iles, and it seems there’s a typo regarding \"pi-config\". I might want to clarify this with the user using a questionnaire after I read through the three AGENTS files. So, let’s locate those files and read their contents!","thinkingSignature":"{\"id\":\"rs_09ce6544570a8b100169e1546423dc81939076ca473b7c3853\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp4VRpd3hCOd4-VEuz3o291kyFgEqWv-sQqBSA1DLwRTQkp-RYmkL8Qgi0pIAnxzjBLnEDqCNnKttPCxmCyBDwcegdBmPjG7AGSZDrkY3sQnUV5iryjiztuCI2nt6DMuHgHaOB4UkkM-TBZmg0PZ_qHkmR2ppAv2q3AGGG3RmwVB6LjneKVBmnlKIX1_SRG2UFH_ghdovVlKDnRm_Uc35WYyiMlNHCb5gyAJtEEHGOEUkydA0Z9ALGazO5oGX_Z9QS4cWKtntQG_Pxi5OPG7hdkLLN8596TS57lBA2iHegExoT8Zw8nmhCQTl44XTSQ1BGGir-m-Ld0T2JJYalP7v3sESrRO8MGBzb46YDY2OtQWv1S5pxjDmKSbJrocgdKEAc7hTb2WrywUVmOgfDmevozcTl-ZsFqBTvt30D45Tn1cyKgFe0zKowtT9F2Kokjy27NL6Fdg_-F-cCfwXKMBIktK9NpqJU5luJ3Xf1f3XrXffG1bRh0UHrHWmQjEn0neZXXtXCMb9c7S8vrA3UWZqeQwhamD24lHbcDLw3CQYsOsPcyH0xL5te-ODy_2nWghvyahLBEEJ9G1Gf7pU2ZwOTg_ZQ6dJShulaQ67OuQf9kn5BNS0EQxbavWBIqlzSq_UuL2l2w6s4t0EeIVt_oaYs-DybficD6em84u1w3XYCUl9DiVEub6am_8gpzlKwv8D6j9qhoPh_Q5i7XosbXbbNEVQfXGx3wZlmYR3DVee40hQ891GrT2au4DU__YzUaWJsZAWKjLmPvOA_0UmcCVEyXvZkLOzauNTqI0UAif610etGGAiVSt3kYXG_SPheZGpmdzPGKgcoBGfoqf6w931Ek9BPxPpa_Q_lpo0b6KZvndo61xcKI0x8KESFawguWr2zDj5JGGZhVawUJXF6inW7OH1l9Nqe09w30DivbuLZ1D4oQaxR0MJeOS8mBGNkJ0LgotOsZPGx7vfAEiuvEaDAusQL3FBxFWTyJHOjIteA28wJSLdAaXhRvBApuERscOnnQ2v7MB9IHIvyv0gq762sPUwmV1M9FyY1v8D0ngmzpgXaBYzXSqBSFxp_eFQmTPxBqeNF0V_hWDaGZIPuX3CVH2_YTYvGp6d4hihXX-qLREBzemZfXLcHcRprZyMQtKLydSKsKTnkKvYlmKusDproOj2t_2WwE2W5gufg3gqcymnknt0prmjiBCb5SsuZtpHE3Qsuf7OV3hNoufJJVivz-CvUyuyYIjeCyIPd79jfgcxeVafQwv7LSUacp2D9UvIH4Bb-AjEw83T81PKyyvnPa6Z4fZFoHJiRQ7CdXKZartyMpsWf8-X15EuKS40fwagRGSGJID6zgfEJ3l-pMgST8467PQ==\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Locating files for inspection**\\n\\nI need to check some files, like /AGENTS.md, maybe /home/sebas/AGENTS.md, and possibly /home/sebas/.pi/agent/AGENTS.md. The user mentioned something about agent files, and it seems there’s a typo regarding \\\"pi-config\\\". I might want to clarify this with the user using a questionnaire after I read through the three AGENTS files. So, let’s locate those files and read their contents!\"}]}"},{"type":"toolCall","id":"call_Dff6UmYDqGi1DqdY7tFP6BCn|fc_09ce6544570a8b100169e15469ae688193ba244628292ccb51","name":"bash","arguments":{"command":"printf 'HOME_AGENTS\\n'; find /home/sebas -maxdepth 1 -name 'AGENTS.md' -o -name 'CLAUDE.md' | sort; printf '\\nPI_AGENTS\\n'; find /home/sebas/.pi -maxdepth 3 -name 'AGENTS.md' -o -name 'CLAUDE.md' | sort; printf '\\nOPENCODE_AGENTS\\n'; find /home/sebas/.config/opencode -maxdepth 2 -name 'AGENTS.md' -o -name 'CLAUDE.md' | sort","timeout":30}},{"type":"toolCall","id":"call_sXAvNqVl5TeVxrKZdnQ8K6Bb|fc_09ce6544570a8b100169e15469ae788193ac533be0e6db15ef","name":"read","arguments":{"path":"/mnt/rpi/pi-config/AGENTS.md"}},{"type":"toolCall","id":"call_xsLltXvjpznSC4DGVUAXTFDA|fc_09ce6544570a8b100169e15469ae848193ab0a0aad55e2a9f5","name":"read","arguments":{"path":"/home/sebas/.config/opencode/AGENTS.md"}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":272,"output":293,"cacheRead":161408,"cacheWrite":0,"totalTokens":161973,"cost":{"input":0.00068,"output":0.0043950000000000005,"cacheRead":0.040352,"cacheWrite":0,"total":0.045427}},"stopReason":"toolUse","timestamp":1776374882303,"responseId":"resp_09ce6544570a8b100169e1546317c08193bf1165ff042581ad"}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:259:{"type":"message","id":"5e19f830","parentId":"a11bb0d9","timestamp":"2026-04-16T21:28:09.891Z","message":{"role":"toolResult","toolCallId":"call_Dff6UmYDqGi1DqdY7tFP6BCn|fc_09ce6544570a8b100169e15469ae688193ba244628292ccb51","toolName":"bash","content":[{"type":"text","text":"HOME_AGENTS\n/home/sebas/AGENTS.md\n\nPI_AGENTS\n\nOPENCODE_AGENTS\n/home/sebas/.config/opencode/AGENTS.md\n"}],"isError":false,"timestamp":1776374889890}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:264:{"type":"message","id":"6384f724","parentId":"8670e640","timestamp":"2026-04-16T21:28:56.068Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"**Planning descriptive questions**\n\nI'm thinking I need to create detailed questions for each section I found. The sections include Communication/Rule, Intent, Operating Profile/Intent (which I might merge), Rules, Endpoints, Playwright, Servidor/Environment, and Telegram. I wonder if eight descriptive questions will suffice. It’s important to ensure that each section gets the attention it deserves! I’ll need to formulate clear questions that help gather the necessary information effectively.","thinkingSignature":"{\"id\":\"rs_09ce6544570a8b100169e154757b4481939995f90d22abee9e\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp4VR4UvgckiPTzwksK6w92kHyqWM6sBqGa5AA1CGw6BITsezbLA2Jgy24JYlDRZgHfsDZSOX4ovDMcqmfHoQbU1M-1_iicae22iZU3TP95p50qiU6EMJy1itR7phLjU34LiKO6VLPaBynDswWzCQoo9KXFjOvkdHdtv_5aE7hJowK-l1znf6dGx7_jcg5hmRbZPlNQD0gx-9KRZdfWqjLeJFnCcB2CkHIfcMbQUNt98Xu1NLpBAaDiYDESTFZBaFsVHzJwa1OMCjvc3mnutuQfCdT5RzX2uXcCKA07YWuuX9hdr6Cad43_i0jQLxRl7iqrDmQI-njk31-Cd_tJi_BFxtZvQNQhmnrYNLWGS7_gH0zRpq1GOtMDpigrz3C092ryzkX2QgKVJSsk-Xn7Kl9vy4JRkBlrATWVVmFC0GwHqJ2b0Ent_yc9QrNj9LbKy-GfThDDOEFKgdn2HzCRCDjL95JQ9DpxrUJ7HfrfIvf9NbsKFsRzZNg8WFSUqPlbwLLUXqDkjtkmU-LSovO30WNXDuMVNvUx4GCJxePHHPYrYzRBF8rajp3MzzuAak_xMCoxjG9GLdhm7U1FHHJiHYKSzoUaOet6MoVFDrERJM4h1W5z3cLsxYHEnwAGeWsSovq2udlC0i4qYBQ0-3PkZJ0tpeA-5PuyrRP3jn3LRHp2pw1EBadBzjnMVRHmPI93hUfZVXYvxBbAcBymzBIA6fRbHqD0uY0_-EjmmlfF_TOtdD8VdfAuf1RwiGpM1yEMOzqvBgW-JzVKsXCwQVets32HxgSygwcWXikaM7CQIQekE6Z7cO3C5EbMQKKAQvB7IkHuFTyPVTu9exMgdF9811eQTmpxcHT6MMHy-CeSj6JIHEYVUXNms_meuQLyQtwZN2eJCrFtK7ZWv61BT2i0fIgQ6tGYGVrKl2KOizQtQ26W-KgMO8pXTeeNG8TKAQSBh3qEE2wXKReNdiLhVmd5_tIjwGH-J5riCnarEjoDM96LAOG3R5jbyvzLRVzhB057Ah-28jYPB1tNjibPwxCNdET2ZrsPhxbVhDZOkWCKS5ozGL5rhw-pT891_F2zOadDE2fPRFi_SkDNF0Z796pyVHUZSgvqGoyzWWxvo4JW_w-rb6Y0NX5Mq6mjI2C2C-gLpFY47s9UeKQBuVS4RGbuLFZYLwVLymCPqYVNVK5ImTT1DWdhcCPrtrtO_gJfp5mi6WsRiQ_LQoi55c5Ffe1vih3PVPCF03tzMKbVfuldVOYh1RVGwE=\",\"summary\":[{\"type\":\"summary_text\",\"text\":\"**Planning descriptive questions**\\n\\nI'm thinking I need to create detailed questions for each section I found. The sections include Communication/Rule, Intent, Operating Profile/Intent (which I might merge), Rules, Endpoints, Playwright, Servidor/Environment, and Telegram. I wonder if eight descriptive questions will suffice. It’s important to ensure that each section gets the attention it deserves! I’ll need to formulate clear questions that help gather the necessary information effectively.\"}]}"},{"type":"toolCall","id":"call_g1y3kfUQ7e1cWowIXVfufnjP|fc_09ce6544570a8b100169e15478b6cc8193b358c808e60f53b9","name":"questionnaire","arguments":{"questions":[{"id":"identity","label":"Identidad","prompt":"Veo que hoy hay dos familias de contenido: (1) la versión vieja en `~/AGENTS.md` y `~/.config/opencode/AGENTS.md`, muy centrada en “Personal Agent — Caveman Full”, y (2) la versión nueva en `pi-config/AGENTS.md`, más Pi-native y más corta. Para el archivo principal versionado en `pi-config/AGENTS.md`, ¿qué identidad base querés conservar? 