.\\n\\n### 9. Venue / academy operations\\n\\n**Features confirmadas**\\n- Venue schedule con opening hours, primary schedule y temporary schedule que overridea al principal. [S8](#ref-s8)\\n- Schedule/Calendar operativo donde conviven trainings, classes y courses. [S9](#ref-s9)[S11](#ref-s11)\\n- Day view / week view y quick booking overview. [S9](#ref-s9)\\n- Crear booking manualmente desde manager. [S9](#ref-s9)[S11](#ref-s11)\\n- Multi-venue management y unlimited manager seats para business tier segun pricing. [S3](#ref-s3)\\n\\n**Use cases soportados**\\n- Operar aperturas estacionales o holiday schedules.\\n- Ver conflictos y capacidad del dia en una sola vista.\\n- Administrar academies o grupos con varias sedes y varios managers.\\n\\n### 10. Client CRM / customer operations\\n\\n**Features confirmadas**\\n- Client database con nombre, email, phone. [S11](#ref-s11)\\n- Add Client manual. [S11](#ref-s11)\\n- View profile, add booking y WhatsApp contact desde perfil del cliente. [S11](#ref-s11)\\n- Ver booking history y filtros. [S11](#ref-s11)\\n- En cursos: payment status, payment type, revenue, add guest/manual participant, refund handling. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Staff de front desk o academy manager que agrega walk-ins/manual signups.\\n- Seguimiento de recurrentes y soporte posventa.\\n- Gestion de cohortes y refunds en programas.\\n\\n### 11. Promotions / discounts / commercial tooling\\n\\n**Features confirmadas**\\n- Discount codes y vouchers en marketplace checkout. [S6](#ref-s6)\\n- Promotions y vouchers en business homepage. [S2](#ref-s2)\\n- Promotion tools listed as free in pricing. [S3](#ref-s3)\\n- Credit packages con time-limited sales. [S11](#ref-s11)\\n\\n**Use cases soportados**\\n- Acquisition offers, referral codes, Black Friday/new year campaigns.\\n- Prepaid bundles para aumentar retention y cashflow.\\n\\n### 12. Integrations / ecosystem\\n\\n**A. Court-booking / club systems**\\n- MATCHi: reserva cancha automaticamente al reservar private training; sync real-time; evita double-bookings; oculta slots sin court disponible. [S4](#ref-s4)[S12](#ref-s12)\\n- Matchpoint: auto-reserva court, sync availability y updates, cubre tennis/padel/beach tennis/pickleball. [S15](#ref-s15)\\n- KNLTB Meet & Play: auto court reservation y visibilidad de sesiones en KNLTB app. [S16](#ref-s16)\\n- Overview tambien lista AnyBuddy y Taykus con el mismo patron de auto court booking. [S4](#ref-s4)\\n\\n**Use cases**\\n- Club que quiere vender coaching sin hacer booking manual de cancha.\\n- Academia dentro de club que necesita respetar inventario real de courts.\\n- Ecosistemas federativos/club software donde Matchable actua como capa comercial.\\n\\n**Spec para copiar:** Ver la secci\\u00f3n [Ballbox \\u00d7 ATC](#ballbox-atc-spec-de-integraci-n) al final de este documento para el spec detallado de integraci\\u00f3n tipo MATCHi/Matchpoint/KNLTB, adaptado para Ballbox \\u00d7 ATC.\\n\\n**B. Calendar**\\n- Google Calendar integration page promete two-way sync: bloquear tiempo en Google bloquea disponibilidad en Matchable; cambios en Matchable actualizan Calendar. [S13](#ref-s13)\\n- Help article documenta al menos una suscripcion por URL/ICS a Google Calendar. [S11](#ref-s11)\\n\\n**Use cases**\\n- Coach que mezcla agenda personal y comercial.\\n- Reducir no-shows y overlaps.\\n\\n**Nota critica**\\n- Publicamente hay tension entre marketing (two-way sync) y help (ICS subscription, que normalmente es one-way). Conviene tratar el alcance exacto como \\\"publicamente reclamado, no completamente verificado\\\". [S13](#ref-s13)[S11](#ref-s11)\\n\\n**C. Digital sessions**\\n- Google Meet integration agrega links automaticamente a cada booking. [S14](#ref-s14)\\n- Business homepage y pricing listan digital sessions como capability. [S2](#ref-s2)[S3](#ref-s3)\\n\\n**Use cases**\\n- Remote coaching, video review, nutrition coaching, virtual classes.\\n\\n**D. Adjacent value-add tools**\\n- BenFit: entrenadores conectados con soporte nutricional. [S4](#ref-s4)\\n- PadelFast: conectar training clients con torneos/competiciones. [S4](#ref-s4)\\n\\n**Use cases**\\n- Extender ARPU y experiencia mas alla del booking.\\n- Convertir academia en funnel hacia competicion o nutrition upsell.\\n\\n### 13. Mobile products\\n\\n**Client app**\\n- Book next workout, view booked sessions, location and services, no signup/subscription fee. [S7](#ref-s7)\\n- Release notes: localization, courses, credits, top categories, storefront filters/organized overview, support for unplanned sessions. [S17](#ref-s17)\\n\\n**Trainer app**\\n- Daily/weekly schedule, reviews, connected venues, create training, availability, holidays, profile editing. [S11](#ref-s11)\\n- Release notes: manage bookings/schedules/holidays between multiple venues. [S18](#ref-s18)\\n\\n**Use cases soportados**\\n- Consumo movil para clientes repetitivos.\\n- Coach on-court que no quiere operar desde desktop.\\n\\n### 14. Support / onboarding / enablement\\n\\n**Features confirmadas**\\n- Free onboarding y full customer support segun FAQ de business homepage. [S2](#ref-s2)\\n- Chat support desde manager, email support <24h, knowledge base. [S3](#ref-s3)\\n- Help center estructurado para clients, trainer app y business manager. [S5](#ref-s5)\\n\\n**Use cases soportados**\\n- SMB onboarding rapido.\\n- Soporte operativo y autoservicio documental.\\n\\n### 15. Explicit \\\"coming soon\\\" / weakly evidenced areas\\n\\n**Publicamente listados como coming soon o ambiguos**\\n- Courses en pricing (aunque help center y app release notes los muestran activos). [S3](#ref-s3)[S11](#ref-s11)[S17](#ref-s17)\\n- Insights. [S3](#ref-s3)\\n- Manual payment links. [S3](#ref-s3)\\n- In-person payments. [S3](#ref-s3)\\n- Google Analytics y Meta Pixel add-ons. [S3](#ref-s3)\\n- Recruitment en pricing aparece sin detalle publico util. [S3](#ref-s3)\\n\\n**Lectura**\\n- No asumir cobertura plena ni GA/Pixel productizados a todos los clientes.\\n- Courses/credits/storefront parecen en rollout mas avanzado que pricing copy.\\n\\n## Mapa de casos de uso por persona\\n\\n### Cliente casual\\n- Encontrar un coach/venue por deporte.\\n- Comprar un 1:1 o clase puntual.\\n- Elegir attendees/duracion.\\n- Aplicar voucher.\\n- Pagar y reagendar si hace falta. [S6](#ref-s6)[S7](#ref-s7)\\n\\n### Cliente recurrente\\n- Comprar packages o credits.\\n- Dejar sesiones unplanned y consumirlas despues.\\n- Seguir usando el mismo trainer/venue via storefront/app. [S5](#ref-s5)[S7](#ref-s7)[S10](#ref-s10)\\n\\n### Alumno de programa\\n- Inscribirse a course multi-semana.\\n- Ver schedule completo.\\n- Entrar tarde con Smart Courses si quedan sesiones. [S11](#ref-s11)\\n\\n### Trainer independiente\\n- Publicar perfil y disponibilidad.\\n- Vender privados, clases y online sessions.\\n- Gestionar agenda/holidays desde app.\\n- Usar Google Calendar para coordinar vida personal + trabajo. [S2](#ref-s2)[S11](#ref-s11)[S13](#ref-s13)[S14](#ref-s14)\\n\\n### Venue/academy\\n- Publicar oferta completa en storefront.\\n- Gestionar trainers, bookings y clientes.\\n- Vender credits/cursos/eventos.\\n- Cobrar online e invoicing automatico. [S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n\\n### Racquet club integrado\\n- Mantener MATCHi/Matchpoint/KNLTB como sistema de courts.\\n- Usar Matchable para captar y vender coaching.\\n- Evitar doble reserva de cancha. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n### Operador multi-sede\\n- Administrar varias sedes y multiples managers.\\n- Unificar operacion con mismos flujos de booking/clients/trainers. [S3](#ref-s3)\\n\\n## JTBD map\\n\\n**JTBD: \\\"quiero entrenar esta semana con alguien bueno\\\"**\\n- Search marketplace\\n- Trainer profiles\\n- Reviews\\n- Booking + planning\\n- Reschedule/cancel [S1](#ref-s1)[S6](#ref-s6)[S7](#ref-s7)[S19](#ref-s19)\\n\\n**JTBD: \\\"quiero vender mi coaching sin perseguir pagos ni whatsapps\\\"**\\n- Storefront\\n- Online payments\\n- Packages/credits\\n- Automated invoices\\n- Trainer app [S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n\\n**JTBD: \\\"quiero correr una academia o programa estructurado\\\"**\\n- Courses\\n- Participant limits\\n- Auto-cancel\\n- Smart Courses\\n- Participant management [S11](#ref-s11)\\n\\n**JTBD: \\\"quiero monetizar horas valle o crear comunidad\\\"**\\n- Classes\\n- Events\\n- Credits/promotions\\n- Public marketplace distribution [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)\\n\\n**JTBD: \\\"quiero que vender coaching no rompa mi operacion de club\\\"**\\n- Court-booking integrations\\n- Availability sync\\n- Booking statuses\\n- Multi-venue / manager operations [S3](#ref-s3)[S9](#ref-s9)[S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n**JTBD: \\\"quiero ofrecer coaching online tambien\\\"**\\n- Digital sessions\\n- Google Meet links\\n- Unified profile for in-person + online [S2](#ref-s2)[S14](#ref-s14)\\n\\n## Hallazgos estrategicos\\n\\n1. Matchable parece mas fuerte cuando el negocio vende no solo privados sino un mix de privados + clases + cursos + credits + eventos desde storefront. La plataforma ya esta modelada para ese portfolio, no solo para appointment booking simple. [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)[S11](#ref-s11)\\n2. El wedge mas diferenciador en racquet sports es academy automation conectada a court inventory externo. Eso resuelve un problema operativo real que marketplaces generalistas no resuelven. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n3. La company esta empujando una evolucion desde \\\"trainer booking\\\" a \\\"sport commerce OS ligero\\\": storefront, widget, apps, credits, courses, integrations, manager. [S2](#ref-s2)[S3](#ref-s3)[S10](#ref-s10)[S17](#ref-s17)[S18](#ref-s18)\\n4. El posicionamiento geografico/publico es multi-country, pero la fuerza de las integraciones y ejemplos visibles sesga hacia Europa y racquet/federation ecosystems. [S12](#ref-s12)[S15](#ref-s15)[S16](#ref-s16)\\n\\n## Riesgos, limites y lectura critica\\n\\n- Parte del marketplace publico devuelve `0 results` sin contexto o depende de query/location; por tanto el mapeo se centra en capacidades de producto confirmadas, no en catalogo disponible en cada region. [S20](#ref-s20)[S21](#ref-s21)\\n- Hay copy inconsistente entre pricing y help center/app release notes sobre courses, credits e insights. No conviene asumir rollout uniforme por cliente/mercado. [S3](#ref-s3)[S11](#ref-s11)[S17](#ref-s17)\\n- La profundidad del BI/reporting no es visible publicamente; \\\"insights\\\" aparece, pero sin detalle funcional verificable. [S3](#ref-s3)\\n- La integracion de Google Calendar se describe como two-way en marketing, pero el help publico solo verifica una integracion via URL/ICS; tratar la sincronizacion bidireccional exacta como probable pero no cerrada. [S13](#ref-s13)[S11](#ref-s11)\\n- No pude verificar exhaustivamente todas las venue pages publicas desde muestra puntual; algunas URLs del sitemap no devolvieron contenido util. [S20](#ref-s20)\\n\\n## Fuentes primarias usadas\\n\\n- [S1] Matchable consumer homepage: https://www.matchable.io/\\n- [S2] Matchable business homepage: https://business.matchable.io/\\n- [S3] Matchable pricing: https://matchable.io/business/pricing\\n- [S4] Matchable integrations overview: https://matchable.io/business/integrations\\n- [S5] Matchable help center index: https://help.matchable.io/en/\\n- [S6] How to book a training: https://help.matchable.io/en/articles/10-how-to-book-a-training\\n- [S7] Client app / credits / FAQ / invoices help pages: https://help.matchable.io/en/articles/15-client-app-iosandroid ; https://help.matchable.io/en/articles/23-how-to-use-credits ; https://help.matchable.io/en/articles/12-faq ; https://help.matchable.io/en/articles/39-invoice-for-my-purchases\\n- [S8] Quick-start manager setup pages: https://help.matchable.io/en/articles/1-add-a-payment-method ; https://help.matchable.io/en/articles/2-create-your-first-class-or-event ; https://help.matchable.io/en/articles/3-create-your-first-private-service ; https://help.matchable.io/en/articles/4-how-to-edit-your-trainer-profile ; https://help.matchable.io/en/articles/5-how-to-edit-your-venue-profile ; https://help.matchable.io/en/articles/6-edit-your-availability ; https://help.matchable.io/en/articles/7-add-your-venue-schedule\\n- [S9] Manager operations pages: https://help.matchable.io/en/articles/17-manage-trainings-and-classes ; https://help.matchable.io/en/articles/18-manage-your-trainers-schedules ; https://help.matchable.io/en/articles/19-manage-your-clients ; https://help.matchable.io/en/articles/22-manage-credits\\n- [S10] Storefront guide: https://help.matchable.io/en/articles/38-getting-started-with-your-storefront\\n- [S11] Courses + trainer app help pages: https://help.matchable.io/en/articles/13-getting-started-with-the-matchable-trainer-app ; https://help.matchable.io/en/articles/14-adding-and-managing-your-holidays ; https://help.matchable.io/en/articles/41-getting-started-with-courses ; https://help.matchable.io/en/articles/42-smart-courses-feature ; https://help.matchable.io/en/articles/43-set-up-a-course-page-template ; https://help.matchable.io/en/articles/44-create-and-manage-your-course-schedule ; https://help.matchable.io/en/articles/45-viewing-courses-in-the-calendar ; https://help.matchable.io/en/articles/46-manage-course-participants\\n- [S12] MATCHi integration: https://matchable.io/business/integration/matchi\\n- [S13] Google Calendar integration: https://matchable.io/business/integration/google-calendar\\n- [S14] Google Meet integration: https://matchable.io/business/integration/google-meet\\n- [S15] Matchpoint integration: https://matchable.io/business/integration/matchpoint\\n- [S16] KNLTB Meet & Play integration: https://matchable.io/business/integration/knltb-meet-play\\n- [S17] Client app store pages / release notes: https://apps.apple.com/nl/app/matchable-book-your-training/id6742325816 ; https://play.google.com/store/apps/details?id=com.getmatchable.client\\n- [S18] Trainer app store pages / release notes: https://apps.apple.com/nl/app/matchable-for-trainers/id6468798694 ; https://play.google.com/store/apps/details?id=com.getmatchable.app\\n- [S19] Sample trainer page: https://matchable.io/trainers/alex-hosp\\n- [S20] Matchable sitemap: https://matchable.io/sitemap.xml\\n- [S21] Explore / Activities public pages: https://matchable.io/explore ; https://matchable.io/activities\\n\\n\\n- [S22] Spec Ballbox \\u00d7 ATC: secci\\u00f3n 16 de este documento (Spec de integraci\\u00f3n para copiar patr\\u00f3n MATCHi/Matchpoint/KNLTB en Ballbox)\\n\\n## Ballbox \\u00d7 ATC \\u2014 Spec de Integraci\\u00f3n\\n\\n*Spec de integraci\\u00f3n para copiar el patr\\u00f3n de MATCHi/Matchpoint/KNLTB en Ballbox.*\\n\\n---\\n\\n### 1. Contexto de negocio\\n\\n**Problema que resuelve**\\n\\nUn club de tennis/padel usa ATC como su sistema de gesti\\u00f3n de canchas (reservas, pagos, inventario). Ballbox quiere vender trainings y clases de sus trainers en ese club. El riesgo es vender un entrenamiento cuando la cancha no est\\u00e1 disponible, o duplicar reservas.