[telegram] se puede hacer un Dry Run a las memorias existentes sin ver la sesion, en cambio solo viendo la memoria?


**Considering memory capabilities**

I think the user is asking for an answer that's conceptual, possibly related to agents and memory reading. I might want to check what I can do in terms of memory skills. Perhaps I can respond with a straightforward yes or no, but I’ll also include some necessary caveats. It's also important to note that the user’s question is in Spanish, so I need to keep my response concise.

Sí, pero con límites.

Se puede hacer un dry run basado solo en memorias:
- buscar memorias relevantes
- reconstruir contexto probable
- proponer acciones, riesgos, y próximos pasos
- detectar huecos o contradicciones

No se puede garantizar lo mismo que viendo la sesión completa:
- falta intención exacta del momento
- faltan matices, descartes, y cambios de rumbo
- una memoria puede estar resumida, sesgada, o vieja

Regla práctica:
- si querés continuidad operativa: memoria sola suele alcanzar
- si querés auditoría fina o reproducir decisiones: no alcanza, mejor sesión + memoria

Puedo trabajar en 3 modos:
1. solo memoria
2. memoria + artifacts
3. memoria + sesión completa

Si querés, te armo el dry run ideal “solo memoria” y qué datos mínimos tendría que tener cada memoria para que sirva bien.


[telegram] solo quiero consolidar memorias previas con la nueva heuristica, pero haciendo un dry run primero


**Considering memory consolidation**

It looks like the user wants to consolidate old memories with a new heuristic. I think I should first clarify their request. I can confidently say that yes, I can help with this! I should mention my approach and suggest a plan, possibly asking for their confirmation since it may involve reading the memory database, but a dry run would not include any writes. Also, I might consider using a memory-read skill if necessary, but just answering might be sufficient.

Sí.

Plan seguro:
1. leer memorias existentes
2. aplicar nueva heurística en modo dry run
3. mostrar diff lógico, sin escribir nada:
   - qué memorias quedan
   - cuáles fusionar
   - cuáles borrar/no migrar
   - cuáles re-tipar
   - cuáles reescribir
4. si aprobás, recién ahí consolidar de verdad

Dry run puede devolver algo así:
- `keep`
- `merge_into`
- `rewrite`
- `drop`
- `needs_human_decision`

También puedo marcar:
- ruido
- duplicados
- memorias viejas pero útiles
- memorias que hoy violan la heurística

Si querés, lo hago así:
- alcance: todas las memorias tuyas, o solo de un proyecto/repo
- salida: reporte corto, sin cambios

Decime:
- `todas`
- `solo proyecto X`
- `solo repo Y`


[telegram] si. one time asi que no es codigo que tiene que persistir. hacelo para todas


**Considering task execution**

I see that I need to use my memory-read skill for this task. Maybe there's no need to ask further questions. I should search through memories using the API. Additionally, it seems I might need to create a to-do for better organization. I wonder if I could use a bash curl command for this? I think inspecting the skill will be helpful too. Let's get started!

todo

Dry run consolidate all memories with new heuristic

Read all existing memories, apply current consolidation heuristic without writing changes, and report keep/merge/rewrite/drop recommendations across all memories.


Created #1: Dry run consolidate all memories with new heuristic (pending)


---
name: memory-read
description: Read persisted research memory, claims, and tasks
---

# personal-memory-search

## Workflow

1. Execute:
   - `curl -fsSL "${AGENTS_DB_API:-http://100.116.176.16:8091}/api/search?q=<query>&scope=global&scope=project&limit=20"`
2. Return matching runs, claims, and tasks from the JSON response.
3. Prefer reuse of prior work before starting a new run.


**Considering search options**

I think I might need heuristic docs for guidance. Searching for “AGENTS” could be potentially sufficient too. I’ll need to fetch all memories and inspect the API to see if I can search everything. It’s possible there’s no direct endpoint available. Maybe using an empty query could work, so I’ll give that a test run to see if it yields any results. Let’s see what I can find!

bash

python - <<'PY'
import urllib.parse, subprocess
base='http://100.116.176.16:8091'
for q in ['', '*', 'a']:
    url=f"{base}/api/search?q={urllib.parse.quote(q)}&scope=global&scope=project&limit=3"
    print('URL',url)
    r=subprocess.run(['curl','-fsSL',url],capture_output=True,text=True)
    print('code',r.returncode)
    print(r.stdout[:400])
    print(r.stderr)
PY