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En `pi-config` lo dejamos como intención, pero además marcamos como pendiente validar que de verdad se cargue en todas las sesiones. Para el archivo principal que vamos a versionar, ¿qué querés dejar escrito como política final? Elegí pensando si querés una exigencia fuerte en el documento, aunque la validación técnica todavía no esté resuelta, o una redacción más honesta que deje claro que sigue siendo intención pero no garantía técnica confirmada.","options":[{"value":"hard-default","label":"Dejar caveman full como política fuerte","description":"Escribirlo como default obligatorio del agente principal"},{"value":"default-with-pending","label":"Dejar caveman default pero con nota de validación pendiente","description":"Mantener la intención, sin fingir que ya está técnicamente garantizado"},{"value":"soft-preference","label":"Bajarlo a preferencia, no política dura","description":"Caveman es deseado pero no define todo el archivo"}],"allowOther":false},{"id":"intent","label":"Intent","prompt":"En la parte de intención hay dos líneas posibles: la vieja, que incluye preferencias durables en `~/agents-database`, necesidad de sincronizar cambios al installer source y reinstalar para propagar; y la nueva, que pone foco en impacto de negocio, preguntar poco, ejecutar completo y usar subagentes cuando convenga. Para el `pi-config/AGENTS.md` principal, ¿qué querés conservar en esta sección? Pensalo como la misión estable del agente: qué cosas deben seguir siendo verdad aunque cambiemos herramientas o prompts alrededor.","options":[{"value":"keep-ops-intent","label":"Quedarnos con la intención operativa nueva","description":"Impacto, foco, pocas preguntas, ejecución completa, subagentes útiles"},{"value":"merge-old-and-new","label":"Fusionar intención vieja y nueva","description":"Sumar también durable preferences / sync concerns donde sigan teniendo sentido"},{"value":"rewrite-intent","label":"Reescribir desde cero","description":"Tomar ideas de ambos, pero sin comprometerse con la redacción actual"}],"allowOther":true},{"id":"profile","label":"Perfil","prompt":"Los archivos viejos tienen una sección fuerte de Operating Profile: priorizar business impact, reframing técnico hacia objetivo, no over-explaining, señalar contradicciones, workflow low-noise, broad task → orchestrator → subagents. 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Para el AGENTS principal versionado, ¿qué nivel de detalle de infraestructura querés mantener? Pensalo en función de si este archivo debe ser una fuente viva de operación cotidiana o sólo una guía compacta que apunte a documentación más específica.","options":[{"value":"keep-detailed","label":"Mantener bastante detalle de infraestructura","description":"Hostname, IP, puertos, notas operativas útiles en el día a día"},{"value":"keep-essential","label":"Mantener sólo lo esencial","description":"Servidor, hostname/IP y lo mínimo para no perder contexto"},{"value":"move-out","label":"Mover casi todo a docs separadas","description":"AGENTS principal breve; infra detallada en otro archivo"}],"allowOther":false},{"id":"endpoints","label":"Endpoints","prompt":"Los endpoints de `personal-agent` y `agents-database` aparecen tanto en viejo como en nuevo. Parecen bastante estables y útiles, pero también son el tipo de dato que puede quedar viejo. Para el archivo principal versionado, ¿querés mantenerlos directamente ahí como referencia rápida del agente, o preferís tratarlos como documentación secundaria para no mezclar comportamiento del agente con infraestructura cambiante?","options":[{"value":"keep-inline","label":"Mantener endpoints en el AGENTS principal","description":"Son útiles y suficientemente importantes como para estar visibles ahí"},{"value":"keep-brief","label":"Mantenerlos pero muy resumidos","description":"Sólo nombre + URL, sin mucho contexto adicional"},{"value":"move-out","label":"Sacarlos del AGENTS principal","description":"Dejarlos en docs aparte para reducir ruido"}],"allowOther":false},{"id":"playwright-telegram","label":"Herramientas","prompt":"Hay dos bloques pequeños pero prácticos: Playwright (preferir headless Chromium, evitar Firefox/WebKit salvo necesidad) y Telegram (variables requeridas + comando de notificación). Estos bloques mezclan preferencias de tooling con atajos operativos. Para el AGENTS principal de `pi-config`, ¿querés que estas ayudas sigan estando ahí como memoria operativa rápida, o preferís sacar alguna de ellas para que el archivo quede más conceptual y menos “runbook”?","options":[{"value":"keep-both","label":"Mantener ambos bloques","description":"Playwright y Telegram siguen siendo parte del contexto operativo útil"},{"value":"keep-playwright-only","label":"Mantener sólo Playwright","description":"Telegram no hace falta en el AGENTS principal"},{"value":"keep-telegram-only","label":"Mantener sólo Telegram","description":"Playwright puede ir a otro lado"},{"value":"drop-both","label":"Sacar ambos del AGENTS principal","description":"Dejarlo más limpio y mover eso a docs separadas"}],"allowOther":false}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":632,"output":1895,"cacheRead":162688,"cacheWrite":0,"totalTokens":165215,"cost":{"input":0.00158,"output":0.028425000000000002,"cacheRead":0.040672,"cacheWrite":0,"total":0.070677}},"stopReason":"toolUse","timestamp":1776374892901,"responseId":"resp_09ce6544570a8b100169e15473c6508193b2ca32e086a3b274"}}
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Para el AGENTS principal en `pi-config`, ¿cómo querés dejar la filosofía de reglas? Elegí pensando en el equilibrio entre velocidad y control humano.","options":[{"value":"minimal-hard-rules","label":"Pocas reglas duras y claras","description":"Confirmar irreversibles, no push a main, resto bastante libre"},{"value":"medium-guardrails","label":"Agregar más guardrails explícitos","description":"Además de lo anterior, dejar límites más detallados en el AGENTS principal"},{"value":"keep-current-style","label":"Dejarlo parecido a como está ahora en pi-config","description":"Directo, bajo ruido, con pocas restricciones críticas"}],"allowOther":true},{"id":"infra","label":"Infra","prompt":"Los archivos viejos incluyen mucha info de infraestructura: servidor = Raspberry Pi 5 en casa, ballbox-first, hostname, IP, puertos y notas sobre routing (`/api/`, `/portal/`). En el archivo nuevo ya dejamos parte de eso, pero simplificado. Para el AGENTS principal versionado, ¿qué nivel de detalle de infraestructura querés mantener? Pensalo en función de si este archivo debe ser una fuente viva de operación cotidiana o sólo una guía compacta que apunte a documentación más específica.","options":[{"value":"keep-detailed","label":"Mantener bastante detalle de infraestructura","description":"Hostname, IP, puertos, notas operativas útiles en el día a día"},{"value":"keep-essential","label":"Mantener sólo lo esencial","description":"Servidor, hostname/IP y lo mínimo para no perder contexto"},{"value":"move-out","label":"Mover casi todo a docs separadas","description":"AGENTS principal breve; infra detallada en otro archivo"}],"allowOther":false},{"id":"endpoints","label":"Endpoints","prompt":"Los endpoints de `personal-agent` y `agents-database` aparecen tanto en viejo como en nuevo. Parecen bastante estables y útiles, pero también son el tipo de dato que puede quedar viejo. Para el archivo principal versionado, ¿querés mantenerlos directamente ahí como referencia rápida del agente, o preferís tratarlos como documentación secundaria para no mezclar comportamiento del agente con infraestructura cambiante?","options":[{"value":"keep-inline","label":"Mantener endpoints en el AGENTS principal","description":"Son útiles y suficientemente importantes como para estar visibles ahí"},{"value":"keep-brief","label":"Mantenerlos pero muy resumidos","description":"Sólo nombre + URL, sin mucho contexto adicional"},{"value":"move-out","label":"Sacarlos del AGENTS principal","description":"Dejarlos en docs aparte para reducir ruido"}],"allowOther":false},{"id":"playwright-telegram","label":"Herramientas","prompt":"Hay