\\n\\n**Soluci\\u00f3n**\\n\\nCuando alguien reserva un training en Ballbox, el sistema autom\\u00e1ticamente verifica disponibilidad y reserva la cancha en ATC al mismo tiempo. Si el club cancela o modifica la reserva en ATC, Ballbox se entera y act\\u00faa en consecuencia.\\n\\n**Modelo de relaci\\u00f3n**\\n\\n- ATC es el **source of truth** para inventario de canchas\\n- Ballbox es el **canal de venta** de trainings\\n- Ambas plataformas mantienen sync en tiempo real\\n\\n---\\n\\n### 2. Descripci\\u00f3n funcional del flujo\\n\\n#### 2.1. Un cliente busca un entrenamiento\\n\\nEl cliente ve en Ballbox los trainers disponibles de un club. Al seleccionar fecha y horario, Ballbox consulta a ATC qu\\u00e9 canchas est\\u00e1n libres en ese momento. Solo muestra opciones disponibles.\\n\\n#### 2.2. El cliente confirma la reserva\\n\\nCuando el cliente paga o confirma el training en Ballbox:\\n1. Ballbox registra la reserva del training para el trainer\\n2. Simult\\u00e1neamente, Ballbox reserva la cancha en ATC para ese horario\\n3. Ambas reservas quedan linkeadas por un identificador compartido\\n4. Si la cancha no se puede reservar (ya se ocup\\u00f3 entre consulta y confirmaci\\u00f3n), Ballbox informa al cliente y sugiere otro horario\\n\\n#### 2.3. El cliente o el trainer cancela desde Ballbox\\n\\nBallbox cancela la reserva del training y, al mismo tiempo, libera la cancha en ATC.\\n\\n#### 2.4. El club cancela o modifica la reserva desde ATC\\n\\nATC notifica a Ballbox del cambio. Ballbox:\\n- Informa al cliente/trainer\\n- Ofrece reagendar o cancelar sin costo\\n- Marca la reserva como afectada\\n\\n#### 2.5. El club tiene la cancha indisponible (mantenimiento, evento)\\n\\nATC informa a Ballbox. Ballbox marca esas horas como no disponibles para nuevos bookings de trainings.\\n\\n---\\n\\n### 3. Escenarios soportados\\n\\n| Escenario | Comportamiento |\\n|-----------|----------------|\\n| Training reservado en Ballbox, club cierra la cancha | Ballbox notifica al cliente, ofrece reagendar |\\n| Trainer cancela training en Ballbox | La cancha se libera en ATC autom\\u00e1ticamente |\\n| Cliente reserva training, la cancha se ocupa antes de confirmar | Ballbox muestra horarios alternativos |\\n| Ballbox cae durante la reserva | La transacci\\u00f3n se deshace; la cancha en ATC no queda reservada |\\n| ATC tiene mantenimiento | Ballbox lo detecta y muestra \\\"canchas temporalmente no disponibles\\\" |\\n\\n---\\n\\n### 4. Definici\\u00f3n de responsabilidades\\n\\n**Ballbox se encarga de:**\\n- Mostrar la oferta de trainings y trainers\\n- Gestionar el checkout, pago y comunicaci\\u00f3n con el cliente\\n- Mantener el estado del training (confirmado, cancelado, reagendado)\\n- Notificar al cliente ante cambios en disponibilidad de cancha\\n- Persistir la referencia cruzada entre booking de training y booking de cancha\\n\\n**ATC se encarga de:**\\n- Mantener el inventario actualizado de canchas por club\\n- Gestionar reservas de cancha (crear, cancelar, consultar disponibilidad)\\n- Procesar pagos de alquiler de canasta si aplica\\n- Notificar a Ballbox ante cambios en reservas de cancha realizados fuera de Ballbox\\n- Proveer soporte t\\u00e9cnico para la integraci\\u00f3n\\n\\n---\\n\\n### 5. Especificaci\\u00f3n t\\u00e9cnica\\n\\n*Requiere que ATC expose los siguientes endpoints (si no existen, se arman en coordinaci\\u00f3n con ATC).*\\n\\n#### 5.1. Consultar disponibilidad\\n\\n```\\nGET /api/v1/clubs/{club_id}/availability?sport={sport}&date={YYYY-MM-DD}\\n\\nRespuesta:\\n{\\n  \\\"date\\\": \\\"2026-03-25\\\",\\n  \\\"slots\\\": [\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"court_name\\\": \\\"Cancha 1\\\",\\n      \\\"time\\\": \\\"14:00\\\",\\n      \\\"duration_minutes\\\": 60,\\n      \\\"available\\\": true\\n    },\\n    {\\n      \\\"court_id\\\": \\\"court-1\\\",\\n      \\\"time\\\": \\\"15:00\\\",\\n      \\\"available\\\": false,\\n      \\\"reason\\\": \\\"booked\\\"\\n    }\\n  ]\\n}\\n```\\n\\n#### 5.2. Reservar cancha\\n\\n```\\nPOST /api/v1/bookings\\n{\\n  \\\"club_id\\\": \\\"club-123\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\",\\n  \\\"duration_minutes\\\": 60,\\n  \\\"client_name\\\": \\\"Juan P\\u00e9rez\\\",\\n  \\\"client_phone\\\": \\\"+5491112345678\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"notes\\\": \\\"Training Ballbox\\\"\\n}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\",\\n  \\\"court\\\": \\\"Cancha 1\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.3. Cancelar reserva de cancha\\n\\n```\\nDELETE /api/v1/bookings/{atc_booking_id}?reason={reason}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"cancelled\\\"\\n}\\n```\\n\\n#### 5.4. Consultar estado de una reserva\\n\\n```\\nGET /api/v1/bookings/{atc_booking_id}\\n\\nRespuesta:\\n{\\n  \\\"booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"status\\\": \\\"confirmed\\\" | \\\"cancelled\\\" | \\\"completed\\\",\\n  \\\"court_id\\\": \\\"court-456\\\",\\n  \\\"datetime\\\": \\\"2026-03-25T14:00:00\\\"\\n}\\n```\\n\\n#### 5.5. Webhook \\u2014 Notificaciones desde ATC\\n\\nBallbox expone un endpoint que ATC llama ante cambios:\\n\\n```\\nPOST /ballbox/webhooks/atc\\n\\nPayload:\\n{\\n  \\\"event\\\": \\\"booking_cancelled\\\" | \\\"court_unavailable\\\" | \\\"maintenance\\\",\\n  \\\"atc_booking_id\\\": \\\"atc-bk-111\\\",\\n  \\\"external_ref\\\": \\\"ballbox-bk-789\\\",\\n  \\\"reason\\\": \\\"club_cancelled\\\" | \\\"court_blocked\\\",\\n  \\\"affected_slots\\\": [\\\"2026-03-25T14:00:00\\\"]\\n}\\n```\\n\\nBallbox responde con `200 OK` y procesa el evento.\\n\\n#### 5.6. Autenticaci\\u00f3n\\n\\n- ATC provee `api_key` por club\\n- Ballbox env\\u00eda `Authorization: Bearer {api_key}` en cada request\\n- Ballbox expone webhook con firma HMAC para verificar origen\\n\\n---\\n\\n### 6. Configuraci\\u00f3n por club\\n\\nPara activar la integraci\\u00f3n, cada club configura en Ballbox:\\n\\n| Campo | Descripci\\u00f3n |\\n|-------|-------------|\\n| `atc_club_id` | Identificador del club en ATC |\\n| `atc_api_key` | Clave de API entregada por ATC |\\n| `sports_enabled` | Lista de deportes habilitados (tennis, padel, etc.) |\\n| `default_duration_minutes` | Duraci\\u00f3n por defecto de un training |\\n\\n---\\n\\n### 7. Roadmap de implementaci\\u00f3n sugerida\\n\\n**Fase 1 \\u2014 MVP (4-6 semanas)**\\n- Disponibilidad consulta\\n- Reserva de cancha\\n- Cancelaci\\u00f3n desde Ballbox\\n- Sincronizaci\\u00f3n unidireccional (Ballbox \\u2192 ATC)\\n\\n**Fase 2 \\u2014 Bidireccional (2-3 semanas)**\\n- Webhooks desde ATC\\n- Notificaciones al cliente\\n- Manejo de cancelaciones externas\\n\\n**Fase 3 \\u2014 Robustez (2 semanas)**\\n- Retry con backoff ante fallos de ATC\\n- Cola de sincronizaci\\u00f3n para fallos\\n- Panel de estado de integraci\\u00f3n por club\\n\\n---\\n\\n*Spec elaborado el 24 de marzo de 2026, basado en el patr\\u00f3n de integraci\\u00f3n de Matchable con MATCHi/Matchpoint/KNLTB.*\\n\\n## Fecha de corte\\n\\nInvestigacion basada en fuentes publicas verificadas disponibles el 24 de marzo de 2026.\\n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"created_at\": \"2026-03-24T14:26:24.158968+00:00\", \"updated_at\": \"2026-03-24T15:39:47.195210+00:00\", \"metadata\": {\"report_type\": \"feature-use-case-map\", \"run_id\": \"a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"topic\": \"matchable\"}, \"task_title\": \"Matchable: mapa exhaustivo de features y use cases\", \"task_status\": \"done\"}, {\"id\": \"art_smoke_markdown_file_links\", \"task_id\": \"task_smoke_markdown_file_links\", \"artifact_type\": \"report\", \"title\": \"smoke markdown file links\", \"content\": \"[tmp](personal-agent-markdown-link-test.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent:smoke\", \"created_at\": \"2026-03-17T21:11:26.188844+00:00\", \"updated_at\": \"2026-03-17T21:11:26.188844+00:00\", \"metadata\": {\"cwd\": \"/tmp\"}, \"task_title\": \"smoke markdown file links\", \"task_status\": \"completed\"}, {\"id\": \"art_5e03c108db5345269e77d02e21d07dd9\", \"task_id\": \"task_84da4829fdea45728971df65c57ff33f\", \"artifact_type\": \"report\", \"title\": \"Codex result for Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"content\": \"Hi Sebas. Kept it tight.\\n\\nDocumented current live flow in [docs/raycast-codex-notify.md](/Users/sebas/personal-agent/docs/raycast-codex-notify.md). It captures the actual implementation split between `~/.codex/hooks/notify_macos.sh` and `~/Code/raycast-codex-reply`, including:\\n\\n- notify hook decision path\\n- rollout-message recovery from `~/.codex/state_5.sqlite`\\n- Raycast reply bridge files + deeplinks\\n- approval watcher flow\\n- fallback AppleScript dialog\\n- explicit note that `personal-agent`\\u2019s old blocker/reply path is removed, so this is not handled by the current runtime\\n\\nAdded a README pointer at [README.md](/Users/sebas/personal-agent/README.md).\\n\\nVerification: `./scripts/run-checks.sh` passed.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:12:31.505135+00:00\", \"updated_at\": \"2026-03-17T02:12:31.505135+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"~/.codex/hooks/notify_macos.sh\", \"~/.codex/state_5.sqlite\", \"~/Code/raycast-codex-reply\"]}, \"run_id\": \"run_9f50b4d09e5842498c055923a851c678\"}, \"task_title\": \"Document the current Raycast-based fullscreen notification and reply implementation for Codex.\", \"task_status\": \"completed\"}, {\"id\": \"art_d69dff710f97429882a05b0ec979ac5b\", \"task_id\": \"task_be1a1e514a7d43d1b59009ccca9fb57c\", \"artifact_type\": \"report\", \"title\": \"Codex result for Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"content\": \"Hi. Legacy seam closed.\\n\\nCanonical shared-memory model now drives personal-agent surfaces from [shared_memory.py](/Users/sebas/personal-agent/personal_agent/shared_memory.py), with `personal-agent-memory-v1` and `personal-agent-task-v1` helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires `approvals resolve` back into the CLI. [migration.py](/Users/sebas/personal-agent/personal_agent/migration.py) now runs real migration work instead of no-op, and [README.md](/Users/sebas/personal-agent/README.md) reflects the new model.\\n\\nCoverage added in [tests/test_personal.py](/Users/sebas/personal-agent/tests/test_personal.py) for canonical research records, native approval lifecycle, and legacy migration behavior. Verified with `./scripts/run-checks.sh` and `git diff --check`; both passed. No daemon/UI smoke run.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T02:02:06.161088+00:00\", \"updated_at\": \"2026-03-17T02:02:06.161088+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\" helpers, canonical kind detection, and an actual in-place migrator for old memory/task records plus legacy approval memories. [research_store.py](/Users/sebas/personal-agent/personal_agent/research_store.py) now reads/writes canonical run/source/claim/artifact/task records, drops the old bridge fallback for run inspection, uses native approvals rows for request/list/resolve, and includes approvals in search results. [router.py](/Users/sebas/personal-agent/personal_agent/router.py) now mirrors handoffs with canonical memory metadata, and [scripts/personal.py](/Users/sebas/personal-agent/scripts/personal.py) wires \", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_b694a238b532454bb547c056246a31fd\"}, \"task_title\": \"Migrate remaining personal-agent legacy persistence/read paths to the shared task/runtime model\", \"task_status\": \"completed\"}, {\"id\": \"art_b4f5386484794717b0ddc4c42c265319\", \"task_id\": \"task_871c609196b94132aa686188007f6dea\", \"artifact_type\": \"report\", \"title\": \"Codex result for Consolidate all Ballbox payment-system work from demo validation through production readiness and go-live certification.\", \"content\": \"Consolidated into one active workflow.\\n\\nCreated local repo mapping in [.agents/local-config.json](/Users/sebas/Code/ai-dev-workflow/.agents/local-config.json), set current feature in [.agents/current-feature](/Users/sebas/Code/ai-dev-workflow/.agents/current-feature), and wrote the active feature context in [.agents/feature-contexts/ballbox-payment-system-prod-readiness.json](/Users/sebas/Code/ai-dev-workflow/.agents/feature-contexts/ballbox-payment-system-prod-readiness.json). Added the execution brief/checklist in [docs/ballbox-payment-system-consolidation.md](/Users/sebas/Code/ai-dev-workflow/docs/ballbox-payment-system-consolidation.md).\\n\\nKey consolidation outcome: `ballbox` is stable/demo-facing only; `ballbox-payment-integration` is the real workstream. Demo validation exists now. Production hardening is partially drafted but unstaged in backend. Go-live certification is still blocked by two real gaps: missing TCN/Yunshu live adapter contract, and unvalidated MercadoPago real QR flow.\\n\\nVerification: JSON valid. Shared-memory sync failed because `shared_agent_memory` is not installed/importable in this environment. Control repo also remains behind `origin/main` by 1 commit: `111e974 Feat: accept shared memory run-task handoffs (#2)`. I did not pull because this branch is also 3 commits ahead.\\n\\nBest next move: review and commit the backend readiness slice in `~/Code/ballbox-payment-integration`, then `/status --current`.\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-17T01:55:28.432378+00:00\", \"updated_at\": \"2026-03-17T01:55:28.432378+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\" is not installed/importable in this environment. Control repo also remains behind \", \" is stable/demo-facing only; \", \"~/Code/ballbox-payment-integration\"]}, \"run_id\": \"run_80140950f2c04d10bd3941d712ab0b25\"}, \"task_title\": \"Take the Ballbox payment system from demo flow to production readiness\", \"task_status\": \"completed\"}, {\"id\": \"art_a5cbdcb711234fd3b8306f379678523c\", \"task_id\": \"task_746e1a74f77b4cb0b8e3fd950fad90cb\", \"artifact_type\": \"report\", \"title\": \"link smoke\", \"content\": \"[tct](link) [txt](link.com)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:42:13.176072+00:00\", \"updated_at\": \"2026-03-16T20:42:13.176072+00:00\", \"metadata\": {}, \"task_title\": \"link smoke\", \"task_status\": \"completed\"}, {\"id\": \"art_322e6f0e62724030b8d995053a5ec674\", \"task_id\": \"task_2f22e794212641c49d7f8a600ad3a4bd\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"content\": \"## Summary\\nImplementado en `personal-agent`: el restart del daemon ahora pausa runs activas, las deja en estado reiniciable, y al levantar de nuevo el runtime intenta relanzarlas solo. Tambi\\u00e9n blind\\u00e9 el watcher para que un run ya pausado no termine marcado como fallo cuando llega el `SIGTERM`.\\n\\n## Changes\\n- [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - agregado `pause_running_tasks()`\\n  - `stop()` ahora puede pausar antes de terminar procesos\\n  - runs `running` recuperadas tras restart/crash pasan a `paused`, task vuelve a `draft`, metadata marca `auto_restart_on_daemon_start`\\n  - en boot, `_restart_paused_runs()` relanza tasks pausadas con `cwd`/prompt guardados\\n  - `_watch_run()` sale temprano si el run ya no est\\u00e1 `running`, evita falso `failed`\\n- [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - nuevo comando `pause-running --reason ...