URL http://100.116.176.16:8091/api/search?q=&scope=global&scope=project&limit=3
code 22

curl: (22) The requested URL returned error: 400

URL http://100.116.176.16:8091/api/search?q=%2A&scope=global&scope=project&limit=3
code 0
{"retrieval_id": "ret_c62f01fa8a5946c49263cd34fca2b86a", "results": [{"memory": {"id": "mem_cda20c374a614e6ca531f9e9e121c5bd", "type": "project", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Laptop helpers use dedicated SSH key on port 2222", "content": "Configured laptop access to avoid expiring Tailscale SSH brow

URL http://100.116.176.16:8091/api/search?q=a&scope=global&scope=project&limit=3
code 0
{"retrieval_id": "ret_b8064465f7e94c1aadcc93753f50c682", "results": [{"memory": {"id": "legacy_task_12", "type": "task_hint", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Legacy task: Build a shortlist", "content": "Build a shortlist\nkind=task\nstatus=open\nnotes=", "summary": "Build a shortlist", "confidence": 0.


**Exploring memory retrieval**

I'm considering how to retrieve all memories effectively. It seems like I need to set a query with a limit, maybe around 1000? Pagination could be essential here, depending on how large the dataset is. I should inspect the structure to see how I can count them accurately, which might help in understanding the overall number of memories I can work with. Let's figure this out step by step!

python - <<'PY'
import requests, json
url='http://100.116.176.16:8091/api/search?q=*&scope=global&scope=project&limit=500'
r=requests.get(url,timeout=30)
print(r.status_code)
data=r.json()
print(data.keys())
print('results',len(data.get('results',[])))
print('first keys',data['results'][0].keys())
print('memory keys',data['results'][0]['memory'].keys())
PY


200
dict_keys(['retrieval_id', 'results'])
results 200
first keys dict_keys(['memory', 'score', 'score_breakdown', 'matched_scope', 'evidence_ref', 'explanation'])
memory keys dict_keys(['id', 'type', 'scope', 'status', 'project_id', 'repo_id', 'agent_id', 'source_kind', 'title', 'content', 'summary', 'confidence', 'freshness', 'created_at', 'updated_at', 'observed_at', 'source_ref', 'evidence_ref', 'schema_version', 'subtype', 'run_id', 'task_id', 'url', 'domain', 'origin_agent', 'metadata', 'embedding'])


python - <<'PY'
import requests,string
base='http://100.116.176.16:8091/api/search?scope=global&scope=project&limit=200&q='
queries=['*']+list('etaoinshrdlucmfwypvbgkjqxz')
seen={}
for q in queries:
    url=base+requests.utils.quote(q,safe='')
    r=requests.get(url,timeout=30)
    if r.status_code!=200:
        print('bad',q,r.status_code)
        continue
    data=r.json()['results']
    for item in data:
        seen[item['memory']['id']]=item['memory']
    print(q,len(data),len(seen))
print('total unique',len(seen))
PY


* 200 200
e 200 213
t 200 213
a 200 213
o 200 213
i 200 214
n 200 214
s 200 214
h 200 228
r 200 228
d 200 228
l 200 228
u 200 228
c 200 228
m 200 228
f 200 233
w 200 275
y 200 275
p 200 275
v 200 277
b 200 277
g 200 277
k 200 278
j 200 290
q 200 300
x 200 302
z 200 302
total unique 302


**Considering memory organization**

I might need to gather more memories, possibly using 2-letter combos, but that could be overkill. It feels like I should do a dry run, likely around 302 unique entries, focusing on active ones. I'll fetch a unique set through multiple queries and classify them based on a new heuristic. It's important to understand the specifics of the heuristic from AGENTS. I want to stick with fewer high-signal types and avoid trivia or secrets while analyzing memory titles and content. Finally, I plan to export the dataset.

python - <<'PY'
import requests, json, itertools, string, os
queries=['*']+list('etaoinshrdlucmfwypvbgkjqxz0123456789_-')
seen={}
for q in queries:
    url='http://100.116.176.16:8091/api/search?scope=global&scope=project&limit=200&q='+requests.utils.quote(q,safe='')
    r=requests.get(url,timeout=30)
    if r.status_code!=200:
        continue
    for item in r.json()['results']:
        m=item['memory']
        seen[m['id']]=m
path='/tmp/memory_dryrun_all.json'
with open(path,'w') as f:
    json.dump(list(seen.values()),f,indent=2)
print(path, len(seen))
PY