dos bloques pequeños pero prácticos: Playwright (preferir headless Chromium, evitar Firefox/WebKit salvo necesidad) y Telegram (variables requeridas + comando de notificación). Estos bloques mezclan preferencias de tooling con atajos operativos. Para el AGENTS principal de `pi-config`, ¿querés que estas ayudas sigan estando ahí como memoria operativa rápida, o preferís sacar alguna de ellas para que el archivo quede más conceptual y menos “runbook”?","options":[{"value":"keep-both","label":"Mantener ambos bloques","description":"Playwright y Telegram siguen siendo parte del contexto operativo útil"},{"value":"keep-playwright-only","label":"Mantener sólo Playwright","description":"Telegram no hace falta en el AGENTS principal"},{"value":"keep-telegram-only","label":"Mantener sólo Telegram","description":"Playwright puede ir a otro lado"},{"value":"drop-both","label":"Sacar ambos del AGENTS principal","description":"Dejarlo más limpio y mover eso a docs separadas"}],"allowOther":false}],"answers":[{"id":"identity","value":"personal-caveman","label":"Mantener identidad “Personal Agent — Caveman Full”","wasCustom":false,"index":1},{"id":"communication","value":"hard-default","label":"Dejar caveman full como política fuerte","wasCustom":false,"index":1}],"cancelled":true},"isError":false,"timestamp":1776375707190}}
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/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:291:{"type":"message","id":"eb3d2090","parentId":"c860ea7c","timestamp":"2026-04-16T21:53:46.560Z","message":{"role":"user","content":[{"type":"text","text":"de la 6. mantener tambien el nginx que routea a otros servicios. pero no mencionemos opencode ni clawdbot (este incluso ya fue borrado)\nde la 7: a"}],"timestamp":1776376426538}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:293:{"type":"message","id":"c652d36b","parentId":"c860ea7c","timestamp":"2026-04-16T21:54:11.346Z","message":{"role":"user","content":[{"type":"text","text":"de la 7. mantener tambien el nginx que routea a otros servicios. pero no mencionemos opencode ni clawdbot (este incluso ya fue borrado)\nde la 8: a"}],"timestamp":1776376451341}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:317:{"type":"message","id":"6127db54","parentId":"dfad15d9","timestamp":"2026-04-16T22:01:09.138Z","message":{"role":"toolResult","toolCallId":"call_5sx0csBxwQE5ANrV55RIPzcc|fc_09ce6544570a8b100169e15c24e59c8193a8e8dc2f8a94191f","toolName":"read","content":[{"type":"text","text":"# ~/.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\"\n# opencode\nexport PATH=/home/sebas/.opencode/bin:$PATH\nexport PERSONAL_AGENT_SHARED_MEMORY_DB_PATH=~/agents-database/data/shared-agent-memory.sqlite3\n"}],"isError":false,"timestamp":1776376869137}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:323:{"type":"message","id":"137255f8","parentId":"f306f1fb","timestamp":"2026-04-16T22:01:42.665Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"","thinkingSignature":"{\"id\":\"rs_09ce6544570a8b100169e15c42061081939a97b0e55a6acb06\",\"type\":\"reasoning\",\"encrypted_content\":\"gAAAAABp4VxFnQIORboaSZQits-xDKmhZa8T_J4JbL54zJd1f7yvE_dMZi_2FoKF_adBZoCikAl7bCd8MEDMTeSWrL-j81ti6jWw4x6Sx-4G47lxB6XLSD4CumpfCLsja5mrLkEIvvrs7l2VcEqBifr7pjLDRzjOmqfgqX0HQQ_EqIt-LPAKZMYQZ88bWbOq0XNIjKsDPcpDBMAzvllRixr7Lb72xzICTFphX-xpZobVLCWbveaWO2pOhJ1xgC-ZNcHK3H2qQK4IfNgYeO9oCyoxyoxLH9qsDqa1gF-UF500TTw2LlX49kEh8pR-TuiFzZlXf7WE_Q8TSP4U6hdv-OeKkI0Uamikb5ESBdHQ4USPj5stEuMU_opxICbv4Ba5lMnJeIH5WhRpyN5HwoK9fpaEZC1fLLfa3YzRgMNWSWFz7HVySvbqowfPJ0ZlSJYp5L-7CkyiMHAv1TYKU0EjrRNGMasI-C3hGFo2yZYSStJFGL0XMLpR74fIFcoiAb9wrbPGmi5WS53EXq9ir6EBvjy6Xz5CTUB9oRIUrl6gDCHuBx6j-XCleDkopqEN9lZq6ZfKapkF63HkzP1oZPjaBZlsvC5lzcG1fE7flSkfwErvkgnvA1AT3tMA0V6hbspSgWGHmthLbTURNIR0H4fd6rLjhoi_npn0RyvFa2thAvlcYBRKQRep2hFLu0v1kj7-99xeeoWknSF1sb88DyqoRDvCYB2r-uu5ZpCp-yx1-QVRsi3w6HwahiVJ-QiYLi7fzCy-6jn5jGnhQ_I_3mcP-FAEsMUeIh9iXwJxlNgWuAMzU44deNA6kprlFTCGuJKF9kBXgYxHmK6w5LYwAM820YhFXb1k5NiaJzNqp2-PPOGnqYQZF8gyZGnuOExL5RgLhU2NUvKByP9CoX9H4tvJBnpf2zSrOOdNGMg582E8ZWqHbIpD-Oo9jZ97AUBBuoBhi7ehNt1-bIx3QBGcai_0RFn1kzcvCU7x-UQlW8iK2BX71r8h_6UkVCyQxHBE0sYIDA64Dx8hnHBtf6CmoBzfGngA2wEtsoSgOxvu2OzJ7zIla49RrDKFmbb06Hz-6Qj1tO7iUruk7ydsGnUe_qyhPU0OsBk657cDmQO4PBvrHbPZFndOobX0-ygrQ2wsAJ1189AxeRIuopuMAyrg9o80oIZ3t4yL8d1L5I12rTkdEneWYoMAY9sRPvbEr2qxArCMRD-DjdKbFBYqyhzsewvTyldrWZiDPlXPq4NobLcuRdGSknlSS7xsMJWF1C43ymCfr-X88sFApRo-iyDRuH_Gz6ss_281d0XC2zkyeE83TZJFbtwRqbIMjodphRnnemSDhuj4oyAagowYld8KJDrWAwgEFc8ySKQdRwiKZRrEU3EGcQgjUOdFB5e9ztWzXudWKHTu_tmJvMB97KujFjpthOvqZZ_2nue-swFtJc7Bn8cDgf7eASSI5DEH_7XACM7Kf7Dk9xD67suFBpzhyvzDiSFQYiRHK8rUQ9gEzbP91JFQKmpIM7lTAcEk_X7A66CYl5WyfvwhVOgqxrzOGWu0O40QCAQcriGxCJZyN0KGRY5JN-C7Ds9wqEzybdm7v-QEtnok6iXOWd_pcR9IpLmVZkj0scpXH0Z4SKsz3V9wZroFCG56YquRFKCgZMvn4-J7xOPh2Sew2PMCi7DHc4KCN9gnY-1RcWQPJfqd9ngStaOKi3g31Zj3erks_8WRSFZL3tYPZJQIHIR6e4O2S6qDJL9khkaX8Iea0I_J36dAhnUYTHfrenYdQLmRNeUcx5uZlvhwHPHv-ghNzUYQqUtVI6lh-36WFhyMbA==\",\"summary\":[]}"},{"type":"toolCall","id":"call_3b6xzGOfdAi8wFK7tbPVGtTn|fc_09ce6544570a8b100169e15c4540b08193a414c7e2b382f406","name":"edit","arguments":{"path":"/home/sebas/.bashrc","edits":[{"oldText":"export PATH=\"$HOME/.npm-global/bin:$PATH\"\n# opencode\n","newText":"export PATH=\"$HOME/.npm-global/bin:$PATH\"\nexport PI_CODING_AGENT_DIR=/mnt/rpi/pi-config\n# opencode\n"}]}}],"api":"openai-codex-responses","provider":"openai-codex","model":"gpt-5.4","usage":{"input":661,"output":235,"cacheRead":174976,"cacheWrite":0,"totalTokens":175872,"cost":{"input":0.0016525,"output":0.003525,"cacheRead":0.043744,"cacheWrite":0,"total":0.0489215}},"stopReason":"toolUse","timestamp":1776376895448,"responseId":"resp_09ce6544570a8b100169e15c4102208193a2381f7b227ac46b"}}
/home/sebas/.pi/agent/sessions/--mnt-rpi--/2026-04-16T19-33-46-674Z_019d97c9-0431-734a-b9ce-92b7cb3e75df.jsonl:324:{"type":"message","id":"02e25837","parentId":"137255f8","timestamp":"2026-04-16T22:01:42.697Z","message":{"role":"toolResult","toolCallId":"call_3b6xzGOfdAi8wFK7tbPVGtTn|fc_09ce6544570a8b100169e15c4540b08193a414c7e2b382f406","toolName":"edit","content":[{"type":"text","text":"Successfully replaced

Command timed out after 20 seconds


**Troubleshooting noise issues**

It sounds like I'm encountering a timeout problem, possibly due to noise in the system. I want to make sure to proceed using known references. I’m considering using a targeted find method, and I think inspecting the directory at `/.config/opencode/AGENTS` could help. Removing entire directories might be a way to clean things up, but I need to be careful and sure about what I’m doing. I’ll keep thinking it through!

bash

find /home/sebas /mnt/rpi \( -path '/home/sebas/.codex' -o -path '/home/sebas/.pi/agent/sessions' -o -path '*/.git' -o -path '*/node_modules' \) -prune -o -type f \( -name '*.md' -o -name '*.sh' -o -name '*.bash' -o -name '*.zsh' -o -name '*.json' -o -name '*.yaml' -o -name '*.yml' -o -name '*.service' -o -name '*.conf' -o -name '*.txt' \) -print0 | xargs -0 rg -n --no-messages 'opencode' | head -n 200

ls -la /home/sebas/.opencode /home/sebas/.config/opencode /home/sebas/.local/share/opencode 2>/dev/null


El archivo AGENTS principal se movió a `/mnt/rpi/pi-config/AGENTS.md`. Tomá ese archivo como fuente de verdad.