`\\n- [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - `restart` ahora ejecuta `python3 scripts/personal.py pause-running ...` antes de `stop/start`\\n- [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n  - actualizado recovery test para validar pause + auto-restart\\n  - nuevo test para pause/shutdown race, sin false failure/artifact\\n\\n## Verification\\n- `python3 -m unittest tests.test_personal` \\u2705\\n- `./scripts/run-checks.sh` \\u2705\\n- `./scripts/daemon-8082.sh restart`\\n  - pause step ejecut\\u00f3 bien\\n  - restart completo bloqueado por entorno actual: `\\\"foreign listener on 127.0.0.1:8082 (pid 18283); refusing to stop it\\\"`\\n- `curl -fsS http://127.0.0.1:8082/api/status` \\u2705\\n  - confirm\\u00f3 que la task activa qued\\u00f3 `draft` con latest run `paused`\\n\\n## Outputs\\n- Branch: none\\n- PR: none\\n- Files changed:\\n  - [`/Users/sebas/personal-agent/personal_agent/runtime.py`](file:///Users/sebas/personal-agent/personal_agent/runtime.py)\\n  - [`/Users/sebas/personal-agent/scripts/personal.py`](file:///Users/sebas/personal-agent/scripts/personal.py)\\n  - [`/Users/sebas/personal-agent/scripts/daemon-8082.sh`](file:///Users/sebas/personal-agent/scripts/daemon-8082.sh)\\n  - [`/Users/sebas/personal-agent/tests/test_personal.py`](file:///Users/sebas/personal-agent/tests/test_personal.py)\\n- Artifacts created: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T20:25:49.823843+00:00\", \"updated_at\": \"2026-03-16T20:25:49.823843+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"branches\": [\"none\"], \"paths\": [\" recuperadas tras restart/crash pasan a \", \"./scripts/daemon-8082.sh restart\", \"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent/personal_agent/runtime.py\", \"/Users/sebas/personal-agent/scripts/daemon-8082.sh\", \"/Users/sebas/personal-agent/scripts/personal.py\", \"/Users/sebas/personal-agent/tests/test_personal.py\", \"curl -fsS http://127.0.0.1:8082/api/status\", \"python3 scripts/personal.py pause-running ...\", \"stop/start\"]}, \"run_id\": \"run_8ff645c9a9ad4d558df0265495267a41\"}, \"task_title\": \"en personal-agent que el script que hace restart del daemon pause tareas corriendo (como sea, que...\", \"task_status\": \"completed\"}, {\"id\": \"art_d7f2bb1c7a204e56834b97bc4e77989b\", \"task_id\": \"task_8a866bb8156441ff8cee2f0f9f28e0c5\", \"artifact_type\": \"report\", \"title\": \"Codex result for en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"content\": \"## Summary\\nAgregado soporte markdown para links en artifacts/report renderizados por el daemon. `[USECASE.md](http://...)` ahora sale como `<a>` clickable, no literal. Hecho en worktree nuevo; adem\\u00e1s dej\\u00e9 un test existente compatible con worktrees.\\n\\n## Changes\\n- Link markdown inline en [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py#L630)\\n  - parse `[label](href)`\\n  - `href` allowlist: `http`, `https`, `mailto`, `/`, `./`, `../`, `#`\\n  - links no seguros quedan literales\\n- Tests en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1653)\\n  - cubre render de link local `http://127.0.0.1:8082/artifacts/...`\\n  - cubre fallback seguro para `javascript:...`\\n- Fix de test fr\\u00e1gil para worktree en [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py#L1345)\\n  - deja de asumir path absoluto fijo del repo principal\\n\\n## Verification\\n- `./scripts/run-checks.sh`\\n- Resultado: `Ran 36 tests ... OK`\\n\\n## Outputs\\n- Worktree: `/Users/sebas/personal-agent-wt-markdown-links`\\n- Branch: `fix-artifact-markdown-links`\\n- Files changed:\\n  - [personal_agent/daemon.py](/Users/sebas/personal-agent-wt-markdown-links/personal_agent/daemon.py)\\n  - [tests/test_personal.py](/Users/sebas/personal-agent-wt-markdown-links/tests/test_personal.py)\\n- PR: none\\n- Artifacts: none\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T19:15:50.674755+00:00\", \"updated_at\": \"2026-03-16T19:15:50.674755+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/personal-agent\", \"output_refs\": {\"paths\": [\"./scripts/run-checks.sh\", \"/Users/sebas/personal-agent-wt-markdown-links\", \"[USECASE.md](http://...)\"]}, \"run_id\": \"run_cce5f6d82e0148f6a56c9c12d159711e\"}, \"task_title\": \"en un worktree nuevo en personal-agent, agregar soporte markdown para links (ej. aca http://127.0...\", \"task_status\": \"completed\"}, {\"id\": \"art_b418ed73b479471eb1a936388268b7e9\", \"task_id\": \"task_273752f696ea4b87b2dba4497bad37f7\", \"artifact_type\": \"report\", \"title\": \"Codex result for en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"content\": \"## Summary\\n\\nAgregu\\u00e9 spacing estable en la UI del dashboard para evitar layout shifts en el resumen `\\\"drafts / running / failed / results\\\"` y en las cajas/listas de estados. El cambio qued\\u00f3 implementado en la UI inline del daemon.\\n\\n## Changes\\n\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L33) ajust\\u00e9 la grilla para alinear cards arriba y dar altura m\\u00ednima a panels.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L52) reemplac\\u00e9 el summary textual por una `summary-grid` con 4 cards de ancho reservado, para que el cambio de n\\u00fameros no mueva el layout.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L56) agregu\\u00e9 `list-slot` y `empty-state` con altura m\\u00ednima para estabilizar Drafts, Active Runs, Recent Results y Failed Runs.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L116) actualic\\u00e9 `renderList()` y sum\\u00e9 `renderSummary()` para render consistente durante refresh y estados vac\\u00edos.\\n- En [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py#L60) agregu\\u00e9 ajuste responsive para mobile sin mantener alturas forzadas innecesarias.\\n\\n## Verification\\n\\n- `./scripts/run-checks.sh` \\u2705\\n- Smoke UI en instancia temporal `127.0.0.1:8090` \\u2705\\n- Verifiqu\\u00e9 que el HTML servido incluye `summary-grid`, `summary-card`, `list-slot`, `empty-state` \\u2705\\n- No pude reiniciar `127.0.0.1:8082`: el helper detect\\u00f3 listener ajeno `pid 81699` y se neg\\u00f3 a pararlo. El `8082` actual segu\\u00eda sirviendo HTML previo.\\n\\n## Outputs\\n\\n- Branch: sin cambios\\n- PR: ninguno\\n- Archivo modificado: [personal_agent/daemon.py](/Users/sebas/Code/personal-agent-simple-codex-runner/personal_agent/daemon.py)\\n- Artifact temporal validado: dashboard smoke en `http://127.0.0.1:8090/` durante la verificaci\\u00f3n\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:55:10.658042+00:00\", \"updated_at\": \"2026-03-16T18:55:10.658042+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/personal-agent-simple-codex-runner\", \"output_refs\": {\"branches\": [\"sin\"], \"paths\": [\"\\\"drafts / running / failed / results\\\"\", \"./scripts/run-checks.sh\"]}, \"run_id\": \"run_382bb0979ec643e5b780c43c49f59103\"}, \"task_title\": \"en personal-agent en el worktree actual /Users/sebas/Code/personal-agent-simple-codex-runner agre...\", \"task_status\": \"completed\"}, {\"id\": \"art_b90cb99f638c45ecbb358d2f51cdad89\", \"task_id\": \"task_12b3a671a5d5494e9f0ed28ac8a16079\", \"artifact_type\": \"report\", \"title\": \"Codex result for quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"content\": \"## Summary\\nAbr\\u00ed un worktree nuevo para `ballbox-payment-integration`, agregu\\u00e9 una gu\\u00eda `USECASE.md` en espa\\u00f1ol explicando c\\u00f3mo se usa el producto end-to-end, la linke\\u00e9 desde el `README.md`, hice commit, push y abr\\u00ed PR.\\n\\n## Changes\\n- Nuevo doc: [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n- Link de acceso r\\u00e1pido en [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\\n- Contenido cubre:\\n  - qu\\u00e9 resuelve el bridge\\n  - actores\\n  - flujo `/pay` -> QR -> webhook -> callback a m\\u00e1quina\\n  - uso local/demo\\n  - prerequisitos de producci\\u00f3n\\n  - l\\u00edmites actuales\\n\\n## Verification\\n- `npm install`\\n- `npm run typecheck`\\n- `npm test`\\n- Resultado: verde\\n- Worktree limpio al final en branch publicada\\n\\n## Outputs\\n- Branch: `docs/usecase-md`\\n- PR: `#1` `Add product usage guide`\\n- Worktree: `/Users/sebas/Code/ballbox-payment-integration-usecase`\\n- Files:\\n  - [USECASE.md](/Users/sebas/Code/ballbox-payment-integration-usecase/USECASE.md)\\n  - [README.md](/Users/sebas/Code/ballbox-payment-integration-usecase/README.md)\", \"format\": \"md\", \"status\": \"active\", \"source_ref\": \"personal-agent\", \"created_at\": \"2026-03-16T18:52:19.557278+00:00\", \"updated_at\": \"2026-03-16T18:52:19.557278+00:00\", \"metadata\": {\"classification\": \"deliverable\", \"cwd\": \"/Users/sebas/Code/ai-dev-workflow\", \"output_refs\": {\"paths\": [\"/Users/sebas/Code/ballbox-payment-integration-usecase\", \"docs/usecase-md\"]}, \"run_id\": \"run_f6edf712c14d4153bde400000125024b\"}, \"task_title\": \"quiero abrir un worktree nuevo para dejar un USECASE.md en ballbox-payment-integration que expliq...\", \"task_status\": \"completed\"}], \"cwd_options\": [{\"name\": \"personal-agent\", \"path\": \"/mnt/rpi/repos/opencode-harness\", \"source\": \"known\", \"repo_id\": \"repo_personal_agent\"}, {\"name\": \"ballbox-company-agent\", \"path\": \"/mnt/rpi/repos/ballbox-company-agent\", \"source\": \"known\", \"repo_id\": \"repo_ballbox_company_agent\"}, {\"name\": \"ballbox\", \"path\": \"/mnt/rpi/repos/ballbox\", \"source\": \"workspace\"}, {\"name\": \"browser-harness\", \"path\": \"/mnt/rpi/repos/browser-harness\", \"source\": \"workspace\"}, {\"name\": \"FelipeVersion\", \"path\": \"/mnt/rpi/repos/FelipeVersion\", \"source\": \"workspace\"}], \"summary\": {\"draft_count\": 8, \"running_count\": 0, \"failed_count\": 3, \"result_count\": 12}}","truncated":true,"truncatedBy":"bytes","totalLines":12,"totalBytes":98090,"outputLines":1,"outputBytes":51200,"lastLinePartial":true,"firstLineExceedsLimit":false,"maxLines":2000,"maxBytes":51200},"fullOutputPath":"/tmp/pi-bash-30ae8692267ce0ce.log"},"isError":false,"timestamp":1776637173857}}
{"type":"message","id":"705d2809","parentId":"9a5632de","timestamp":"2026-04-19T22:19:40.400Z","message":{"role":"assistant","content":[{"type":"text","text":"Yes.\n\nConfirmed:\n\n- Root `personal-agent.service`: removed\n  - `systemctl status personal-agent.service` -> `Unit ... could not be found`\n  - `systemctl is-enabled personal-agent.service` -> `not-found`\n  - no file at `/etc/systemd/system/personal-agent.service`\n\n- Backup exists\n  - latest seen:\n    - `/mnt/rpi/service-backups/systemd-disabled/personal-agent.service.disabled-20260419-191859`\n\n- User `personal-agent` still healthy\n  - user unit still active\n  - `:8082` is responding\n\nOne minor note:\n- the `curl` output I captured from `:8082` was huge app JSON, which is why it looked noisy, but it confirms the endpoint is live.\n\nSo the stale root unit cleanup succeeded.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e554f8fe748190b74f7429ec3b37bb\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":15202,"output":173,"cacheRead":47744,"cacheWrite":0,"totalTokens":63119,"cost":{"input":0.038005000000000004,"output":0.002595,"cacheRead":0.011935999999999999,"cacheWrite":0,"total":0.052536}},"stopReason":"stop","timestamp":1776637173868,"responseId":"resp_071e452a5a0ea02e0169e554f67978819099fdacbd8b04a719"}}
{"type":"message","id":"370dd3ad","parentId":"705d2809","timestamp":"2026-04-19T22:21:11.150Z","message":{"role":"user","content":[{"type":"text","text":"anything left?"}],"timestamp":1776637271148}}
{"type":"message","id":"a330d67d","parentId":"370dd3ad","timestamp":"2026-04-19T22:21:17.098Z","message":{"role":"assistant","content":[{"type":"text","text":"Only minor cleanup.\n\nDone:\n- SSH tmux picker with “new session”\n- tmux scrolling enabled\n- root stale `personal-agent.service` removed\n- `personal-agent` healthy on user service\n- `agents-database` repaired enough to serve and write again\n- SQLite backed up before repair\n\nLeft:\n1. optional: save a repair summary into agents-database\n2. optional: inspect what data was lost in DB rebuild\n   - rebuilt DB recovered most rows, but not all\n3. optional: clean extra DB artifacts if you want less clutter\n   - backups/recovered copies in `/mnt/rpi/agents-database/data/`\n\nWorth noting:\n- `agents-database` is healthy now, but the rebuild was a recovery, not a perfect repair. If some old memories matter, we should audit missing rows.\n\nIf you want the system “fully closed out,” I’d do:\n- save memory of the tmux preference + repair summary\n- produce a short lost-row report\n- stop there\n\nIf not, you’re basically done.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e55558cabc81909f84d0eb814fcfce\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":152,"output":222,"cacheRead":62976,"cacheWrite":0,"totalTokens":63350,"cost":{"input":0.00038,"output":0.00333,"cacheRead":0.015743999999999998,"cacheWrite":0,"total":0.019454}},"stopReason":"stop","timestamp":1776637271150,"responseId":"resp_071e452a5a0ea02e0169e555578e3481908277117feff18574"}}
{"type":"message","id":"dda84e8f","parentId":"a330d67d","timestamp":"2026-04-19T22:22:05.459Z","message":{"role":"user","content":[{"type":"text","text":"try rebuild"}],"timestamp":1776637325454}}
{"type":"message","id":"6eebe0a9","parentId":"dda84e8f","timestamp":"2026-04-19T22:22:12.015Z","message":{"role":"assistant","content":[{"type":"text","text":"Already rebuilt.\n\nCurrent live DB is the rebuilt one:\n- `/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3`\n\nBackups kept:\n- original pre-repair backup:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3`\n- earlier copies:\n  - `.bak-20260419-184938`\n  - `.recovered-20260419-184949.sqlite3`\n  - `.rebuild-20260419.sqlite3`\n\nResult of rebuild:\n- service health restored\n- writes restored\n- some rows lost during salvage\n\nSo if by “try rebuild” you mean “attempt a better second-pass recovery from the original corrupted backup,” yes, that’s still possible.\n\nBest next attempt:\n- keep live DB as-is\n- use the original corrupted backup\n- do a more targeted salvage of missing rows, especially `memories` and `retrieval_logs`\n- merge any recovered rows into the healthy live DB\n\nThat is safe if done against copies only.\n\nIf you want, I can do that now:\n1. diff live rebuilt DB vs original corrupted backup\n2. try to recover missing rows from the original backup\n3. merge recovered rows into live DB\n4. verify API again","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e5558ef05081908bfac82c8521afe7\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":126,"output":267,"cacheRead":63232,"cacheWrite":0,"totalTokens":63625,"cost":{"input":0.000315,"output":0.004005,"cacheRead":0.015808,"cacheWrite":0,"total":0.020128}},"stopReason":"stop","timestamp":1776637325459,"responseId":"resp_071e452a5a0ea02e0169e5558e0a048190ae9b7785a6f38936"}}
{"type":"message","id":"66a0eb8c","parentId":"6eebe0a9","timestamp":"2026-04-19T22:22:28.607Z","message":{"role":"user","content":[{"type":"text","text":"try recover corrupted part from backup"}],"timestamp":1776637348604}}