/tmp/memory_dryrun_all.json 304


python - <<'PY'
import json, collections
mems=json.load(open('/tmp/memory_dryrun_all.json'))
print('count',len(mems))
print('types',collections.Counter(m['type'] for m in mems).most_common())
print('scopes',collections.Counter(m['scope'] for m in mems).most_common())
print('status',collections.Counter(m['status'] for m in mems).most_common())
print('source_kind',collections.Counter(m['source_kind'] for m in mems).most_common(10))
PY


count 304
types [('task_hint', 83), ('episode', 63), ('artifact', 56), ('profile', 39), ('decision', 29), ('project', 27), ('procedural', 4), ('task', 3)]
scopes [('global', 249), ('project', 55)]
status [('active', 304)]
source_kind [('manual', 268), ('document', 22), ('run', 14)]


**Considering duplicates and clustering**

I think I need to identify duplicates or clusters among items. To do this, using heuristics based on title similarity seems like a good approach. A concise report would be helpful, I guess. I could utilize an LLM via a subagent or consider Python clustering methods. It might be useful to read through the list first, particularly inspecting the top entries along with their IDs and titles for better clarity.

python - <<'PY'
import json
mems=json.load(open('/tmp/memory_dryrun_all.json'))
for m in sorted(mems,key=lambda x:(x['type'],x['updated_at'] or ''))[:120]:
    print(f"{m['id']}\t{m['type']}\t{m['scope']}\t{m['title']}")
PY