l.append(\"AND task_id = ?\")\n            params.append(task_id)\n        if status is not None:\n            sql.append(\"AND status = ?\")\n            params.append(status)\n        sql.append(\"ORDER BY created_at DESC LIMIT ?\")\n        params.append(limit)\n        with self.store.connection() as conn:\n            rows = conn.execute(\" \".join(sql), params).fetchall()\n            return [self._row_to_task_run(row) for row in rows]\n\n    def create_artifact(\n        self,\n        *,\n        task_id: str,\n        artifact_type: str,\n        title: str,\n        content: str,\n        fmt: str = \"md\",\n        status: str = \"active\",\n        source_ref: str | None = None,\n        metadata: dict[str, Any] | None = None,\n        artifact_id: str | None = None,\n    ) -> dict[str, Any]:\n        now = utcnow()\n        record = {\n            \"id\": artifact_id or make_id(\"art\"),\n            \"task_id\": task_id,\n            \"artifact_type\": artifact_type,\n            \"title\": title,\n            \"content\": content,\n            \"format\": fmt,\n            \"status\": status,\n            \"source_ref\": source_ref,\n            \"created_at\": now,\n            \"updated_at\": now,\n            \"metadata_json\": self.store.dumps(metadata or {}),\n        }\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                INSERT INTO artifacts (\n                    id, task_id, artifact_type, title, content, format, status, source_ref, created_at, updated_at, metadata_json\n                ) VALUES (\n                    :id, :task_id, :artifact_type, :title, :content, :format, :status, :source_ref, :created_at, :updated_at, :metadata_json\n                )\n                \"\"\",\n                record,\n            )\n        self._run_opportunistic_maintenance(limit=1)\n        return self.get_artifact(record[\"id\"])\n\n    def get_artifact(self, artifact_id: str) -> dict[str, Any]:\n        with self.store.connection() as conn:\n            row = conn.execute(\"SELECT * FROM artifacts WHERE id = ?\", (artifact_id,)).fetchone()\n            if row is None:\n                raise KeyError(artifact_id)\n            return self._row_to_artifact(row)\n\n    def list_artifacts(self, *, task_id: str | None = None, limit: int = 50) -> list[dict[str, Any]]:\n        sql = [\"SELECT * FROM artifacts WHERE 1=1\"]\n        params: list[Any] = []\n        if task_id is not None:\n            sql.append(\"AND task_id = ?\")\n            params.append(task_id)\n        sql.append(\"ORDER BY created_at DESC LIMIT ?\")\n        params.append(limit)\n        with self.store.connection() as conn:\n            rows = conn.execute(\" \".join(sql), params).fetchall()\n            return [self._row_to_artifact(row) for row in rows]\n\n    def dashboard_snapshot(self, *, owner_agent: str | None = None) -> dict[str, Any]:\n        active_tasks = self.list_tasks(owner_agent=owner_agent, limit=50)\n        active_tasks = [task for task in active_tasks if task[\"status\"] in {\"open\", \"draft\", \"in_progress\"}][:20]\n        blocked_tasks = self.list_tasks(status=\"blocked\", owner_agent=owner_agent, limit=20)\n        recent_runs = self.list_task_runs(limit=20)\n        recent_artifacts = self.list_artifacts(limit=20)\n        return {\n            \"active_tasks\": active_tasks,\n            \"blocked_tasks\": blocked_tasks,\n            \"recent_runs\": recent_runs,\n            \"recent_artifacts\": recent_artifacts,\n        }\n\n    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                        (self.store.dumps(metadata), utcnow(), approval[\"task_id\"]),\n                    )\n                    conn.execute(\n                        \"\"\"\n                        INSERT INTO artifacts (\n                            id, task_id, artifact_type, title, content, format, status, source_ref, created_at, updated_at, metadata_json\n                        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\n                        \"\"\",\n                        (\n                            make_id(\"art\"),\n                            approval[\"task_id\"],\n                            \"approval_resolution\",\n                            f\"Approval {approval['kind']}\",\n                            json.dumps(metadata[\"approval\"], sort_keys=True),\n                            \"json\",\n                            \"archived\" if approval[\"status\"] != \"pending\" else \"active\",\n                            \"migration:v2\",\n                            utcnow(),\n                            utcnow(),\n                            self.store.dumps({}),\n                        ),\n                    )\n                    migrated[\"approval_artifacts\"] += 1\n                conn.execute(\"DROP TABLE approvals\")\n            if self._table_exists(conn, \"handoffs\"):\n                for row in conn.execute(\"SELECT * FROM handoffs\").fetchall():\n                    handoff = dict(row)\n                    payload = self.store.loads(handoff[\"payload_json\"]) or {}\n                    conn.execute(\n                        \"\"\"\n                        INSERT INTO artifacts (\n                            id, task_id, artifact_type, title, content, format, status, source_ref, created_at, updated_at, metadata_json\n                        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\n                        \"\"\",\n                        (\n                            make_id(\"art\"),\n                            handoff[\"task_id\"],\n                            \"delegation_note\",\n                            f\"Handoff {handoff['from_agent']} -> {handoff['to_agent']}\",\n                            json.dumps(\n                                {\n                                    \"from_agent\": handoff[\"from_agent\"],\n                                    \"to_agent\": handoff[\"to_agent\"],\n                                    \"reason\": handoff[\"reason\"],\n                                    \"status\": handoff[\"status\"],\n                                    \"payload\": payload,\n                                    \"result_summary\": handoff[\"result_summary\"],\n                                    \"error_message\": handoff[\"error_message\"],\n                                    \"completed_at\": handoff[\"completed_at\"],\n                                },\n                                sort_keys=True,\n                            ),\n                            \"json\",\n                            \"active\",\n                            \"migration:v2\",\n                            utcnow(),\n                            utcnow(),\n                            self.store.dumps({}),\n                        ),\n                    )\n                    migrated[\"handoff_artifacts\"] += 1\n                conn.execute(\"DROP TABLE handoffs\")\n        after = self.audit_v2()\n        return {\"status\": \"ok\", \"before\": before, \"after\": after, \"migrated\": migrated}\n\n    def _capture_source(\n        self, trigger_type: str, source_kind: str, source_ref: str, scope: str, content: str, metadata: dict[str, Any]\n    ) -> dict[str, Any]:\n        now = utcnow()\n        source = {\n            \"id\": make_id(\"src\"),\n            \"source_kind\": source_kind,\n            \"title\": metadata.get(\"title\") or source_ref,\n            \"content\": content,\n            \"source_ref\": source_ref,\n            \"metadata_json\": self.store.dumps(metadata),\n            \"created_at\": now,\n        }\n        event = {\n            \"id\": make_id(\"ing\"),\n            \"trigger_type\": trigger_type,\n            \"source_id\": source[\"id\"],\n            \"requested_scope\": scope,\n            \"job_state\": \"pending\",\n            \"processor_outcome\": None,\n            \"retry_count\": 0,\n            \"error_message\": None,\n            \"created_at\": now,\n            \"updated_at\": now,\n            \"processed_at\": None,\n        }\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                INSERT INTO sources (id, source_kind, title, content, source_ref, metadata_json, created_at)\n                VALUES (:id, :source_kind, :title, :content, :source_ref, :metadata_json, :created_at)\n                \"\"\",\n                source,\n            )\n            conn.execute(\n                \"\"\"\n                INSERT INTO ingestion_events (\n                    id, trigger_type, source_id, requested_scope, job_state, processor_outcome,\n                    retry_count, error_message, created_at, updated_at, processed_at\n                ) VALUES (\n                    :id, :trigger_type, :source_id, :requested_scope, :job_state, :processor_outcome,\n                    :retry_count, :error_message, :created_at, :updated_at, :processed_at\n                )\n                \"\"\",\n                event,\n            )\n        self._run_opportunistic_maintenance(limit=1)\n        return {\"source\": source, \"event\": event}\n\n    def _run_opportunistic_maintenance(self, *, limit: int) -> None:\n        if self._maintenance_check_running:\n            return\n        due_jobs = self.list_due_maintenance_jobs(limit=1)\n        if not due_jobs:\n            return\n        self._maintenance_check_running = True\n        try:\n            from .engine import MemoryEngine\n\n            MemoryEngine(self).run_due_maintenance(limit=limit)\n        except Exception:\n            return\n        finally:\n            self._maintenance_check_running = False\n\n    def _memory_filter_sql(self, sql: list[str], filters: dict[str, Any]) -> list[Any]:\n        params: list[Any] = []\n        allowed = {\"project_id\", \"repo_id\", \"type\", \"subtype\", \"run_id\", \"task_id\", \"origin_agent\", \"url\", \"domain\"}\n        for key, value in filters.items():\n            if key not in allowed or value is None:\n                continue\n            sql.append(f\"AND {key} = ?\")\n            params.append(value)\n        return params\n\n    def _facet_score(self, memory: dict[str, Any], filters: dict[str, Any]) -> float:\n        tracked = [\"project_id\", \"repo_id\", \"type\", \"subtype\", \"run_id\", \"task_id\", \"origin_agent\", \"url\", \"domain\"]\n        applied = [key for key in tracked if filters.get(key) is not None]\n        if not applied:\n            return 0.0\n        matched = sum(1 for key in applied if memory.get(key) == filters[key])\n        return matched / len(applied)\n\n    def _migrate_memory_row(self, row: dict[str, Any]) -> dict[str, Any] | None:\n        metadata = self.store.loads(row.get(\"metadata_json\")) or {}\n        if row.get(\"schema_version\") == SCHEMA_VERSION and not metadata.get(\"legacy_kind\") and not metadata.get(\"legacy_system\"):\n            return None\n        subtype = self._memory_subtype(metadata)\n        origin_agent = row.get(\"origin_agent\") or metadata.get(\"origin_agent\") or metadata.get(\"legacy_system\") or row.get(\"agent_id\")\n        run_id = row.get(\"run_id\") or metadata.get(\"run_id\") or metadata.get(\"legacy_run_id\") or self._infer_run_id(row, subtype)\n        task_id = row.get(\"task_id\") or metadata.get(\"task_id\")\n        url = row.get(\"url\") or metadata.get(\"url\") or metadata.get(\"source_url\") or self._infer_url(row, subtype)\n        domain = row.get(\"domain\") or metadata.get(\"domain\") or (urlparse(url).netloc if url else None)\n        clean = {key: value for key, value in metadata.items() if key not in {\"legacy_kind\", \"legacy_system\", \"legacy_run_id\", \"run_id\", \"task_id\", \"url\", \"domain\", \"source_url\", \"record_kind\", \"schema\"}}\n        if subtype == \"research_run\":\n            clean[\"goal\"] = clean.get(\"goal\") or _line_value(row[\"content\"], \"Goal\") or row[\"title\"].removeprefix(\"Research run: \").strip()\n            clean[\"scope\"] = clean.get(\"scope\") or _line_value(row[\"content\"], \"Scope\")\n            clean[\"assumptions\"] = clean.get(\"assumptions\") or _line_value(row[\"content\"], \"Assumptions\")\n            clean[\"summary\"] = clean.get(\"summary\") or _line_value(row[\"content\"], \"Summary\") or row[\"summary\"]\n        clean[\"schema\"] = SCHEMA_VERSION\n        clean[\"subtype\"] = subtype\n        record_type = row[\"type\"]\n        if subtype == \"router_handoff\":\n            record_type = \"episode\"\n        elif subtype == \"research_source\":\n            record_type = \"artifact\"\n        return {\n            \"id\": row[\"id\"],\n            \"schema_version\": SCHEMA_VERSION,\n            \"type\": record_type,\n            \"subtype\": subtype,\n            \"origin_agent\": origin_agent,\n            \"run_id\": run_id,\n            \"task_id\": task_id,\n            \"url\": url,\n            \"domain\": domain,\n            \"summary\": clean.get(\"summary\", row[\"summary\"]),\n            \"metadata_json\": self.store.dumps(clean),\n        }\n\n    def _migrate_task_row(self, row: dict[str, Any]) -> dict[str, Any] | None:\n        metadata = self.store.loads(row.get(\"metadata_json\")) or {}\n        if row.get(\"schema_version\") == SCHEMA_VERSION and not metadata.get(\"legacy_kind\") and not metadata.get(\"legacy_system\"):\n            return None\n        run_id = row.get(\"run_id\") or metadata.get(\"run_id\") or metadata.get(\"legacy_run_id\")\n        clean = {key: value for key, value in metadata.items() if key not in {\"legacy_kind\", \"legacy_system\", \"legacy_run_id\"}}\n        clean[\"schema\"] = SCHEMA_VERSION\n        return {\n            \"id\": row[\"id\"],\n            \"schema_version\": SCHEMA_VERSION,\n            \"run_id\": run_id,\n            \"metadata_json\": self.store.dumps(clean),\n        }\n\n    def _ensure_default_jobs(self) -> None:\n        defaults = [\n            {\n                \"id\": \"job_consolidation_daily_10\",\n                \"job_type\": \"consolidation\",\n                \"cadence\": \"daily\",\n                \"interval_minutes\": None,\n                \"window_start\": \"10:00\",\n                \"window_end\": None,\n                \"metadata\": {\n                    \"mode\": \"daily_10\",\n                    \"candidate_age_days\": 7,\n                    \"max_candidates\": 200,\n                    \"dedupe_high_threshold\": 0.9,\n                    \"dedupe_mid_threshold\": 0.75,\n                    \"promote_confidence\": 0.7,\n                    \"conflict_threshold\": 0.55,\n                    \"llm_enabled\": False,\n                    \"llm_provider\": \"opencode\",\n                    \"llm_command\": [\"opencode\", \"-m\", \"MiniMax M2.5 Free\"],\n                },\n            },\n            {\n                \"id\": \"job_consolidation_daily_15\",\n                \"job_type\": \"consolidation\",\n                \"cadence\": \"daily\",\n                \"interval_minutes\": None,\n                \"window_start\": \"15:00\",\n                \"window_end\": None,\n                \"metadata\": {\n                    \"mode\": \"daily_15\",\n                    \"candidate_age_days\": 7,\n                    \"max_candidates\": 200,\n                    \"dedupe_high_threshold\": 0.9,\n                    \"dedupe_mid_threshold\": 0.75,\n                    \"promote_confidence\": 0.7,\n                    \"conflict_threshold\": 0.55,\n                    \"llm_enabled\": False,\n                    \"llm_provider\": \"opencode\",\n                    \"llm_command\": [\"opencode\", \"-m\", \"MiniMax M2.5 Free\"],\n                },\n            },\n            {\n                \"id\": \"job_consolidation_weekly\",\n                \"job_type\": \"consolidation\",\n                \"cadence\": \"weekly\",\n                \"interval_minutes\": None,\n                \"window_start\": None,\n                \"window_end\": None,\n                \"metadata\": {\n                    \"mode\": \"weekly\",\n                    \"candidate_age_days\": 7,\n                    \"max_candidates\": 800,\n                    \"dedupe_high_threshold\": 0.9,\n                    \"dedupe_mid_threshold\": 0.75,\n                    \"promote_confidence\": 0.7,\n                    \"conflict_threshold\": 0.55,\n                    \"llm_enabled\": True,\n                    \"llm_provider\": \"opencode\",\n                    \"llm_command\": [\"opencode\", \"-m\", \"MiniMax M2.5 Free\"],\n                },\n            },\n        ]\n        with self.store.connection() as conn:\n            legacy = conn.execute(\"SELECT id FROM maintenance_jobs WHERE id = ?