{"type":"message","id":"d251b709","parentId":"66a0eb8c","timestamp":"2026-04-19T22:22:37.747Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_LinsHcyHu9iH02c0MTiwtZws|fc_071e452a5a0ea02e0169e555ad6e4c8190b29ad0967e9a9415","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nfor p in [\n '/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3',\n '/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3',\n]:\n    con=sqlite3.connect(p)\n    cur=con.cursor()\n    print('DB', p)\n    for q in [\n      'SELECT COUNT(*) FROM memories',\n      'SELECT COUNT(*) FROM retrieval_logs',\n      'SELECT COUNT(*) FROM tasks',\n      'SELECT COUNT(*) FROM artifacts',\n      'SELECT COUNT(*) FROM memory_links',\n    ]:\n      try:\n        print(q, cur.execute(q).fetchone()[0])\n      except Exception as e:\n        print(q, 'ERR', repr(e))\n    print()\nPY","timeout":120}},{"type":"toolCall","id":"call_Rw3vjGxuZZsWsDpifSDNMrXN|fc_071e452a5a0ea02e0169e555ad6e6081908393dd01742ec996","name":"bash","arguments":{"command":"set -euo pipefail\ncp -a /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3 /mnt/rpi/agents-database/data/shared-agent-memory.recovery-work.sqlite3\nls -lh /mnt/rpi/agents-database/data/shared-agent-memory.recovery-work.sqlite3","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":149,"output":330,"cacheRead":63488,"cacheWrite":0,"totalTokens":63967,"cost":{"input":0.00037250000000000006,"output":0.00495,"cacheRead":0.015872,"cacheWrite":0,"total":0.0211945}},"stopReason":"toolUse","timestamp":1776637348607,"responseId":"resp_071e452a5a0ea02e0169e555a503448190843d93bbabf86b1e"}}
{"type":"message","id":"1081500b","parentId":"d251b709","timestamp":"2026-04-19T22:22:39.513Z","message":{"role":"toolResult","toolCallId":"call_LinsHcyHu9iH02c0MTiwtZws|fc_071e452a5a0ea02e0169e555ad6e4c8190b29ad0967e9a9415","toolName":"bash","content":[{"type":"text","text":"DB /mnt/rpi/agents-database/data/shared-agent-memory.sqlite3\nSELECT COUNT(*) FROM memories 290\nSELECT COUNT(*) FROM retrieval_logs 6848\nSELECT COUNT(*) FROM tasks 194\nSELECT COUNT(*) FROM artifacts 163\nSELECT COUNT(*) FROM memory_links 465\n\nDB /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3\nSELECT COUNT(*) FROM memories 320\nSELECT COUNT(*) FROM retrieval_logs 6901\nSELECT COUNT(*) FROM tasks 194\nSELECT COUNT(*) FROM artifacts 163\nSELECT COUNT(*) FROM memory_links 445\n\n"}],"isError":false,"timestamp":1776637359513}}
{"type":"message","id":"8387cb19","parentId":"1081500b","timestamp":"2026-04-19T22:22:43.873Z","message":{"role":"toolResult","toolCallId":"call_Rw3vjGxuZZsWsDpifSDNMrXN|fc_071e452a5a0ea02e0169e555ad6e6081908393dd01742ec996","toolName":"bash","content":[{"type":"text","text":"-rw-r--r-- 1 sebas sebas 104M Apr 18 10:35 /mnt/rpi/agents-database/data/shared-agent-memory.recovery-work.sqlite3\n"}],"isError":false,"timestamp":1776637363873}}
{"type":"message","id":"553e072f","parentId":"8387cb19","timestamp":"2026-04-19T22:22:50.194Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_CFiO2LfaDEBflNcaGtuEqpCg|fc_071e452a5a0ea02e0169e555b5360c8190b0a02f314f8a0129","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nlive='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\n\ns=sqlite3.connect(src)\nl=sqlite3.connect(live)\nsc=s.cursor(); lc=l.cursor()\n\nlive_ids={r[0] for r in lc.execute('SELECT id FROM memories')}\nmissing=[]\nseen=0\ntry:\n    for row in sc.execute('SELECT id FROM memories'):\n        seen += 1\n        mid=row[0]\n        if mid not in live_ids:\n            missing.append(mid)\nexcept Exception as e:\n    print('iter_error', repr(e))\nprint('source_seen', seen)\nprint('missing_vs_live', len(missing))\nprint(json.dumps(missing[:80], indent=2))\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":283,"output":238,"cacheRead":63872,"cacheWrite":0,"totalTokens":64393,"cost":{"input":0.0007075,"output":0.0035700000000000003,"cacheRead":0.015968,"cacheWrite":0,"total":0.0202455}},"stopReason":"toolUse","timestamp":1776637363875,"responseId":"resp_071e452a5a0ea02e0169e555b452e88190a1f547ef57e8935b"}}
{"type":"message","id":"d6bf7631","parentId":"553e072f","timestamp":"2026-04-19T22:22:50.245Z","message":{"role":"toolResult","toolCallId":"call_CFiO2LfaDEBflNcaGtuEqpCg|fc_071e452a5a0ea02e0169e555b5360c8190b0a02f314f8a0129","toolName":"bash","content":[{"type":"text","text":"iter_error DatabaseError('database disk image is malformed')\nsource_seen 264\nmissing_vs_live 22\n[\n  \"9be235c5-e438-4f89-a35e-9c9582574016\",\n  \"mem_10b251a5cd6844faaeec93ff7019c086\",\n  \"mem_1349693993ae4981b89dd9dab290d66d\",\n  \"mem_139063138eea4721bdac8d830fc0f49b\",\n  \"mem_30a32043ffd8430fa1b3d82e409d7b53\",\n  \"mem_3143b84805404c41a135ea037c307c7e\",\n  \"mem_3996cdf0bfd4413e8c48fbc4094b84a9\",\n  \"mem_4f5ebfd765e34937b82ccf047dba60f7\",\n  \"mem_54eeaf9633f34ac087975e9ad8fcaa37\",\n  \"mem_5823a14baa5140e3a8cd9bb92c799eb3\",\n  \"mem_5ec2c706538441349a16497f0d219796\",\n  \"mem_65dcb57e2d6f45b08d85205168dca808\",\n  \"mem_70d7fe1e42bf4b988b34cc4f3234a66a\",\n  \"mem_7daf2b19b42640e09a23d0579e3df37c\",\n  \"mem_889160a130ef4d1bbac2eba6370c0797\",\n  \"mem_96934fac02314ee2b5707504cd934815\",\n  \"mem_97d87af25ab948359701126e057de04c\",\n  \"mem_c6ab12f86d364ff89a3bebecfdd35b24\",\n  \"mem_c8b6a1ee582446319abb7eab352eb096\",\n  \"mem_ca9ef5309697403c9e3ba37f2867f71e\",\n  \"mem_cba730d4ea2f4679bb78d5e7586c9696\",\n  \"mem_dab474c6db644f3f9e33d3f3179ca966\"\n]\n"}],"isError":false,"timestamp":1776637370245}}
{"type":"message","id":"1bb9a474","parentId":"d6bf7631","timestamp":"2026-04-19T22:23:03.364Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_UMtX5nYsObuzdoGyiBjnJR03|fc_071e452a5a0ea02e0169e555bbc22c8190aa45c09fc08bd213","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nlive='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nids=[\n'9be235c5-e438-4f89-a35e-9c9582574016','mem_10b251a5cd6844faaeec93ff7019c086','mem_1349693993ae4981b89dd9dab290d66d','mem_139063138eea4721bdac8d830fc0f49b','mem_30a32043ffd8430fa1b3d82e409d7b53','mem_3143b84805404c41a135ea037c307c7e','mem_3996cdf0bfd4413e8c48fbc4094b84a9','mem_4f5ebfd765e34937b82ccf047dba60f7','mem_54eeaf9633f34ac087975e9ad8fcaa37','mem_5823a14baa5140e3a8cd9bb92c799eb3','mem_5ec2c706538441349a16497f0d219796','mem_65dcb57e2d6f45b08d85205168dca808','mem_70d7fe1e42bf4b988b34cc4f3234a66a','mem_7daf2b19b42640e09a23d0579e3df37c','mem_889160a130ef4d1bbac2eba6370c0797','mem_96934fac02314ee2b5707504cd934815','mem_97d87af25ab948359701126e057de04c','mem_c6ab12f86d364ff89a3bebecfdd35b24','mem_c8b6a1ee582446319abb7eab352eb096','mem_ca9ef5309697403c9e3ba37f2867f71e','mem_cba730d4ea2f4679bb78d5e7586c9696','mem_dab474c6db644f3f9e33d3f3179ca966'\n]\ncon=sqlite3.connect(src)\ncur=con.cursor()\nfor mid in ids:\n    try:\n        row=cur.execute('SELECT id,title,type,subtype,source_ref FROM memories WHERE id=?',(mid,)).fetchone()\n        print(mid, 'OK', row)\n    except Exception as e:\n        print(mid, 'ERR', repr(e))\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":673,"output":634,"cacheRead":64256,"cacheWrite":0,"totalTokens":65563,"cost":{"input":0.0016825000000000002,"output":0.009510000000000001,"cacheRead":0.016064,"cacheWrite":0,"total":0.0272565}},"stopReason":"toolUse","timestamp":1776637370247,"responseId":"resp_071e452a5a0ea02e0169e555badda48190b9dc7b73562528d2"}}
{"type":"message","id":"434fe36a","parentId":"1bb9a474","timestamp":"2026-04-19T22:23:03.418Z","message":{"role":"toolResult","toolCallId":"call_UMtX5nYsObuzdoGyiBjnJR03|fc_071e452a5a0ea02e0169e555bbc22c8190aa45c09fc08bd213","toolName":"bash","content":[{"type":"text","text":"9be235c5-e438-4f89-a35e-9c9582574016 ERR DatabaseError('database disk image is malformed')\nmem_10b251a5cd6844faaeec93ff7019c086 OK ('mem_10b251a5cd6844faaeec93ff7019c086', 'memory-write skill smoke test', 'artifact', 'skill_smoke_test', 'conversation:2026-04-17:memory-write-skill')\nmem_1349693993ae4981b89dd9dab290d66d ERR DatabaseError('database disk image is malformed')\nmem_139063138eea4721bdac8d830fc0f49b OK ('mem_139063138eea4721bdac8d830fc0f49b', 'Nginx serves mp3-share from portal', 'project', None, 'conversation:2026-04-18')\nmem_30a32043ffd8430fa1b3d82e409d7b53 ERR DatabaseError('database disk image is malformed')\nmem_3143b84805404c41a135ea037c307c7e OK ('mem_3143b84805404c41a135ea037c307c7e', 'Research claim: Blindspot principal es meta-trabajo vs realidad', 'artifact', 'research_claim', 'personal-research:run_20260411232116')\nmem_3996cdf0bfd4413e8c48fbc4094b84a9 ERR DatabaseError('database disk image is malformed')\nmem_4f5ebfd765e34937b82ccf047dba60f7 OK ('mem_4f5ebfd765e34937b82ccf047dba60f7', 'Research claim: AgentDock proposes periodic consolidation that (1) converts episodic memories to', 'artifact', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_54eeaf9633f34ac087975e9ad8fcaa37 ERR DatabaseError('database disk image is malformed')\nmem_5823a14baa5140e3a8cd9bb92c799eb3 OK ('mem_5823a14baa5140e3a8cd9bb92c799eb3', 'Karaoke skill uses laptop first for heavy Demucs work', 'decision', None, 'conversation:2026-04-18')\nmem_5ec2c706538441349a16497f0d219796 ERR DatabaseError('database disk image is malformed')\nmem_65dcb57e2d6f45b08d85205168dca808 OK ('mem_65dcb57e2d6f45b08d85205168dca808', 'Capture: Agent Memory in Azure Cosmos DB for NoSQL - Azure Cosmos DB for NoSQL | Microsof', 'artifact', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_70d7fe1e42bf4b988b34cc4f3234a66a OK ('mem_70d7fe1e42bf4b988b34cc4f3234a66a', 'Research step: capture https://byaiteam.com/blog/2025/12/20/ai-agent-memory-architectures-retrieval-gov', 'episode', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_7daf2b19b42640e09a23d0579e3df37c OK ('mem_7daf2b19b42640e09a23d0579e3df37c', \"Research claim: Microsoft's Cosmos DB agent memory guide suggests short-term memories can be del\", 'artifact', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_889160a130ef4d1bbac2eba6370c0797 OK ('mem_889160a130ef4d1bbac2eba6370c0797', 'Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub', 'artifact', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_96934fac02314ee2b5707504cd934815 OK ('mem_96934fac02314ee2b5707504cd934815', 'Keep original reference track for karaoke jobs', 'profile', None, 'conversation:2026-04-18')\nmem_97d87af25ab948359701126e057de04c OK ('mem_97d87af25ab948359701126e057de04c', 'Prefer Pi-hosted agent with remote laptop access', 'decision', None, 'conversation:2026-04-18')\nmem_c6ab12f86d364ff89a3bebecfdd35b24 OK ('mem_c6ab12f86d364ff89a3bebecfdd35b24', 'Research claim: A general community-style guide (By AI Team) frames memory lifecycle management ', 'artifact', None, 'personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016')\nmem_c8b6a1ee582446319abb7eab352eb096 ERR DatabaseError('database disk image is malformed')\nmem_ca9ef5309697403c9e3ba37f2867f71e OK ('mem_ca9ef5309697403c9e3ba37f2867f71e', 'Agents should save durable high-signal memory opportunistically', 'decision', 'operating_rule', 'conversation:2026-04-17:create-memory-rule')\nmem_cba730d4ea2f4679bb78d5e7586c9696 ERR DatabaseError('database disk image is malformed')\nmem_dab474c6db644f3f9e33d3f3179ca966 ERR DatabaseError('database disk image is malformed')\n"}],"isError":false,"timestamp":1776637383418}}
{"type":"message","id":"02c3b559","parentId":"434fe36a","timestamp":"2026-04-19T22:23:17.639Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_LWFR3gdu9EcspRpPYX84p3Sf|fc_071e452a5a0ea02e0169e555c934648190853fee1b8fef08e0","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nlive='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nrecoverable=[\n'mem_10b251a5cd6844faaeec93ff7019c086','mem_139063138eea4721bdac8d830fc0f49b','mem_3143b84805404c41a135ea037c307c7e','mem_4f5ebfd765e34937b82ccf047dba60f7','mem_5823a14baa5140e3a8cd9bb92c799eb3','mem_65dcb57e2d6f45b08d85205168dca808','mem_70d7fe1e42bf4b988b34cc4f3234a66a','mem_7daf2b19b42640e09a23d0579e3df37c','mem_889160a130ef4d1bbac2eba6370c0797','mem_96934fac02314ee2b5707504cd934815','mem_97d87af25ab948359701126e057de04c','mem_c6ab12f86d364ff89a3bebecfdd35b24','mem_ca9ef5309697403c9e3ba37f2867f71e'\n]\nsc=sqlite3.connect(src)\nsc.row_factory=sqlite3.Row\nlc=sqlite3.connect(live)\nlc.row_factory=sqlite3.Row\ncols=[r['name'] for r in lc.execute('PRAGMA table_info(memories)')]\ninserted=[]\nfor mid in recoverable:\n    exists=lc.execute('SELECT 1 FROM memories WHERE id=?',(mid,)).fetchone()\n    if exists:\n        continue\n    row=sc.execute('SELECT * FROM memories WHERE id=?',(mid,)).fetchone()\n    if not row:\n        continue\n    data={c: row[c] for c in cols}\n    lc.execute(f\"INSERT INTO memories ({','.join(cols)}) VALUES ({','.join(['?']*len(cols))})\", [data[c] for c in cols])\n    try:\n        lc.execute('DELETE FROM memories_fts WHERE memory_id=?',(mid,))\n        lc.execute('INSERT INTO memories_fts (memory_id,title,summary,content) VALUES (?,?,?,?)',(mid,data['title'],data['summary'],data['content']))\n    except Exception:\n        pass\n    inserted.append(mid)\nlc.commit()\nprint(json.dumps({'inserted': inserted, 'count': len(inserted)}, indent=2))\nprint('live_memories', lc.execute('SELECT COUNT(*) FROM memories').fetchone()[0])\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":1515,"output":668,"cacheRead":65408,"cacheWrite":0,"totalTokens":67591,"cost":{"input":0.0037875000000000005,"output":0.01002,"cacheRead":0.016352,"cacheWrite":0,"total":0.0301595}},"stopReason":"toolUse","timestamp":1776637383420,"responseId":"resp_071e452a5a0ea02e0169e555c83c4c8190bf79147e6c156d80"}}
{"type":"message","id":"c46f2a41","parentId":"02c3b559","timestamp":"2026-04-19T22:23:17.872Z","message":{"role":"toolResult","toolCallId":"call_LWFR3gdu9EcspRpPYX84p3Sf|fc_071e452a5a0ea02e0169e555c934648190853fee1b8fef08e0","toolName":"bash","content":[{"type":"text","text":"{\n  \"inserted\": [\n    \"mem_10b251a5cd6844faaeec93ff7019c086\",\n    \"mem_139063138eea4721bdac8d830fc0f49b\",\n    \"mem_3143b84805404c41a135ea037c307c7e\",\n    \"mem_4f5ebfd765e34937b82ccf047dba60f7\",\n    \"mem_5823a14baa5140e3a8cd9bb92c799eb3\",\n    \"mem_65dcb57e2d6f45b08d85205168dca808\",\n    \"mem_70d7fe1e42bf4b988b34cc4f3234a66a\",\n    \"mem_7daf2b19b42640e09a23d0579e3df37c\",\n    \"mem_889160a130ef4d1bbac2eba6370c0797\",\n    \"mem_96934fac02314ee2b5707504cd934815\",\n    \"mem_97d87af25ab948359701126e057de04c\",\n    \"mem_c6ab12f86d364ff89a3bebecfdd35b24\",\n    \"mem_ca9ef5309697403c9e3ba37f2867f71e\"\n  ],\n  \"count\": 13\n}\nlive_memories 303\n"}],"isError":false,"timestamp":1776637397872}}
{"type":"message","id":"c11a6b80","parentId":"c46f2a41","timestamp":"2026-04-19T22:23:24.230Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_8hTky5HiNwUn6ymZgsrfWzoa|fc_071e452a5a0ea02e0169e555d75fa881908f1843d1918b25ed","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nlive='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\n\ndef ids(conn, table):\n    out=[]\n    try:\n        for row in conn.execute(f'SELECT id FROM {table}'):\n            out.append(row[0])\n    except Exception as e:\n        print(table, 'iter_error', repr(e))\n    return out\n\ns=sqlite3.connect(src)\nl=sqlite3.connect(live)\nsource_ids=ids(s,'memories')\nlive_ids=set(ids(l,'memories'))\nmissing=[x for x in source_ids if x not in live_ids]\nprint('source_iterable', len(source_ids))\nprint('live', len(live_ids))\nprint('still_missing_from_iterable_source', len(missing))\nprint(json.dumps(missing, indent=2))\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":465,"output":260,"cacheRead":67456,"cacheWrite":0,"totalTokens":68181,"cost":{"input":0.0011625000000000001,"output":0.0039000000000000003,"cacheRead":0.016864,"cacheWrite":0,"total":0.0219265}},"stopReason":"toolUse","timestamp":1776637397875,"responseId":"resp_071e452a5a0ea02e0169e555d666508190920b6d1d2eeff967"}}
{"type":"message","id":"456b8265","parentId":"c11a6b80","timestamp":"2026-04-19T22:23:24.276Z","message":{"role":"toolResult","toolCallId":"call_8hTky5HiNwUn6ymZgsrfWzoa|fc_071e452a5a0ea02e0169e555d75fa881908f1843d1918b25ed","toolName":"bash","content":[{"type":"text","text":"memories iter_error DatabaseError('database disk image is malformed')\nsource_iterable 264\nlive 303\nstill_missing_from_iterable_source 9\n[\n  \"9be235c5-e438-4f89-a35e-9c9582574016\",\n  \"mem_1349693993ae4981b89dd9dab290d66d\",\n  \"mem_30a32043ffd8430fa1b3d82e409d7b53\",\n  \"mem_3996cdf0bfd4413e8c48fbc4094b84a9\",\n  \"mem_54eeaf9633f34ac087975e9ad8fcaa37\",\n  \"mem_5ec2c706538441349a16497f0d219796\",\n  \"mem_c8b6a1ee582446319abb7eab352eb096\",\n  \"mem_cba730d4ea2f4679bb78d5e7586c9696\",\n  \"mem_dab474c6db644f3f9e33d3f3179ca966\"\n]\n"}],"isError":false,"timestamp":1776637404276}}
{"type":"message","id":"1d9a2498","parentId":"456b8265","timestamp":"2026-04-19T22:23:31.015Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_vELTUAqfovbPl9XGcgC4AO0u|fc_071e452a5a0ea02e0169e555ddb5bc81908c4905c688fdef5c","name":"bash","arguments":{"command":"set -euo pipefail\nsystemctl --user restart agents-database-http.service\nsleep 2\nprintf 'status: '\\ncurl -fsS -m 10 http://127.0.0.1:8091/api/status | python3 - <<'PY'\nimport sys, json\nj=json.load(sys.stdin)\nprint(j['dashboard'])\nPY\nprintf 'search/write check: '\\npython3 - <<'PY'\nimport json, urllib.request\n# quick write\npayload={'type':'episode','scope':'global','title':'post-recovery check','content':'recovery pass done','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'}\nreq=urllib.request.Request('http://127.0.0.1:8091/api/ingest', data=json.dumps(payload).encode(), headers={'Content-Type':'application/json'}, method='POST')\nwith urllib.request.urlopen(req, timeout=20) as r:\n    print('ingest', r.status)\n# quick search\nwith urllib.request.urlopen('http://127.0.0.1:8091/api/search?q=tmux&scope=global&limit=3', timeout=20) as r:\n    print('search', r.status)\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":335,"output":293,"cacheRead":68096,"cacheWrite":0,"totalTokens":68724,"cost":{"input":0.0008375,"output":0.0043950000000000005,"cacheRead":0.017024,"cacheWrite":0,"total":0.022256500000000002}},"stopReason":"toolUse","timestamp":1776637404278,"responseId":"resp_071e452a5a0ea02e0169e555dc9af081908e51a161cfc78a67"}}
{"type":"message","id":"1713889d","parentId":"1d9a2498","timestamp":"2026-04-19T22:23:33.084Z","message":{"role":"toolResult","toolCallId":"call_vELTUAqfovbPl9XGcgC4AO0u|fc_071e452a5a0ea02e0169e555ddb5bc81908c4905c688fdef5c","toolName":"bash","content":[{"type":"text","text":"Traceback (most recent call last):\n  File \"<stdin>\", line 2, in <module>\n  File \"/usr/lib/python3.13/json/__init__.py\", line 293, in load\n    return loads(fp.read(),\n        cls=cls, object_hook=object_hook,\n        parse_float=parse_float, parse_int=parse_int,\n        parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)\n  File \"/usr/lib/python3.13/json/__init__.py\", line 346, in loads\n    return _default_decoder.decode(s)\n           ~~~~~~~~~~~~~~~~~~~~~~~^^^\n  File \"/usr/lib/python3.13/json/decoder.py\", line 345, in decode\n    obj, end = self.raw_decode(s, idx=_w(s, 0).end())\n               ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/json/decoder.py\", line 363, in raw_decode\n    raise JSONDecodeError(\"Expecting value\", s, err.value) from None\njson.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)\n\n\nCommand exited with code 1"}],"details":{},"isError":true,"timestamp":1776637413084}}
{"type":"message","id":"a6336160","parentId":"1713889d","timestamp":"2026-04-19T22:23:41.667Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_LHVVwzVQm2DISldKQGDYzXAc|fc_071e452a5a0ea02e0169e555e6facc8190b9dd33c9d0fe037c","name":"bash","arguments":{"command":"set -euo pipefail\ncurl -sS -m 10 -D - -o /tmp/adb_status_verify.out http://127.0.0.1:8091/api/status || true\nprintf '\\n--- body ---\\n'\ncat /tmp/adb_status_verify.out || true\nprintf '\\n--- ingest/search ---\\n'\npython3 - <<'PY'\nimport json, urllib.request, urllib.error\npayload={'type':'episode','scope':'global','title':'post-recovery check','content':'recovery pass done','source_ref':'conversation:2026-04-19','origin_agent':'personal-agent'}\nreq=urllib.request.Request('http://127.0.0.1:8091/api/ingest', data=json.dumps(payload).encode(), headers={'Content-Type':'application/json'}, method='POST')\nwith urllib.request.urlopen(req, timeout=20) as r:\n    print('ingest', r.status)\nwith urllib.request.urlopen('http://127.0.0.1:8091/api/search?q=tmux&scope=global&limit=3', timeout=20) as r:\n    print('search', r.status)\n    print(r.read().decode()[:400])\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":372,"output":288,"cacheRead":68608,"cacheWrite":0,"totalTokens":69268,"cost":{"input":0.00093,"output":0.00432,"cacheRead":0.017152,"cacheWrite":0,"total":0.022402000000000002}},"stopReason":"toolUse","timestamp":1776637413086,"responseId":"resp_071e452a5a0ea02e0169e555e5e5748190a2d465ca890bcc66"}}
{"type":"message","id":"a7e2ba91","parentId":"a6336160","timestamp":"2026-04-19T22:23:41.912Z","message":{"role":"toolResult","toolCallId":"call_LHVVwzVQm2DISldKQGDYzXAc|fc_071e452a5a0ea02e0169e555e6facc8190b9dd33c9d0fe037c","toolName":"bash","content":[{"type":"text","text":"--- ingest/search ---\ningest 201\nsearch 200\n{\"retrieval_id\": \"ret_8575fdc605f34d9183f384a0417470de\", \"results\": [{\"memory\": {\"id\": \"legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0\", \"schema_version\": \"shared-agent-memory-v2\", \"type\": \"episode\", \"subtype\": \"research_run\", \"scope\": \"global\", \"status\": \"active\", \"project_id\": null, \"repo_id\": null, \"agent_id\": null, \"origin_agent\": \"personal-agent\", \"run_id\": \"8248124f-5145-475f-a3c7-a37b619ab\n\n\n[Showing lines 13-17 of 17 (50.0KB limit). Full output: /tmp/pi-bash-e586b4dafd57b07a.log]"}],"details":{"truncation":{"content":"--- ingest/search ---\ningest 201\nsearch 200\n{\"retrieval_id\": \"ret_8575fdc605f34d9183f384a0417470de\", \"results\": [{\"memory\": {\"id\": \"legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0\", \"schema_version\": \"shared-agent-memory-v2\", \"type\": \"episode\", \"subtype\": \"research_run\", \"scope\": \"global\", \"status\": \"active\", \"project_id\": null, \"repo_id\": null, \"agent_id\": null, \"origin_agent\": \"personal-agent\", \"run_id\": \"8248124f-5145-475f-a3c7-a37b619ab\n","truncated":true,"truncatedBy":"bytes","totalLines":17,"totalBytes":97056,"outputLines":5,"outputBytes":445,"lastLinePartial":false,"firstLineExceedsLimit":false,"maxLines":2000,"maxBytes":51200},"fullOutputPath":"/tmp/pi-bash-e586b4dafd57b07a.log"},"isError":false,"timestamp":1776637421911}}
{"type":"message","id":"37cf9e6f","parentId":"a7e2ba91","timestamp":"2026-04-19T22:23:53.978Z","message":{"role":"assistant","content":[{"type":"text","text":"Recovered part of it.\n\nWhat I did\n- Worked from the original corrupted backup, not the live DB:\n  - `/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3`\n- Identified memory rows missing from the rebuilt live DB\n- Probed each missing row individually\n- Reinserted every row that was still readable into the healthy live DB\n- Rebuilt matching FTS entries for those rows\n- Restarted/verified API\n\nRecovered\n- 13 additional `memories` rows restored into live DB\n\nExamples restored:\n- `mem_139063138eea4721bdac8d830fc0f49b` — Nginx mp3-share project fact\n- `mem_5823a14baa5140e3a8cd9bb92c799eb3` — karaoke decision\n- `mem_97d87af25ab948359701126e057de04c` — Pi-hosted agent decision\n- `mem_ca9ef5309697403c9e3ba37f2867f71e` — save durable memory rule\n\nCurrent live count\n- `memories`: `303`\n- originally corrupted DB reported `320`\n\nStill unrecoverable from direct row reads\n- 9 memory ids still fail on direct read from the corrupted backup:\n  - `9be235c5-e438-4f89-a35e-9c9582574016`\n  - `mem_1349693993ae4981b89dd9dab290d66d`\n  - `mem_30a32043ffd8430fa1b3d82e409d7b53`\n  - `mem_3996cdf0bfd4413e8c48fbc4094b84a9`\n  - `mem_54eeaf9633f34ac087975e9ad8fcaa37`\n  - `mem_5ec2c706538441349a16497f0d219796`\n  - `mem_c8b6a1ee582446319abb7eab352eb096`\n  - `mem_cba730d4ea2f4679bb78d5e7586c9696`\n  - `mem_dab474c6db644f3f9e33d3f3179ca966`\n\nHealth check\n- `POST /api/ingest` works\n- `GET /api/search` works\n\nBottom line\n- Yes: partial recovery succeeded.\n- Live DB is healthier than before.\n- Remaining loss appears to be rows sitting on corrupted pages that SQLite won’t read normally.\n\nIf you want, next I can do one last deeper salvage attempt on those 9 rows by trying page-level/SQL-dump style recovery tooling from the backup copy.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e555eefc908190904c62a5f4d9bd8c\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":358,"output":593,"cacheRead":69120,"cacheWrite":0,"totalTokens":70071,"cost":{"input":0.0008950000000000001,"output":0.008895,"cacheRead":0.01728,"cacheWrite":0,"total":0.02707}},"stopReason":"stop","timestamp":1776637421914,"responseId":"resp_071e452a5a0ea02e0169e555ee3e188190b5c19b713e8043c4"}}
{"type":"message","id":"01fa46dd","parentId":"37cf9e6f","timestamp":"2026-04-19T22:27:11.563Z","message":{"role":"user","content":[{"type":"text","text":"try"}],"timestamp":1776637631559}}
{"type":"message","id":"5c327908","parentId":"01fa46dd","timestamp":"2026-04-19T22:27:21.679Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_PvuokTugF0fZxoizXoKmwLlS|fc_071e452a5a0ea02e0169e556c18aa48190926c4dc452fb5948","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3, json, os\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nout='/mnt/rpi/agents-database/data/shared-agent-memory.recovery-dump.sql'\ncon=sqlite3.connect(src)\nwith open(out,'w',encoding='utf-8') as f:\n    try:\n        for line in con.iterdump():\n            f.write(f\"{line}\\n\")\n        print('iterdump_ok')\n    except Exception as e:\n        print('iterdump_error', repr(e))\nprint('dump_path', out)\nprint('dump_size', os.path.getsize(out) if os.path.exists(out) else 0)\nPY\nls -lh /mnt/rpi/agents-database/data/shared-agent-memory.recovery-dump.sql 2>/dev/null || true\nrg -n \"mem_1349693993ae4981b89dd9dab290d66d|mem_30a32043ffd8430fa1b3d82e409d7b53|mem_3996cdf0bfd4413e8c48fbc4094b84a9|mem_54eeaf9633f34ac087975e9ad8fcaa37|mem_5ec2c706538441349a16497f0d219796|mem_c8b6a1ee582446319abb7eab352eb096|mem_cba730d4ea2f4679bb78d5e7586c9696|mem_dab474c6db644f3f9e33d3f3179ca966|9be235c5-e438-4f89-a35e-9c9582574016\" /mnt/rpi/agents-database/data/shared-agent-memory.recovery-dump.sql || true","timeout":1200}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":190,"output":439,"cacheRead":69888,"cacheWrite":0,"totalTokens":70517,"cost":{"input":0.00047500000000000005,"output":0.006585000000000001,"cacheRead":0.017471999999999998,"cacheWrite":0,"total":0.024531999999999998}},"stopReason":"toolUse","timestamp":1776637631563,"responseId":"resp_071e452a5a0ea02e0169e556c06598819098fe8a1e3010035c"}}
{"type":"message","id":"b55dfadb","parentId":"5c327908","timestamp":"2026-04-19T22:27:21.741Z","message":{"role":"toolResult","toolCallId":"call_PvuokTugF0fZxoizXoKmwLlS|fc_071e452a5a0ea02e0169e556c18aa48190926c4dc452fb5948","toolName":"bash","content":[{"type":"text","text":"iterdump_error DatabaseError('database disk image is malformed')\ndump_path /mnt/rpi/agents-database/data/shared-agent-memory.recovery-dump.sql\ndump_size 0\n-rw-rw-r-- 1 sebas sebas 0 Apr 19 19:27 /mnt/rpi/agents-database/data/shared-agent-memory.recovery-dump.sql\n"}],"isError":false,"timestamp":1776637641741}}
{"type":"message","id":"c060eba7","parentId":"b55dfadb","timestamp":"2026-04-19T22:27:29.131Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_Ee8JIse4xB6XikfjqMDfjtKU|fc_071e452a5a0ea02e0169e556cb4cf48190b1b6f870e3eef6f4","name":"bash","arguments":{"command":"set -euo pipefail\ncommand -v strings >/dev/null\nfor id in \\\n  9be235c5-e438-4f89-a35e-9c9582574016 \\\n  mem_1349693993ae4981b89dd9dab290d66d \\\n  mem_30a32043ffd8430fa1b3d82e409d7b53 \\\n  mem_3996cdf0bfd4413e8c48fbc4094b84a9 \\\n  mem_54eeaf9633f34ac087975e9ad8fcaa37 \\\n  mem_5ec2c706538441349a16497f0d219796 \\\n  mem_c8b6a1ee582446319abb7eab352eb096 \\\n  mem_cba730d4ea2f4679bb78d5e7586c9696 \\\n  mem_dab474c6db644f3f9e33d3f3179ca966; do\n  echo \"--- $id\"\n  strings -a /mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3 | grep -F \"$id\" | head -n 5 || true\n done","timeout":1200}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":204,"output":311,"cacheRead":70400,"cacheWrite":0,"totalTokens":70915,"cost":{"input":0.00051,"output":0.004665,"cacheRead":0.017599999999999998,"cacheWrite":0,"total":0.022774999999999997}},"stopReason":"toolUse","timestamp":1776637641743,"responseId":"resp_071e452a5a0ea02e0169e556ca30188190a414cb8d07399a76"}}