\", (\"job_consolidation_daily\",)).fetchone()\n            if legacy:\n                conn.execute(\n                    \"\"\"\n                    UPDATE maintenance_jobs\n                    SET enabled = 0, last_summary = ?, updated_at = ?\n                    WHERE id = ?\n                    \"\"\",\n                    (\"deprecated: split into 10:00 and 15:00 jobs\", utcnow(), \"job_consolidation_daily\"),\n                )\n            for job in defaults:\n                row = conn.execute(\"SELECT id FROM maintenance_jobs WHERE id = ?\", (job[\"id\"],)).fetchone()\n                if row:\n                    continue\n                now = utcnow()\n                next_due = self._compute_next_due(now, job[\"cadence\"], job[\"interval_minutes\"], job[\"window_start\"], job[\"window_end\"])\n                conn.execute(\n                    \"\"\"\n                    INSERT INTO maintenance_jobs (\n                        id, job_type, cadence, interval_minutes, window_start, window_end, next_due_at,\n                        last_run_at, last_status, last_summary, enabled, metadata_json, created_at, updated_at\n                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)\n                    \"\"\",\n                    (\n                        job[\"id\"],\n                        job[\"job_type\"],\n                        job[\"cadence\"],\n                        job[\"interval_minutes\"],\n                        job[\"window_start\"],\n                        job[\"window_end\"],\n                        next_due,\n                        None,\n                        None,\n                        None,\n                        1,\n                        self.store.dumps(job[\"metadata\"]),\n                        now,\n                        now,\n                    ),\n                )\n\n    def list_maintenance_jobs(self) -> list[dict[str, Any]]:\n        with self.store.connection() as conn:\n            rows = conn.execute(\"SELECT * FROM maintenance_jobs ORDER BY next_due_at ASC\").fetchall()\n            return [self._row_to_maintenance_job(row) for row in rows]\n\n    def list_due_maintenance_jobs(self, *, now: str | None = None, limit: int | None = None) -> list[dict[str, Any]]:\n        now = now or utcnow()\n        sql = \"SELECT * FROM maintenance_jobs WHERE enabled = 1 AND next_due_at <= ? ORDER BY next_due_at ASC\"\n        params: list[Any] = [now]\n        if limit is not None:\n            sql += \" 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_job(row) for row in rows]\n\n    def get_maintenance_job(self, job_id: str) -> dict[str, Any]:\n        with self.store.connection() as conn:\n            row = conn.execute(\"SELECT * FROM maintenance_jobs WHERE id = ?\", (job_id,)).fetchone()\n            if row is None:\n                raise KeyError(job_id)\n            return self._row_to_maintenance_job(row)\n\n    def update_maintenance_job(\n        self,\n        job_id: str,\n        *,\n        cadence: str | None = None,\n        interval_minutes: int | None = None,\n        window_start: str | None = None,\n        window_end: str | None = None,\n        next_due_at: str | None = None,\n        last_run_at: str | None = None,\n        last_status: str | None = None,\n        last_summary: str | None = None,\n        enabled: bool | None = None,\n        metadata: dict[str, Any] | None = None,\n    ) -> dict[str, Any]:\n        job = self.get_maintenance_job(job_id)\n        if cadence is not None:\n            job[\"cadence\"] = cadence\n        if interval_minutes is not None:\n            job[\"interval_minutes\"] = interval_minutes\n        if window_start is not None:\n            job[\"window_start\"] = window_start\n        if window_end is not None:\n            job[\"window_end\"] = window_end\n        if next_due_at is not None:\n            job[\"next_due_at\"] = next_due_at\n        if last_run_at is not None:\n            job[\"last_run_at\"] = last_run_at\n        if last_status is not None:\n            job[\"last_status\"] = last_status\n        if last_summary is not None:\n            job[\"last_summary\"] = last_summary\n        if enabled is not None:\n            job[\"enabled\"] = enabled\n        if metadata is not None:\n            job[\"metadata\"] = metadata\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                UPDATE maintenance_jobs\n                SET cadence = ?, interval_minutes = ?, window_start = ?, window_end = ?,\n                    next_due_at = ?, last_run_at = ?, last_status = ?, last_summary = ?, enabled = ?, metadata_json = ?, updated_at = ?\n                WHERE id = ?\n                \"\"\",\n                (\n                    job[\"cadence\"],\n                    job.get(\"interval_minutes\"),\n                    job.get(\"window_start\"),\n                    job.get(\"window_end\"),\n                    job[\"next_due_at\"],\n                    job.get(\"last_run_at\"),\n                    job.get(\"last_status\"),\n                    job.get(\"last_summary\"),\n                    1 if job.get(\"enabled\") else 0,\n                    self.store.dumps(job.get(\"metadata\") or {}),\n                    utcnow(),\n                    job_id,\n                ),\n            )\n        return self.get_maintenance_job(job_id)\n\n    def compute_next_due(\n        self,\n        *,\n        now: str | None = None,\n        cadence: str,\n        interval_minutes: int | None,\n        window_start: str | None,\n        window_end: str | None,\n    ) -> str:\n        return self._compute_next_due(\n            now or utcnow(),\n            cadence,\n            interval_minutes,\n            window_start,\n            window_end,\n        )\n\n    def create_maintenance_run(self, job_id: str) -> dict[str, Any]:\n        run_id = make_id(\"mrun\")\n        now = utcnow()\n        with self.store.connection() as conn:\n            conn.execute(\n                \"\"\"\n                INSERT INTO maintenance_runs (id, job_id, status, started_at, completed_at, summary, stats_json, error_message)\n                VALUES (?, ?, ?, ?, ?, ?, ?, ?)\n                \"\"\",\n                (run_id, job_id, \"running\", now, None, None, self.store.dumps({}), None),\n            )\n        return self.get_maintenance_run(run_id)\n\n    def finish_maintenance_run(\n        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\"]),\nfind: ‘/mnt/rpi/lost+found’: Permission denied