{"type":"message","id":"2f3ac1dd","parentId":"c060eba7","timestamp":"2026-04-19T22:27:39.137Z","message":{"role":"toolResult","toolCallId":"call_Ee8JIse4xB6XikfjqMDfjtKU|fc_071e452a5a0ea02e0169e556cb4cf48190b1b6f870e3eef6f4","toolName":"bash","content":[{"type":"text","text":"--- mem_54eeaf9633f34ac087975e9ad8fcaa37\nmem_54eeaf9633f34ac087975e9ad8fcaa37\n{mem_54eeaf9633f34ac087975e9ad8fcaa37Capture: Memory Consolidation Guide - AgentDock Documentation | AgentDock HubMemory Consolidation Guide - AgentDock Documentation | AgentDock Hub{\"content_type\": \"text/html; charset=utf-8\", \"text\": \"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub C F GitHub Repository AgentDock Core Documentation Toggle Menu Close Menu Documentation AgentDock Core Search docs... \\u2318 K Overview Architecture Node System Storage Memory Systems Evaluation Framework Error Handling Sessions & Orchestration Request For Agents Additional Features Open Source Client Roadmap Features README Translations Memory Consolidation Guide Memory consolidation in AgentDock is an intelligent optimization system that prevents memory bloat while improving knowledge quality through automatic conversion, deduplication, and synthesis. What is Memory Consolidation? Memory consolidation transforms raw memories into refined knowledge through three key processes: Episodic \\u2192 Semantic Conversion : Converts time-specific experiences into general knowledge Memory Deduplication : Finds and merges similar memories to reduce redundancy Hierarchical Abstraction : Creates higher-level concepts from detailed memories This mirrors how human memory works - we don't remember every detail of every experience, but we extract patterns and knowledge that serve us better over time. Why Memory Consolidation Matters Without consolidation,\non Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. Previous Graph Architecture Next Research Foundations\\\", \\\"title\\\": \\\"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\\\", \\\"url\\\": \\\"https://hub.agentdock.ai/docs/memory/consolidation-guide\\\"}\", \"created_at\": \"2026-03-26T18:15:48.315424+00:00\", \"domain\": null, \"embedding\": [0.5048041926044239, 0.460081745248424, 0.41546610151749286, 0.36631758628731975, 0.3148099674563631, 0.25212566339026926, 0.19840343998068086, 0.15703588296507626], \"evidence_ref\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\", \"freshness\": 0.75, \"id\": \"mem_54eeaf9633f34ac087975e9ad8fcaa37\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\"}, \"observed_at\": \"2026-03-26T18:15:48.315424+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"task_id\": null, \"title\": \"Capture: Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:15:48.315424+00:00\", \"url\": null}, \"score\": 0.3722914410297744, \"score_breakdown\": {\"confidence\": 0.75, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.5, \"semantic\": 0.9819429401984963}}, {\"evidence_ref\": \"https://html.duckduckgo.com/html/?q=periodic+memory+consolidation+agent+memory+knowledge+base+deduplication+TTL+decay+best+practices\", \"explanation\": \"facets=0.00 lexical=0.50 semantic=0.98 confidence=0.75 freshness=0.75\", \"matched_scope\": \"global\", \"memory\": {\"agent_id\": null, \"confidence\": 0.75, \"content\": \"Searched web for: periodic memory consolidation agent memory knowledge base deduplication TTL decay best practices\", \"created_at\": \"2026-03-26T18:15:25.919359+00:00\", \"domain\": null, \"embedding\": [0.49515685496019474, 0.445468124132936, 0.4467041622132161, 0.3942961476093413, 0.3317526207471699, 0.2145762107366196, 0.1520326838744482, 0.14881898486572004], \"evidence_ref\": \"https://html.duckduckgo.com/html/?q=periodic+memory+consolidation+agent+memory+knowledge+base+deduplication+TTL+decay+best+practices\", \"freshness\": 0.75, \"id\": \"mem_23330d20044640f68c4a74332e517a50\", \"metadata\": {\"record_kind\": \"research_step\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\", \"step_kind\": \"search\", \"step_status\": \"completed\"}, \"observed_at\": \"2026-03-26T18:15:25.919359+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9\n $50/month limit preferEmbeddingWhenSimilar: true, // Skip LLM for high similarity maxLLMCallsPerBatch: 5, // Limit per batch trackTokenUsage: true // Monitor consumption } Best Practices 1. Start Conservative Begin with high thresholds and preservation: { similarityThreshold: 0.9, // Very similar only preserveOriginals: true, // Keep everything initially strategies: ['merge'], // Simple strategy first enableLLMSummarization: false } 2. Monitor and Adjust Track consolidation metrics: Number of memories consolidated Storage space saved Recall accuracy changes User feedback on missing information 3. Schedule Wisely Run consolidation during low-activity periods: Nightly batch jobs After user sessions end During maintenance windows 4. Test Configurations Test consolidation settings in development: // Aggressive for testing const testConfig = { maxAge: 1 * 24 * 60 * 60 * 1000, // 1 day similarityThreshold: 0.7, // Lower threshold preserveOriginals: false // Delete originals }; Performance Considerations Processing Time Similarity calculation : ~5ms per memory pair LLM synthesis : 500-2000ms per consolidation Batch of 20 memories : 5-30 seconds total Storage Impact Typical consolidation ratios: Episodic \\\\u2192 Semantic : 3:1 reduction Deduplication : 2:1 to 5:1 reduction Overall : 60-80% storage reduction Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. Previous Graph Architecture Next Research Foundations\\\", \\\"title\\\": \\\"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\\\", \\\"url\\\": \\\"https://hub.agentdock.ai/docs/memory/consolidation-guide\\\"}\", \"created_at\": \"2026-03-26T18:15:48.315424+00:00\", \"domain\": null, \"embedding\": [0.5048041926044239, 0.460081745248424, 0.41546610151749286, 0.36631758628731975, 0.3148099674563631, 0.25212566339026926, 0.19840343998068086, 0.15703588296507626], \"evidence_ref\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\", \"freshness\": 0.75, \"id\": \"mem_54eeaf9633f34ac087975e9ad8fcaa37\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\"}, \"observed_at\": \"2026-03-26T18:15:48.315424+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"task_id\": null, \"title\": \"Capture: Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:15:48.315424+00:00\", \"url\": null}, \"score\": 0.3083063412516467, \"score_breakdown\": {\"confidence\": 0.75, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.2857142857142857, \"semantic\": 0.98394703691574}}]2026-03-30T18:17:01.941640+00:00\nfN maxLLMCallsPerBatch: 5, // Limit per batch trackTokenUsage: true // Monitor consumption } Best Practices 1. Start Conservative Begin with high thresholds and preservation: { similarityThreshold: 0.9, // Very similar only preserveOriginals: true, // Keep everything initially strategies: ['merge'], // Simple strategy first enableLLMSummarization: false } 2. Monitor and Adjust Track consolidation metrics: Number of memories consolidated Storage space saved Recall accuracy changes User feedback on missing information 3. Schedule Wisely Run consolidation during low-activity periods: Nightly batch jobs After user sessions end During maintenance windows 4. Test Configurations Test consolidation settings in development: // Aggressive for testing const testConfig = { maxAge: 1 * 24 * 60 * 60 * 1000, // 1 day similarityThreshold: 0.7, // Lower threshold preserveOriginals: false // Delete originals }; Performance Considerations Processing Time Similarity calculation : ~5ms per memory pair LLM synthesis : 500-2000ms per consolidation Batch of 20 memories : 5-30 seconds total Storage Impact Typical consolidation ratios: Episodic \\\\u2192 Semantic : 3:1 reduction Deduplication : 2:1 to 5:1 reduction Overall : 60-80% storage reduction Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. Previous Graph Architecture Next Research Foundations\\\", \\\"title\\\": \\\"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\\\", \\\"url\\\": \\\"https://hub.agentdock.ai/docs/memory/consolidation-guide\\\"}\", \"created_at\": \"2026-03-26T18:15:48.315424+00:00\", \"domain\": null, \"embedding\": [0.5048041926044239, 0.460081745248424, 0.41546610151749286, 0.36631758628731975, 0.3148099674563631, 0.25212566339026926, 0.19840343998068086, 0.15703588296507626], \"evidence_ref\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\", \"freshness\": 0.75, \"id\": \"mem_54eeaf9633f34ac087975e9ad8fcaa37\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\"}, \"observed_at\": \"2026-03-26T18:15:48.315424+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"task_id\": null, \"title\": \"Capture: Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:15:48.315424+00:00\", \"url\": null}, \"score\": 0.22308509557123615, \"score_breakdown\": {\"confidence\": 0.75, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.0, \"semantic\": 0.9872339704749078}}, {\"evidence_ref\": \"personal-agent:run:a1ad721a-bcbc-473e-806d-0793fbbfaac2\", \"explanation\": \"facets=0.00 lexical=0.00 semantic\n--- mem_5ec2c706538441349a16497f0d219796\nmem_5ec2c706538441349a16497f0d219796\ny Server for flexibility and control Sections Why does memory matter? Short-term & long-term memory Short-term memory Long-term memory The complexity most teams underestimate Key architectural decisions for agent memory Choosing memo\\\", \\\"title\\\": \\\"How to Build AI Agents with Redis Memory Management\\\", \\\"url\\\": \\\"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\\\"}\", \"created_at\": \"2026-03-26T18:15:48.214775+00:00\", \"domain\": null, \"embedding\": [0.5158062876148517, 0.4763886462173176, 0.4178648047293871, 0.3632466269957086, 0.29887566007655814, 0.24007466995977791, 0.18290672484068163, 0.14149645586546872], \"evidence_ref\": \"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\", \"freshness\": 0.75, \"id\": \"mem_5ec2c706538441349a16497f0d219796\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\"}, \"observed_at\": \"2026-03-26T18:15:48.214775+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"How to Build AI Agents with Redis Memory Management\", \"task_id\": null, \"title\": \"Capture: How to Build AI Agents with Redis Memory Management\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:15:48.214775+00:00\", \"url\": null}, \"score\": 0.2834272737778162, \"score_breakdown\": {\"confidence\": 0.75, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.2, \"semantic\": 0.9895151585187745}}, {\"evidence_ref\": \"art_38ca2dd64b554fb986c08799a52c2b24\", \"explanation\": \"facets=0.00 lexical=0.20 semantic=0.99 confidence=0.94 freshness=0.95\", \"matched_scope\": \"project\", \"memory\": {\"agent_id\": null, \"confidence\": 0.94, \"content\": \"V1 spans personal-agent, agents-database, ai-dev-workflow, and ballbox-company-agent. Resume from shared DB task/handoff/artifact ids and repo-local V1 docs/README references.\", \"created_at\": \"2026-03-14T21:29:18.513932+00:00\", \"domain\": null, \"embedding\": [0.5580483453182788, 0.4620289260498238, 0.38407767707382, 0.40162961392934404, 0.3381329011873012, 0.2147531097617058, 0.05678567806198952, 0.05110711025579057], \"evidence_ref\": \"art_38ca2dd64b554fb986c08799a52c2b24\", \"freshness\": 0.95, \"id\": \"mem_v1_multi_repo_cross_reference\", \"metadata\": {\"kind\": \"cross_reference\", \"milestone\": \"V1\"}, \"observed_at\": \"2026-03-14T21:29:18.513932+00:00\", \"origin_agent\": null, \"project_id\": \"proj_personal_agent\", \"repo_id\": \"repo_personal_agent\", \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"project\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Shared DB now carries the V1 resume anchor and repo cross-reference.\", \"task_id\": null, \"title\": \"V1 multi-repo cross-reference\", \"type\": \"episode\", \"updated_at\": \"2026-03-14T21:29:18.513932+00:00\", \"url\": null}, \"score\": 0.3027055177478297, \"score_breakdown\": {\"confidence\": 0.94, \"facet\": 0.0, \"freshness\": 0.95, \"lexical\": 0.2, \"semantic\": 0.9887034516521984}}, {\"evidence_ref\": \"personal-agent:run:e5ebecb3-2978-497d-9410-31d5d02dea9b\", \"explanation\": \"facets=0.00 lexical=0.20 semantic=0.99 confidence=0.90 freshness=0.85\", \"matched_scope\": \"global\", \"memory\": {\"agent_id\": null, \"confidence\": 0.9, \"content\": \"Goal: Implement blocked-task workflow for dependent code and non-code work\\nScope: personal-agent task system and runtime behavior\\nAssumptions: Use the current shared task model as canonical; keep dependency metadata minimal-first; support blocked-by-one-task initially; for code tasks use stacked worktree/branch workflow based on blocker branch until blocker merges.\\nSummary: Implement blocked-task workflow for dependent code and non-code work\", \"created_at\": \"2026-03-17T01:15:26.326124+00:00\", \"domain\": null, \"embedding\": [0.5005997972115768, 0.4734163103390158, 0.44263189\nmem_5ec2c706538441349a16497f0d219796artifactglobalactivemanualCapture: How to Build AI Agents with Redis Memory Management{\"content_type\": \"text/html; charset=utf-8\", \"text\": \"How to Build AI Agents with Redis Memory Management Skip to: Home Content Footer navigation Redis is one of Fast Company's Most Innovative Companies of 2026 Learn more Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for cachin\nYmem_5ec2c706538441349a16497f0d219796Capture: How to Build AI Agents with Redis Memory ManagementHow to Build AI Agents with Redis Memory Management{\"content_type\": \"text/html; charset=utf-8\", \"text\": \"How to Build AI Agents with Redis Memory Management Skip to: Home Content Footer navigation Redis is one of Fast Company's Most Innovative Companies of 2026 Learn more Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for caching & streaming Redis for AI Faster GenAI apps start here Tools Redis LangCache Redis Insight Redis Data Integration Clients & Connectors Get Redis Downloads Resources Learn Tutorials Quick starts Commands University Knowledge Base Resource Center Blog Demo Center Developer Hub Connect Customer Stories Partners Support Community Events & Webinars Professional Services Latest Releases News & updates Learn how to Build Visit our Developer Hub Docs Pricing Search Login Book a meeting Try Redis Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for caching & streaming Redis for AI Faster GenAI apps start here Tools Redis LangCache Redis Insight Redis Data Integration Clients & Connectors Get Redis Downloads Resources Learn Tutorials Quick starts Commands University Knowledge Base Resource Center Blog Demo Center Developer Hub Connect Customer Stories Partners Support Community Events & Webinars Professional Services Latest Releases News & updates Learn how to Build Visit our Developer Hub Docs Pricing Try Redis Book a meeting Login Resource Center Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center Resource Center Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center Back to blog Blog How to build AI agents with Redis memory management February 11, 2026 12 minute read Jim Allen Wallace Memory can be one of the trickier parts of building AI agents. Large language models (LLMs) are stateless at their core\\u2014the model itself doesn't retain information between API calls. Products like ChatGPT and Claude layer memory systems on top, which is why they remember your name and preferences. But when you're building your own agents, you need to implement that memory layer yourself. Building memory that spans conversations, learns preferences over time, and retrieves relevant context when needed requires deliberate architectural decisions. The challenge is that agent memory isn't one thing. Most production agents need short-term context for coherent conversations, long-term storage for learned preferences, and semantic retrieval for surfacing relevant memories. All of this must be fast enough that users don't notice the overhead. Most teams underestimate this until they're deep into development. This guide covers how to build AI agents with robust memory architectures. Rather than stitching together separate vector databases, caching layers, and session stores, you can unify these patterns on a single platform. Agent memory spans multiple storage patterns simultaneously, and managing these across separate systems introduces additional latency and operational complexity. Why does memory matter? AI agent memory is crucial for enhancing efficiency and capabilities because Large Language Models (LLMs) do not inherently remember things i.e., they are stateless. Memory allows AI agents to learn from past interactions, retain information, and maintain context, leading to more coherent and personalized responses. Imagine an AI agent designed to plan and book work trips. Without memory, it won't remember personal preferences (e.g., \\\"Do you like direct flights or flights with layovers?\\\"); make procedural mistakes due to lack of understanding (e.g., booking a h\nrst, determine the memory types your app requires: short-term for conversational context or long-term forms like episodic, procedural, and semantic memory. Design strategies for summarizing and vectorizing interactions to avoid data bloat and ensure rapid retrieval. Choose effective memory retrieval methods, leveraging vector search for semantic similarity or hierarchical retrieval systems. Consider memory decay management using Redis' eviction policies. Finally, balance manual memory management with tools like Redis Agent Memory Server for flexibility and control Sections Why does memory matter? Short-term & long-term memory Short-term memory Long-term memory The complexity most teams underestimate Key architectural decisions for agent memory Choosing memo\\\", \\\"title\\\": \\\"How to Build AI Agents with Redis Memory Management\\\", \\\"url\\\": \\\"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\\\"}\", \"created_at\": \"2026-03-26T18:15:48.214775+00:00\", \"domain\": null, \"embedding\": [0.5158062876148517, 0.4763886462173176, 0.4178648047293871, 0.3632466269957086, 0.29887566007655814, 0.24007466995977791, 0.18290672484068163, 0.14149645586546872], \"evidence_ref\": \"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\", \"freshness\": 0.75, \"id\": \"mem_5ec2c706538441349a16497f0d219796\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": 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\"memory\": {\"agent_id\": null, \"confidence\": 0.82, \"content\": \"Request: In personal-agent, make code-task execution target-repo-aware so repo changes run in the named target repo instead of assuming ai-dev-workflow; include tests and repo checks\\nPrimary agent: code\\nSecondary agent: personal\\nReason: Repo change in personal-agent to route code-task execution by named target repo, with tests and full checks.\", \"created_at\": \"2026-03-16T16:35:47.963315+00:00\", \"domain\": null, \"embedding\": [0.5257217330085674, 0.47327603646785704, 0.4100376563946533, 0.3754673419546352, 0.2916554088976158, 0.2538810165338887, 0.160962756746328, 0.12285109302221053], \"evidence_ref\": \"personal-agent:router\", \"freshness\": 0.9, \"id\": \"router_327cadd15d67586b\", \"metadata\": {\"kind\": \"router_handoff\", \"primary_agent\": \"code\", \"secondary_agent\": \"personal\"}, \"observed_at\": \"2026-03-16T16:35:47.963315+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"agent\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:router\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Request: In personal-agent, make code-task execution target-repo-aware so repo changes run in the named target repo instead of assuming ai-dev-workflow; include tests and repo chec\", \"task_id\": null, \"title\": \"Router handoff: code\", \"type\": \"task\", \"updated_at\": \"2026-03-16T16:35:47.963315+00:00\", \"url\": null}, \"score\": 0.33325195245030004, \"score_breakdown\": {\"confidence\": 0.82, \"facet\": 0.0, \"freshness\": 0.9, \"lexical\": 0.3333333333333333, \"semantic\": 0.9870130163353332}}]2026-03-26T18:47:25.110420+00:00\n--- mem_c8b6a1ee582446319abb7eab352eb096\nmem_c8b6a1ee582446319abb7eab352eb096\nmem_c8b6a1ee582446319abb7eab352eb096Research claim: AgentDock recommends safeguards for consolidation: age/importance thresholds, coAgentDock recommends safeguards for consolidation: age/importance thresholds, confidence checks, preserve originals optionally, cost controls for LLM synthesis, and run during low-AgentDock recommends safeguards for consolidation: age/importance thresholds, confidence checks, preserve originals optionally, cost controls for LLM synthesis, and run during low-activity windows.\n449945996138653, 0.17746958190408735], \"evidence_ref\": \"file:///Users/sebas/Code/ballbox-payment-integration/src/providers/mercadoPagoProvider.ts\", \"freshness\": 0.7, \"id\": \"legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_633b0b4d6c71078d\", \"metadata\": {\"claim_status\": \"active\", \"schema\": \"shared-agent-memory-v2\", \"subtype\": \"research_claim\"}, \"observed_at\": \"2026-03-13T14:01:39.684365+00:00\", \"origin_agent\": \"personal-agent\", \"project_id\": null, \"repo_id\": null, \"run_id\": \"35bd54a1-0135-414e-9c6b-245fca772f54\", \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:35bd54a1-0135-414e-9c6b-245fca772f54\", \"status\": \"active\", \"subtype\": \"research_claim\", \"summary\": \"MercadoPago production integration is not yet production-safe because the real adapter uses placeholder collector/POS identifiers and unvalidated request/response assumptions.\", \"task_id\": null, \"title\": \"Research claim: MercadoPago production integration is not yet production-safe because the real a\", \"type\": \"artifact\", \"updated_at\": \"2026-03-24T14:18:16.798224+00:00\", \"url\": \"file:///Users/sebas/Code/ballbox-payment-integration/src/providers/mercadoPagoProvider.ts\"}, \"score\": 0.23364101150074673, \"score_breakdown\": {\"confidence\": 0.97, \"facet\": 0.0, \"freshness\": 0.7, \"lexical\": 0.0, \"semantic\": 0.9829400766716448}}, {\"evidence_ref\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\", \"explanation\": \"facets=0.00 lexical=0.00 semantic=0.98 confidence=0.60 freshness=0.75\", \"matched_scope\": \"global\", \"memory\": {\"agent_id\": null, \"confidence\": 0.6, \"content\": \"AgentDock recommends safeguards for consolidation: age/importance thresholds, confidence checks, preserve originals optionally, cost controls for LLM synthesis, and run during low-activity windows.\", \"created_at\": \"2026-03-26T18:16:01.698803+00:00\", \"domain\": null, \"embedding\": [0.5097401478718668, 0.4877861369395645, 0.40578572524540224, 0.297905750995281, 0.2810404180936448, 0.27449783205421696, 0.2250649597563177, 0.20936275326169088], \"evidence_ref\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\", \"freshness\": 0.75, \"id\": \"mem_c8b6a1ee582446319abb7eab352eb096\", \"metadata\": {\"claim_status\": \"verified\", \"record_kind\": \"research_claim\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\", \"source_url\": \"https://hub.agentdock.ai/docs/memory/consolidation-guide\"}, \"observed_at\": \"2026-03-26T18:16:01.698803+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"AgentDock recommends safeguards for consolidation: age/importance thresholds, confidence checks, preserve originals optionally, cost controls for LLM synthesis, and run during low-\", \"task_id\": null, \"title\": \"Research claim: AgentDock recommends safeguards for consolidation: age/importance thresholds, co\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:16:01.698803+00:00\", \"url\": null}, \"score\": 0.21340055590200294, \"score_breakdown\": {\"confidence\": 0.6, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.0, \"semantic\": 0.9826703726800196}}, {\"evidence_ref\": null, \"explanation\": \"facets=0.00 lexical=0.00 semantic=0.98 confidence=0.99 freshness=0.70\", \"matched_scope\": \"global\", \"memory\": {\"agent_id\": null, \"confidence\": 0.99, \"content\": \"Sebas said main is already connected for street-cast-server.\", \"created_at\": \"2026-03-13T14:01:39.705759+00:00\", \"domain\": null, \"embedding\": [0.5436834257954364, 0.5107329151411675, 0.43400529747479855, 0.312559129634779, 0.2490117162301176, 0.19582017760251214, 0.18640574598700677, 0.1496894626865357], \"evidence_ref\": null, \"freshness\": 0.7, \"id\": \"legacy_claim_73698c1a-612d-456d-b178-6286ae9ab9cd_2cb5bb444cc49676\", \"metadata\": {\"claim_status\": \"verified\", \"schema\": \"shared-agent-memory-v2\", \"subtype\": \"research_claim\"}, \"observed_at\": \"2026-03-13T14:01:39.705759\n--- mem_cba730d4ea2f4679bb78d5e7586c9696\nmem_cba730d4ea2f4679bb78d5e7586c9696\n/mem_cba730d4ea2f4679bb78d5e7586c9696Research summary: Survey online proposals for periodic memory consolidation in agent memory/knowleFound concrete consolidation guidance (AgentDock) plus broader memory-management recommendations (Redis, Microsoft). 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What is Memory Consolidation? Memory consolidation transforms raw memories into refined knowledge through three key processes: Episodic \\u2192 Semantic Conversion : Converts time-specific experiences into general knowledge Memory Deduplication : Finds and merges similar memories to reduce redundancy Hierarchical Abstraction : Creates higher-level concepts from detailed memories This mirrors how human memory works - we don't remember every detail of every experience, but we extract patterns and knowledge that serve us better over time. Why Memory Consolidation Matters Without consolidation,\non Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. 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Test Configurations Test consolidation settings in development: // Aggressive for testing const testConfig = { maxAge: 1 * 24 * 60 * 60 * 1000, // 1 day similarityThreshold: 0.7, // Lower threshold preserveOriginals: false // Delete originals }; Performance Considerations Processing Time Similarity calculation : ~5ms per memory pair LLM synthesis : 500-2000ms per consolidation Batch of 20 memories : 5-30 seconds total Storage Impact Typical consolidation ratios: Episodic \\\\u2192 Semantic : 3:1 reduction Deduplication : 2:1 to 5:1 reduction Overall : 60-80% storage reduction Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. 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Start Conservative Begin with high thresholds and preservation: { similarityThreshold: 0.9, // Very similar only preserveOriginals: true, // Keep everything initially strategies: ['merge'], // Simple strategy first enableLLMSummarization: false } 2. Monitor and Adjust Track consolidation metrics: Number of memories consolidated Storage space saved Recall accuracy changes User feedback on missing information 3. Schedule Wisely Run consolidation during low-activity periods: Nightly batch jobs After user sessions end During maintenance windows 4. Test Configurations Test consolidation settings in development: // Aggressive for testing const testConfig = { maxAge: 1 * 24 * 60 * 60 * 1000, // 1 day similarityThreshold: 0.7, // Lower threshold preserveOriginals: false // Delete originals }; Performance Considerations Processing Time Similarity calculation : ~5ms per memory pair LLM synthesis : 500-2000ms per consolidation Batch of 20 memories : 5-30 seconds total Storage Impact Typical consolidation ratios: Episodic \\\\u2192 Semantic : 3:1 reduction Deduplication : 2:1 to 5:1 reduction Overall : 60-80% storage reduction Memory Quality Consolidation improves retrieval: Faster searches : Fewer memories to scan Better relevance : Consolidated knowledge matches queries better Reduced noise : Eliminates redundant information Integration with Memory System The consolidator integrates seamlessly with other memory components: With Decay System : Important memories survive, trivial ones fade With Connections : Consolidated memories maintain relationships With Search : Better recall through refined knowledge With PRIME : Extraction rules guide what becomes semantic Troubleshooting Common Issues Too Much Consolidation Increase similarityThreshold Enable preserveOriginals Reduce batchSize Not Enough Consolidation Decrease maxAge requirement Lower similarityThreshold Add more strategies High LLM Costs Reduce maxLLMCallsPerBatch Lower monthlyBudget Use simpler model Summary Memory consolidation is a powerful feature that: Prevents memory bloat through intelligent optimization Improves knowledge quality through synthesis Reduces costs through deduplication Maintains system performance at scale When configured properly, it creates a self-organizing memory system that gets better over time - just like human memory. 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Short-term & long-term memory Short-term memory Long-term memory The complexity most teams underestimate Key architectural decisions for agent memory Choosing memo\\\", \\\"title\\\": \\\"How to Build AI Agents with Redis Memory Management\\\", \\\"url\\\": \\\"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\\\"}\", \"created_at\": \"2026-03-26T18:15:48.214775+00:00\", \"domain\": null, \"embedding\": [0.5158062876148517, 0.4763886462173176, 0.4178648047293871, 0.3632466269957086, 0.29887566007655814, 0.24007466995977791, 0.18290672484068163, 0.14149645586546872], \"evidence_ref\": \"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\", \"freshness\": 0.75, \"id\": \"mem_5ec2c706538441349a16497f0d219796\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": \"personal-agent-memory-v1\"}, \"observed_at\": \"2026-03-26T18:15:48.214775+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"global\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:run:9be235c5-e438-4f89-a35e-9c9582574016\", \"status\": \"active\", \"subtype\": null, \"summary\": \"How to Build AI Agents with Redis Memory Management\", \"task_id\": null, \"title\": \"Capture: How to Build AI Agents with Redis Memory Management\", \"type\": \"artifact\", \"updated_at\": \"2026-03-26T18:15:48.214775+00:00\", \"url\": null}, \"score\": 0.2834272737778162, \"score_breakdown\": {\"confidence\": 0.75, \"facet\": 0.0, \"freshness\": 0.75, \"lexical\": 0.2, \"semantic\": 0.9895151585187745}}, {\"evidence_ref\": \"art_38ca2dd64b554fb986c08799a52c2b24\", \"explanation\": \"facets=0.00 lexical=0.20 semantic=0.99 confidence=0.94 freshness=0.95\", \"matched_scope\": \"project\", \"memory\": {\"agent_id\": null, \"confidence\": 0.94, \"content\": \"V1 spans personal-agent, agents-database, ai-dev-workflow, and ballbox-company-agent. Resume from shared DB task/handoff/artifact ids and repo-local V1 docs/README references.\", \"created_at\": \"2026-03-14T21:29:18.513932+00:00\", \"domain\": null, \"embedding\": [0.5580483453182788, 0.4620289260498238, 0.38407767707382, 0.40162961392934404, 0.3381329011873012, 0.2147531097617058, 0.05678567806198952, 0.05110711025579057], \"evidence_ref\": \"art_38ca2dd64b554fb986c08799a52c2b24\", \"freshness\": 0.95, \"id\": \"mem_v1_multi_repo_cross_reference\", \"metadata\": {\"kind\": \"cross_reference\", \"milestone\": \"V1\"}, \"observed_at\": \"2026-03-14T21:29:18.513932+00:00\", \"origin_agent\": null, \"project_id\": \"proj_personal_agent\", \"repo_id\": \"repo_personal_agent\", \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"project\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Shared DB now carries the V1 resume anchor and repo cross-reference.\", \"task_id\": null, \"title\": \"V1 multi-repo cross-reference\", \"type\": \"episode\", \"updated_at\": \"2026-03-14T21:29:18.513932+00:00\", \"url\": null}, \"score\": 0.3027055177478297, \"score_breakdown\": {\"confidence\": 0.94, \"facet\": 0.0, \"freshness\": 0.95, \"lexical\": 0.2, \"semantic\": 0.9887034516521984}}, {\"evidence_ref\": \"personal-agent:run:e5ebecb3-2978-497d-9410-31d5d02dea9b\", \"explanation\": \"facets=0.00 lexical=0.20 semantic=0.99 confidence=0.90 freshness=0.85\", \"matched_scope\": \"global\", \"memory\": {\"agent_id\": null, \"confidence\": 0.9, \"content\": \"Goal: Implement blocked-task workflow for dependent code and non-code work\\nScope: personal-agent task system and runtime behavior\\nAssumptions: Use the current shared task model as canonical; keep dependency metadata minimal-first; support blocked-by-one-task initially; for code tasks use stacked worktree/branch workflow based on blocker branch until blocker merges.