find: ‘/mnt/rpi/apt-cache/archives/partial’: Permission denied
        )\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    def _decode_embedding(self, embedding: str | None) -> list[float] | None:\n        if not embedding:\n            return None\n        return list(json.loads(embedding))\n\n    def _lexical_score(self, query_terms: list[str], haystack: str) -> float:\n        if not query_terms:\n            return 0.0\n        matches = sum(1 for term in query_terms if term in haystack)\n        return matches / len(query_terms)\n\n    def _text_embedding(self, text: str, dimensions: int = 8) -> list[float]:\n        vector = [0.0] * dimensions\n        for token in normalize_text(text).split():\n            for idx, char in enumerate(token.encode(\"utf-8\")):\n                vector[idx % dimensions] += float(char)\n        norm = math.sqrt(sum(value * value for value in vector))\n        if norm == 0:\n            return vector\n        return [value / norm for value in vector]\n\n    def _semantic_score(self, query_embedding: list[float], memory_embedding: list[float] | None) -> float:\n        if not query_embedding or memory_embedding is None:\n            return 0.0\n        numerator = sum(a * b for a, b in zip(query_embedding, memory_embedding))\n        return max(0.0, min(1.0, numerator))\n\n    def _table_exists(self, conn: Any, table: str) -> bool:\n        row = conn.execute(\"SELECT name FROM sqlite_master WHERE type = 'table' AND name = ?\", (table,)).fetchone()\n        return row is not None\n\n    def _count_if_table_exists(self, conn: Any, table: str) -> int:\n        if not self._table_exists(conn, table):\n            return 0\n        return conn.execute(f\"SELECT COUNT(*) AS count FROM {table}\").fetchone()[\"count\"]\n\n    def _compute_next_due(\n        self,\n        now: str,\n        cadence: str,\n        interval_minutes: int | None,\n        window_start: str | None,\n        window_end: str | None,\n    ) -> str:\n        base = datetime.fromisoformat(now)\n        if cadence == \"interval\" and interval_minutes:\n            return (base + timedelta(minutes=interval_minutes)).isoformat()\n        if cadence == \"weekly\":\n            target = base + timedelta(days=7)\n        else:\n            target = base + timedelta(days=1)\n        if window_start:\n            hour, minute = self._parse_hhmm(window_start)\n            target = target.replace(hour=hour, minute=minute, second=0, microsecond=0)\n        if window_end:\n            end_hour, end_minute = self._parse_hhmm(window_end)\n            end = target.replace(hour=end_hour, minute=end_minute, second=0, microsecond=0)\n            if target > end:\n                target = end\n        return target.isoformat()\n\n    def _parse_hhmm(self, value: str) -> tuple[int, int]:\n        parts = value.split(\":\")\n        if len(parts) != 2:\n            return (0, 0)\n        return (int(parts[0]), int(parts[1]))\n\n    def _link_memories(self, conn: Any, from_id: str, to_id: str, relation: str, reason: str) -> None:\n        conn.execute(\n            \"\"\"\n            INSERT INTO memory_links (id, from_memory_id, to_memory_id, relation, created_at, metadata_json)\n            VALUES (?, ?, ?, ?, ?, ?)\n            \"\"\",\n            (make_id(\"lnk\"), from_id, to_id, relation, utcnow(), self.store.dumps({\"reason\": reason})),\n        )\n\n    def _record_conflict(self, conn: Any, memory_id: str, conflicting_id: str, reason: str) -> None:\n        conn.execute(\n            \"\"\"\n            INSERT INTO memory_conflicts (id, memory_id, conflicting_memory_id, reason, created_at, metadata_json)\n            VALUES (?, ?, ?, ?, ?, ?)\n            \"\"\",\n            (make_id(\"mcf\"), memory_id, conflicting_id, reason, utcnow(), self.store.dumps({})),\n        )\n\n    def _conflict_signal(self, left: dict[str, Any], right: dict[str, Any]) -> bool:\n        allowed_types = {\"profile\", \"decision\", \"project\"}\n        if left.get(\"type\") not in allowed_types or right.get(\"type\") not in allowed_types:\n            return False\n        negations = {\"not\", \"no\", \"never\", \"nunca\", \"sin\"}\n        left_tokens = set(normalize_text(left[\"content\"]).split())\n        right_tokens = set(normalize_text(right[\"content\"]).split())\n        left_neg = bool(negations & left_tokens)\n        right_neg = bool(negations & right_tokens)\n        overlap = len(left_tokens & right_tokens)\n        return overlap >= 3 and left_neg != right_neg\n\n    def _llm_summarize_pair(\n        self,\n        left: dict[str, Any],\n        right: dict[str, Any],\n        *,\n        provider: str,\n        command: list[str],\n    ) -> str | None:\n        if provider != \"opencode\":\n            return None\n        prompt = (\n            \"Summarize and merge the two memory notes into one concise statement. Preserve key facts and avoid speculation.\\n\\n\"\n            f\"Memory A:\\n{left['content']}\\n\\nMemory B:\\n{right['content']}\\n\"\n        )\n        try:\n            result = subprocess.run(\n                command,\n                input=prompt,\n                text=True,\n                capture_output=True,\n                timeout=60,\n                check=False,\n            )\n            if result.returncode != 0:\n                return None\n            output = result.stdout.strip()\n            return output or None\n        except Exception:\n            return None\n",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package.json:3:    "@whisperopencode/push": "^0.3.0"
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:8:        "@whisperopencode/push": "^0.3.0"
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:11:    "node_modules/@opencode-ai/plugin": {
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:13:      "resolved": "https://registry.npmjs.org/@opencode-ai/plugin/-/plugin-1.2.21.tgz",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:17:        "@opencode-ai/sdk": "1.2.21",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:21:    "node_modules/@opencode-ai/sdk": {
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:23:      "resolved": "https://registry.npmjs.org/@opencode-ai/sdk/-/sdk-1.2.21.tgz",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:27:    "node_modules/@whisperopencode/push": {
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:29:      "resolved": "https://registry.npmjs.org/@whisperopencode/push/-/push-0.3.0.tgz",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:33:        "@opencode-ai/plugin": "1.2.21",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:34:        "@opencode-ai/sdk": "1.2.21",
/mnt/rpi/home-cache/sebas/.npm/_npx/eea16ca70622d4cb/package-lock.json:38:        "opencode-push": "dist/src/cli.js"
/mnt/rpi/pi-config/README.md:35:- `/opencode` → redirect to `http://ballbox-first.emperor-ratio.ts.net:8443/`
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/docs/plans/package-json-fix.md:51:    "opencode",
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/CHANGELOG.md:56:  - Set `OPENCODE_GO_API_KEY` or `opencode_go_api_key` in `~/.pi/free.json`
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/CHANGELOG.md:71:- Added `opencode_go_api_key` to config file template
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/README.md:318:Set `OPENCODE_GO_API_KEY` (or `opencode_go_api_key` in `~/.pi/free.json`) and `GO_SHOW_PAID=true` to enable.
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/README.md:328:**Pricing:** $5 first month, then $10/month. See [opencode.ai/docs/go](https://opencode.ai/docs/go).