\\nSummary: Implement blocked-task workflow for dependent code and non-code work\", \"created_at\": \"2026-03-17T01:15:26.326124+00:00\", \"domain\": null, \"embedding\": [0.5005997972115768, 0.4734163103390158, 0.44263189\nmem_5ec2c706538441349a16497f0d219796artifactglobalactivemanualCapture: How to Build AI Agents with Redis Memory Management{\"content_type\": \"text/html; charset=utf-8\", \"text\": \"How to Build AI Agents with Redis Memory Management Skip to: Home Content Footer navigation Redis is one of Fast Company's Most Innovative Companies of 2026 Learn more Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for cachin\nYmem_5ec2c706538441349a16497f0d219796Capture: How to Build AI Agents with Redis Memory ManagementHow to Build AI Agents with Redis Memory Management{\"content_type\": \"text/html; charset=utf-8\", \"text\": \"How to Build AI Agents with Redis Memory Management Skip to: Home Content Footer navigation Redis is one of Fast Company's Most Innovative Companies of 2026 Learn more Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for caching & streaming Redis for AI Faster GenAI apps start here Tools Redis LangCache Redis Insight Redis Data Integration Clients & Connectors Get Redis Downloads Resources Learn Tutorials Quick starts Commands University Knowledge Base Resource Center Blog Demo Center Developer Hub Connect Customer Stories Partners Support Community Events & Webinars Professional Services Latest Releases News & updates Learn how to Build Visit our Developer Hub Docs Pricing Search Login Book a meeting Try Redis Redis for AI Products Products Redis Cloud Fully managed and integrated with Google Cloud, Azure, and AWS Redis Software Self-managed software with enterprise-grade compliance and reliability Redis Open Source In-memory database for caching & streaming Redis for AI Faster GenAI apps start here Tools Redis LangCache Redis Insight Redis Data Integration Clients & Connectors Get Redis Downloads Resources Learn Tutorials Quick starts Commands University Knowledge Base Resource Center Blog Demo Center Developer Hub Connect Customer Stories Partners Support Community Events & Webinars Professional Services Latest Releases News & updates Learn how to Build Visit our Developer Hub Docs Pricing Try Redis Book a meeting Login Resource Center Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center Resource Center Events & webinars Blog Videos Glossary Resources Architecture Diagrams Demo Center Back to blog Blog How to build AI agents with Redis memory management February 11, 2026 12 minute read Jim Allen Wallace Memory can be one of the trickier parts of building AI agents. Large language models (LLMs) are stateless at their core\\u2014the model itself doesn't retain information between API calls. Products like ChatGPT and Claude layer memory systems on top, which is why they remember your name and preferences. But when you're building your own agents, you need to implement that memory layer yourself. Building memory that spans conversations, learns preferences over time, and retrieves relevant context when needed requires deliberate architectural decisions. The challenge is that agent memory isn't one thing. Most production agents need short-term context for coherent conversations, long-term storage for learned preferences, and semantic retrieval for surfacing relevant memories. All of this must be fast enough that users don't notice the overhead. Most teams underestimate this until they're deep into development. This guide covers how to build AI agents with robust memory architectures. Rather than stitching together separate vector databases, caching layers, and session stores, you can unify these patterns on a single platform. Agent memory spans multiple storage patterns simultaneously, and managing these across separate systems introduces additional latency and operational complexity. Why does memory matter? AI agent memory is crucial for enhancing efficiency and capabilities because Large Language Models (LLMs) do not inherently remember things i.e., they are stateless. Memory allows AI agents to learn from past interactions, retain information, and maintain context, leading to more coherent and personalized responses. Imagine an AI agent designed to plan and book work trips. Without memory, it won't remember personal preferences (e.g., \\\"Do you like direct flights or flights with layovers?\\\"); make procedural mistakes due to lack of understanding (e.g., booking a h\nrst, determine the memory types your app requires: short-term for conversational context or long-term forms like episodic, procedural, and semantic memory. Design strategies for summarizing and vectorizing interactions to avoid data bloat and ensure rapid retrieval. Choose effective memory retrieval methods, leveraging vector search for semantic similarity or hierarchical retrieval systems. Consider memory decay management using Redis' eviction policies. Finally, balance manual memory management with tools like Redis Agent Memory Server for flexibility and control Sections Why does memory matter? Short-term & long-term memory Short-term memory Long-term memory The complexity most teams underestimate Key architectural decisions for agent memory Choosing memo\\\", \\\"title\\\": \\\"How to Build AI Agents with Redis Memory Management\\\", \\\"url\\\": \\\"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\\\"}\", \"created_at\": \"2026-03-26T18:15:48.214775+00:00\", \"domain\": null, \"embedding\": [0.5158062876148517, 0.4763886462173176, 0.4178648047293871, 0.3632466269957086, 0.29887566007655814, 0.24007466995977791, 0.18290672484068163, 0.14149645586546872], \"evidence_ref\": \"https://redis.io/blog/build-smarter-ai-agents-manage-short-term-and-long-term-memory-with-redis/\", \"freshness\": 0.75, \"id\": \"mem_5ec2c706538441349a16497f0d219796\", \"metadata\": {\"artifact_kind\": \"source_capture\", \"record_kind\": \"research_artifact\", \"run_id\": \"9be235c5-e438-4f89-a35e-9c9582574016\", \"schema\": 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\"memory\": {\"agent_id\": null, \"confidence\": 0.82, \"content\": \"Request: In personal-agent, make code-task execution target-repo-aware so repo changes run in the named target repo instead of assuming ai-dev-workflow; include tests and repo checks\\nPrimary agent: code\\nSecondary agent: personal\\nReason: Repo change in personal-agent to route code-task execution by named target repo, with tests and full checks.\", \"created_at\": \"2026-03-16T16:35:47.963315+00:00\", \"domain\": null, \"embedding\": [0.5257217330085674, 0.47327603646785704, 0.4100376563946533, 0.3754673419546352, 0.2916554088976158, 0.2538810165338887, 0.160962756746328, 0.12285109302221053], \"evidence_ref\": \"personal-agent:router\", \"freshness\": 0.9, \"id\": \"router_327cadd15d67586b\", \"metadata\": {\"kind\": \"router_handoff\", \"primary_agent\": \"code\", \"secondary_agent\": \"personal\"}, \"observed_at\": \"2026-03-16T16:35:47.963315+00:00\", \"origin_agent\": null, \"project_id\": null, \"repo_id\": null, \"run_id\": null, \"schema_version\": \"shared-agent-memory-v2\", \"scope\": \"agent\", \"source_kind\": \"manual\", \"source_ref\": \"personal-agent:router\", \"status\": \"active\", \"subtype\": null, \"summary\": \"Request: In personal-agent, make code-task execution target-repo-aware so repo changes run in the named target repo instead of assuming ai-dev-workflow; include tests and repo chec\", \"task_id\": null, \"title\": \"Router handoff: code\", \"type\": \"task\", \"updated_at\": \"2026-03-16T16:35:47.963315+00:00\", \"url\": null}, \"score\": 0.33325195245030004, \"score_breakdown\": {\"confidence\": 0.82, \"facet\": 0.0, \"freshness\": 0.9, \"lexical\": 0.3333333333333333, \"semantic\": 0.9870130163353332}}]2026-03-26T18:47:25.110420+00:00\n--- mem_c8b6a1ee582446319abb7eab352eb096\nmem_c8b6a1ee582446319abb7eab352eb096\nmem_c8b6a1ee582446319abb7eab352eb096Research claim: AgentDock recommends safeguards for consolidation: age/importance thresholds, coAgentDock recommends 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{"type":"message","id":"2685369e","parentId":"2f3ac1dd","timestamp":"2026-04-19T22:27:55.376Z","message":{"role":"assistant","content":[{"type":"toolCall","id":"call_RrcTK6VRByBtE1lDDpd6OlbS|fc_071e452a5a0ea02e0169e556df7814819093d2f1aad46b5e5f","name":"bash","arguments":{"command":"set -euo pipefail\npython3 - <<'PY'\nimport sqlite3\nsrc='/mnt/rpi/agents-database/data/shared-agent-memory.pre-repair-20260419-185338.sqlite3'\nlive='/mnt/rpi/agents-database/data/shared-agent-memory.sqlite3'\nrecover=[\n('mem_54eeaf9633f34ac087975e9ad8fcaa37','Capture: Memory Consolidation Guide - AgentDock Documentation | AgentDock Hub'),\n('mem_5ec2c706538441349a16497f0d219796','Capture: How to Build AI Agents with Redis Memory Management'),\n('mem_c8b6a1ee582446319abb7eab352eb096','Research claim: AgentDock recommends safeguards for consolidation: age/importance thresholds, co'),\n('mem_cba730d4ea2f4679bb78d5e7586c9696','Research summary: Survey online proposals for periodic memory consolidation in agent memory/knowle'),\n('mem_dab474c6db644f3f9e33d3f3179ca966','AI Agent Memory: Architectures, Retrieval, Governance')\n]\nsc=sqlite3.connect(src); sc.row_factory=sqlite3.Row\nlc=sqlite3.connect(live); lc.row_factory=sqlite3.Row\ncols=[r['name'] for r in lc.execute('PRAGMA table_info(memories)')]\ninserted=[]\nfor mid,title in recover:\n    if lc.execute('SELECT 1 FROM memories WHERE id=?',(mid,)).fetchone():\n        continue\n    row=None\n    try:\n        row=sc.execute('SELECT * FROM memories WHERE id=?',(mid,)).fetchone()\n    except Exception:\n        row=None\n    if row is None:\n        try:\n            row=sc.execute('SELECT * FROM memories WHERE id=? OR title LIKE ? LIMIT 1',(mid,title+'%')).fetchone()\n        except Exception:\n            row=None\n    if row is None:\n        continue\n    data={c: row[c] for c in cols}\n    lc.execute(f\"INSERT INTO memories ({','.join(cols)}) VALUES ({','.join(['?']*len(cols))})\", [data[c] for c in cols])\n    try:\n        lc.execute('DELETE FROM memories_fts WHERE memory_id=?',(data['id'],))\n        lc.execute('INSERT INTO memories_fts (memory_id,title,summary,content) VALUES (?,?,?,?)',(data['id'],data['title'],data['summary'],data['content']))\n    except Exception:\n        pass\n    inserted.append(data['id'])\nlc.commit()\nprint('inserted', inserted)\nprint('count', len(inserted))\nprint('live_memories', lc.execute('SELECT COUNT(*) FROM memories').fetchone()[0])\nPY","timeout":120}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":14471,"output":646,"cacheRead":70784,"cacheWrite":0,"totalTokens":85901,"cost":{"input":0.0361775,"output":0.00969,"cacheRead":0.017696,"cacheWrite":0,"total":0.06356350000000001}},"stopReason":"toolUse","timestamp":1776637659140,"responseId":"resp_071e452a5a0ea02e0169e556dbe1a88190b2581448b0ad4e2f"}}
{"type":"message","id":"6b8261cf","parentId":"2685369e","timestamp":"2026-04-19T22:27:55.415Z","message":{"role":"toolResult","toolCallId":"call_RrcTK6VRByBtE1lDDpd6OlbS|fc_071e452a5a0ea02e0169e556df7814819093d2f1aad46b5e5f","toolName":"bash","content":[{"type":"text","text":"inserted []\ncount 0\nlive_memories 304\n"}],"isError":false,"timestamp":1776637675415}}
{"type":"message","id":"a02f6104","parentId":"6b8261cf","timestamp":"2026-04-19T22:28:04.538Z","message":{"role":"assistant","content":[{"type":"text","text":"Tried. No real further row-level recovery via SQLite.\n\nWhat happened\n- `iterdump()` on the corrupted backup failed immediately\n- direct SQLite reads still fail on the remaining damaged rows\n- raw `strings` scan found serialized row content for some of the “unreadable” ids inside the file\n\nWhat that means\n- the bytes for some missing rows still exist in the backup\n- but SQLite can’t traverse those pages cleanly anymore\n- a deeper salvage now means parsing raw file text/fragments, not normal DB recovery\n\nNet result\n- no additional clean rows were recovered in this last pass\n- live DB remains healthy\n- current live `memories` count is `304`\n\nWhat’s left unrecovered\n- at least these ids remain inaccessible through SQLite:\n  - `9be235c5-e438-4f89-a35e-9c9582574016`\n  - `mem_1349693993ae4981b89dd9dab290d66d`\n  - `mem_30a32043ffd8430fa1b3d82e409d7b53`\n  - `mem_3996cdf0bfd4413e8c48fbc4094b84a9`\n- and some others may still only be present as raw fragments\n\nBest next move if you want max salvage\n- do a one-off fragment recovery:\n  - scan raw backup bytes\n  - extract JSON-like record blobs around target ids\n  - validate fields\n  - manually reinsert reconstructed rows\n\nThat is doable, but it’s slower and less trustworthy than the SQLite-level recovery I already did.\n\nRecommendation\n- stop here unless those missing rows matter.\n- We already recovered the service and a meaningful chunk of lost memories.\n\nIf you want, I can do one final forensic pass just for:\n- the run `9be235c5-e438-4f89-a35e-9c9582574016`\n- and reconstruct whatever surviving records from that run are still embedded in the raw file.","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e556ecb4508190a7990e433079bf8a\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":165,"output":423,"cacheRead":85760,"cacheWrite":0,"totalTokens":86348,"cost":{"input":0.00041250000000000005,"output":0.006345,"cacheRead":0.02144,"cacheWrite":0,"total":0.0281975}},"stopReason":"stop","timestamp":1776637675417,"responseId":"resp_071e452a5a0ea02e0169e556ebef288190a8cc878bdbd9a507"}}
{"type":"message","id":"22922692","parentId":"a02f6104","timestamp":"2026-04-19T22:36:07.841Z","message":{"role":"user","content":[{"type":"text","text":"how many are left unrecovered?"}],"timestamp":1776638167836}}
{"type":"message","id":"f3752464","parentId":"22922692","timestamp":"2026-04-19T22:36:13.265Z","message":{"role":"assistant","content":[{"type":"text","text":"From the last solid SQLite-level check:\n\n- original corrupted DB `memories`: `320`\n- current live DB `memories`: `304`\n\nSo:\n\n- unrecovered total vs original count: `16`\n\nBreakdown:\n- `13` were recovered in the targeted merge pass\n- `9` were confirmed still unreadable by direct SQLite row access from the backup\n- the remaining gap to `16` exists because the corrupted source can’t be iterated cleanly end-to-end, so not every missing row can be identified by id from normal reads\n\nSo the safe answer is:\n\n- `16` memories still unrecovered relative to the original reported count\n- `9` of those are explicitly identified as still unreadable rows/items from the backup path we tested","textSignature":"{\"v\":1,\"id\":\"msg_071e452a5a0ea02e0169e558da1e5c8190972e0c1880481630\",\"phase\":\"final_answer\"}"}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":89,"output":160,"cacheRead":86272,"cacheWrite":0,"totalTokens":86521,"cost":{"input":0.00022250000000000001,"output":0.0024000000000000002,"cacheRead":0.021568,"cacheWrite":0,"total":0.0241905}},"stopReason":"stop","timestamp":1776638167841,"responseId":"resp_071e452a5a0ea02e0169e558d843588190b382a0bf83fa3a9b"}}