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/README.md:390:  "opencode_api_key": "YOUR_ZEN_KEY",
/mnt/rpi/pi-config/git/github.com/apmantza/pi-free/README.md:391:  "opencode_go_api_key": "YOUR_GO_KEY",
/mnt/rpi/repos/ballbox/.github/workflows/opencode.yml:1:name: opencode
/mnt/rpi/repos/ballbox/.github/workflows/opencode.yml:10:  opencode:
/mnt/rpi/repos/ballbox/.github/workflows/opencode.yml:11:    if: contains(github.event.comment.body, '/oc') || contains(github.event.comment.body, '/opencode')
/mnt/rpi/repos/ballbox/.github/workflows/opencode.yml:45:        uses: anomalyco/opencode/github@latest
/mnt/rpi/repos/ballbox/.github/workflows/opencode.yml:49:          model: opencode/gpt-5-nano
/mnt/rpi/repos/FelipeVersion/.github/workflows/opencode.yml:1:name: opencode
/mnt/rpi/repos/FelipeVersion/.github/workflows/opencode.yml:10:  opencode:
/mnt/rpi/repos/FelipeVersion/.github/workflows/opencode.yml:11:    if: contains(github.event.comment.body, '/oc') || contains(github.event.comment.body, '/opencode')
/mnt/rpi/repos/FelipeVersion/.github/workflows/opencode.yml:45:        uses: anomalyco/opencode/github@latest
/mnt/rpi/repos/FelipeVersion/.github/workflows/opencode.yml:49:          model: opencode/gpt-5-nano
/mnt/rpi/repos/opencode-harness/scripts/install-opencode.sh:4:REPO_DEFAULT="sebasfavaron/opencode-harness"
/mnt/rpi/repos/opencode-harness/scripts/install-opencode.sh:16:OPENCODE_DIR="${HOME}/.config/opencode"
/mnt/rpi/repos/opencode-harness/scripts/install-opencode.sh:21:MANAGED_STATE_DIR="${HOME}/.agents/opencode-harness-install"
/mnt/rpi/repos/opencode-harness/scripts/install-opencode.sh:109:    ln -s "$LOCAL_PATH/config/opencode/AGENTS.md" "$RULES_FILE"
/mnt/rpi/repos/opencode-harness/scripts/install-opencode.sh:144:  fetch_file "$RAW_BASE/config/opencode/AGENTS.md" "$RULES_FILE"
/mnt/rpi/repos/opencode-harness/docs/services-architecture.md:12:| `https://ballbox-first.emperor-ratio.ts.net:8443/` | `:3967` (opencode web) | OpenCode Web UI |
/mnt/rpi/repos/opencode-harness/docs/services-architecture.md:20:| `:3967` | opencode web | UI de OpenCode |
/mnt/rpi/repos/opencode-harness/config/opencode/AGENTS.md:9:- installer writes this file to ~/AGENTS.md and symlinks ~/.config/opencode/AGENTS.md
/mnt/rpi/repos/opencode-harness/INSTALL.md:30:git clone https://github.com/sebasfavaron/opencode-harness.git
/mnt/rpi/repos/opencode-harness/INSTALL.md:91:curl -fsSL https://raw.githubusercontent.com/sebasfavaron/opencode-harness/main/scripts/install-opencode.sh | sh
/mnt/rpi/repos/opencode-harness/INSTALL.md:97:curl -fsSL https://raw.githubusercontent.com/sebasfavaron/opencode-harness/main/scripts/install-opencode.sh | sh -s -- restore
/mnt/rpi/repos/opencode-harness/INSTALL.md:127:- the OpenCode installer overwrites managed entries under `~/.agents/skills` and `~/AGENTS.md` (and symlinks `~/.config/opencode/AGENTS.md`)
/mnt/rpi/repos/opencode-harness/INSTALL.md:128:- managed skill backups are saved to `~/.agents/skills-backups/<skill>`; rule backups are saved to `~/AGENTS.md.bck` and `~/.config/opencode/AGENTS.md.bck`
/mnt/rpi/repos/opencode-harness/INSTALL.md:129:- `opencode` and `curl` must be on your `PATH`
/mnt/rpi/repos/opencode-harness/scripts/run-server-daemon.sh:8:export PATH="${HOME}/.opencode/bin:${HOME}/.npm-global/bin:/opt/homebrew/bin:/usr/local/bin:/usr/bin:/bin:${PATH}"
/mnt/rpi/repos/opencode-harness/scripts/run-server-daemon.sh:16:  PERSONAL_AGENT_RUNNER_BIN="$(command -v opencode || true)"
/mnt/rpi/repos/opencode-harness/scripts/run-server-daemon.sh:20:  echo "opencode not found on PATH" >&2
/mnt/rpi/repos/opencode-harness/README.md:1:# opencode-harness
/mnt/rpi/repos/opencode-harness/README.md:19:`opencode-harness` now grows toward a front-door runtime:
/mnt/rpi/repos/opencode-harness/README.md:53:- `memory-migrate` rewrites legacy opencode-harness metadata into the canonical shared-memory schema
/mnt/rpi/repos/opencode-harness/README.md:83:`opencode-harness` is the intended front door.
/mnt/rpi/repos/opencode-harness/README.md:93:opencode-harness/
/mnt/rpi/repos/opencode-harness/README.md:148:- `scripts/install-opencode.sh` installs skills + OpenCode rules without cloning (see INSTALL.md)
/mnt/rpi/repos/opencode-harness/AGENTS.md:28:- Codex launch convention for opencode-harness work that must write shared DB: add `--add-dir ~/agents-database` so sandboxed runs can edit the canonical DB in-repo
/mnt/rpi/repos/opencode-harness/docs/system-v1.md:89:   - run `~/personal-agent/scripts/install-opencode.sh`


/home/sebas/.config/opencode:
total 52
drwxr-xr-x  4 sebas sebas  4096 Apr 16 21:42 .
drwx------ 19 sebas sebas  4096 Apr 18 16:22 ..
lrwxrwxrwx  1 sebas sebas    21 Apr 14 22:59 AGENTS.md -> /home/sebas/AGENTS.md
lrwxrwxrwx  1 sebas sebas    21 Apr 11 16:22 AGENTS.md.bck -> /home/sebas/AGENTS.md
-rw-r--r--  1 sebas sebas   844 Mar 30 10:19 bun.lock
-rw-r--r--  1 sebas sebas  4095 Apr 20 18:45 config.json
-rw-r--r--  1 sebas sebas    45 Mar 18 15:07 .gitignore
drwxrwxr-x 27 sebas sebas  4096 Apr 16 21:43 node_modules
-rw-r--r--  1 sebas sebas  4095 Apr 20 18:46 opencode.json
-rw-r--r--  1 sebas sebas    62 Apr 15 10:33 package.json
-rw-r--r--  1 sebas sebas 13548 Apr 16 21:43 package-lock.json
drwxrwxr-x  2 sebas sebas  4096 Apr 15 12:08 rules

/home/sebas/.local/share/opencode:
total 50888
drwxr-xr-x  6 sebas sebas     4096 Apr 16 22:31 .
drwx------ 13 sebas sebas     4096 Apr 18 16:22 ..
-rw-------  1 sebas sebas     2154 Apr  9 23:55 auth.json
drwxr-xr-x  2 sebas sebas     4096 Apr 16 21:40 bin
lrwxrwxrwx  1 sebas sebas       38 Apr 14 12:54 log -> /mnt/rpi/home-cache/sebas/opencode/log
-rw-r--r--  1 sebas sebas 52023296 Apr 16 22:38 opencode.db
-rw-r--r--  1 sebas sebas    32768 Apr 16 22:38 opencode.db-shm
-rw-r--r--  1 sebas sebas    16512 Apr 16 22:38 opencode.db-wal
drwxr-xr-x  6 sebas sebas     4096 Mar 30 10:23 snapshot
drwxr-xr-x  3 sebas sebas     4096 Mar 18 16:43 storage
drwxr-xr-x  2 sebas sebas     4096 Apr 21 00:39 tool-output

/home/sebas/.opencode:
total 44
drwxr-xr-x   4 sebas sebas  4096 Apr 16 21:42 .
drwx--x---+ 36 sebas sebas  4096 Apr 21 10:09 ..
drwxr-xr-x   2 sebas sebas  4096 Apr 15 09:23 bin
-rw-r--r--   1 sebas sebas   844 Mar 30 10:19 bun.lock
-rw-r--r--   1 sebas sebas    45 Mar 18 15:07 .gitignore
drwxrwxr-x  27 sebas sebas  4096 Apr 16 21:43 node_modules
-rw-r--r--   1 sebas sebas    62 Apr 15 10:33 package.json
-rw-r--r--   1 sebas sebas 13549 Apr 16 21:43 package-lock.json


**Assessing reference removal impacts**

I need to determine the impact of breaking references, particularly in the pi-config README. It seems the opencode-harness project might have some references that shouldn’t be removed. The user has asked about the current setup, so I need to warn that removing certain elements could break documentation but not necessarily the setup itself.

I think it's best to avoid altering historical project repositories unless the user specifically requests broader cleanup. I also need to check the pi-config README for details.