mem_24cdae17a688446c970b0a5875e2d2e7	artifact	project	Ballbox company-agent write-path check
mem_5895611b217c4c5db83b7aa9e7399e1e	artifact	global	pi-extension-search skill
mem_adb8071246734b2bb4209f1bf260ae18	artifact	global	pi-tau-mux hardcodes session path
legacy_source_9fdccb34-cf1e-47bd-b133-a224f363a6d4_2baeb052be7182e4	artifact	global	Example source
legacy_source_a8512264-8cd5-4c3c-b62f-7528625227f1_9cd66d7ad4f9c491	artifact	global	Capture Verification
legacy_source_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_d888111349c5949c	artifact	global	HDFocus 55-inch outdoor weatherproof digital signage
legacy_source_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_329a120b76e7014f	artifact	global	Genevision 55-inch floor standing Android signage
legacy_source_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_c68708b376f2850c	artifact	global	WSC 55-inch outdoor floor standing signage
legacy_source_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_03ec74fd2f55f797	artifact	global	Made-in-China outdoor digital signage category
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_b928c046ef9e26cc	artifact	global	Implementing the Full-Screen Experience
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_d400e6d93b89520c	artifact	global	Hammerspoon hs.hotkey
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_6830f94c80239b4d	artifact	global	Hammerspoon hs.webview
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_7c9cff2a855c52be	artifact	global	Raycast AI manual
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_c979d84b00dff9b4	artifact	global	NSWindow.CollectionBehavior.canJoinAllSpaces
legacy_source_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_4a862723e6f3473f	artifact	global	Raycast hotkey
legacy_source_35bd54a1-0135-414e-9c6b-245fca772f54_d6271ff907c7638c	artifact	global	mercadoPagoProvider.ts
legacy_source_35bd54a1-0135-414e-9c6b-245fca772f54_64db63db4f1f1839	artifact	global	ballbox-payment-integration PLAN.md
legacy_source_35bd54a1-0135-414e-9c6b-245fca772f54_60c56c6672d7e2ac	artifact	global	webhook.ts
legacy_source_35bd54a1-0135-414e-9c6b-245fca772f54_c24504bb7770e471	artifact	global	index.ts
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_84b4fd9c44d3870e	artifact	global	GitHub org API metadata for Trading-Mastery
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_87caadc0f912376f	artifact	global	Trading Mastery GitHub organization
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_312775bdd9d78b3d	artifact	global	Trading Mastery go subdomain
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_e9c80596a94bd14d	artifact	global	Trading Mastery Knowledge Centre
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_17e59f8b76b3dce1	artifact	global	Trading Mastery Contact Us
legacy_source_7e6517b3-759f-4063-8d98-121d9cba45c5_b9fb886bdcf19255	artifact	global	Trading Mastery About Us
legacy_claim_9fdccb34-cf1e-47bd-b133-a224f363a6d4_782d8169bfd49348	artifact	global	Research claim: Personal assistants are trending toward local memory plus explicit approval gate
legacy_claim_55b6eaa0-9ff5-438c-a375-50f0452079cb_94c9a4ce114180c3	artifact	global	Research claim: Current ballbox-payment-integration repo is directionally aligned with a vending
legacy_claim_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_debf10ea226a73ff	artifact	global	Research claim: There are multiple 55-inch China-sourced digital signage options already markete
legacy_claim_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_c8f1da6eb425ce87	artifact	global	Research claim: Made-in-China currently lists multiple outdoor Android/high-brightness signage v
legacy_claim_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7_7e34ebfab9d62f01	artifact	global	Research claim: For padel venues with direct sunlight or semi-outdoor placement, 1000-2500 nit o
legacy_claim_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_3b87a932d99841c5	artifact	global	Research claim: macOS fullscreen mueve la ventana principal a un Space separado; para convivir c
legacy_claim_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_a7cb56ffe7c78e19	artifact	global	Research claim: BetterTouchTool permite atajos globales, HUD overlays y floating menus/webviews
legacy_claim_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_f579bd685e817963	artifact	global	Research claim: Raycast ya resuelve el trigger global y se superpone sobre la app actual; AI Cha
legacy_claim_fbe3fc0d-b05c-455e-9afe-1b17b4640d97_3a9bccf15163d7e1	artifact	global	Research claim: Hammerspoon expone hotkeys globales y webviews transparentes con control de leve
legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_fdb013b190e6349a	artifact	global	Research claim: The repo is buildable and passes its current local verification gate, but that g
legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_633b0b4d6c71078d	artifact	global	Research claim: MercadoPago production integration is not yet production-safe because the real a
legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_c6796a97908c5d93	artifact	global	Research claim: Webhook authenticity is not enforced correctly today because signature verificat
legacy_claim_35bd54a1-0135-414e-9c6b-245fca772f54_5aac99d0b141d8cf	artifact	global	Research claim: A first production rollout depends on external contract discovery because the re
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_0c62c2e2636ef4cc	artifact	global	Research claim: Trading-Mastery is a real public GitHub organization account created on 2024-09-
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_a3fa0782e023b5b6	artifact	global	Research claim: Trading Mastery operates a public website at tradingmastery.com.au and presents
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_f211af78097e660e	artifact	global	Research claim: A private repository named Trading Mastery backend is plausible given the org ha
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_abe00dfd75ddd023	artifact	global	Research claim: The official Trading Mastery site publicly exposes company/contact details inclu
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_2308932b1580ee98	artifact	global	Research claim: There are at least two additional web application surfaces under the same brand:
legacy_claim_7e6517b3-759f-4063-8d98-121d9cba45c5_b6e2f67601e668f2	artifact	global	Research claim: The GitHub organization is likely related to the tradingmastery.com.au business
legacy_claim_73698c1a-612d-456d-b178-6286ae9ab9cd_ea83fb560563f112	artifact	global	Research claim: Sebas said main is already connected for street-cast-pwa.
legacy_claim_73698c1a-612d-456d-b178-6286ae9ab9cd_2cb5bb444cc49676	artifact	global	Research claim: Sebas said main is already connected for street-cast-server.
legacy_claim_73698c1a-612d-456d-b178-6286ae9ab9cd_153d4bcd9fffe7e9	artifact	global	Research claim: When Sebas shares notable facts about himself or his projects, persist them in l
mem_3c62253993584122a81f9a21de4acc33	artifact	global	ballbox-first microSD migration handoff
mem_d476503aedfa452cb0be0a7d8a6087cb	artifact	global	Home domotics controllability baseline on ballbox-first
mem_541c5ade3b7141d28217b30d48da4e83	artifact	global	High-value home paths found on root
mem_92e6e50e73a546c39c04cfbb2c58c1d5	artifact	project	Session memory job artifacts live under pi-config session-memory-jobs
mem_4d067cc96f424bd2926982bf02107663	artifact	project	pi-job script path works from /home/sebas/pi-config
mem_a0882b18483d4f4f99913e28c69c06e0	artifact	project	OPS-1 docs and evidence trail should be recorded in plan/queue/docs
mem_7241420239534c22be6b71d3588ca81f	artifact	global	agents-database status endpoint
mem_3032f881e65c43da946671e4bfd6f3c5	artifact	global	Compact task kickoff template
mem_8517007aa63c464c9b84431f6562769a	artifact	project	OurVend FTP host is cloud infra, not machine access
mem_ballbox_atc_constraint	decision	project	Ballbox ATC association constraint
mem_ballbox_alias_resolution_rule	decision	project	Ballbox alias resolution rule for Volvox mentions
mem_sebas_confirm_irreversible_actions	decision	global	Require confirmation for irreversible actions
mem_ballbox_success_metric_6m	decision	project	Ballbox success criteria for next 3 to 6 months
mem_ballbox_cost_over_elegance	decision	project	Ballbox decision priority: cost and business impact over elegance
mem_sebas_uncertainty_policy_question_then_execute	decision	global	Sebas uncertainty handling preference
mem_sebas_name_disambiguation_two_sebastians	decision	global	Disambiguation rule for two Sebastians in Ballbox context
mem_sebas_non_negotiable_relationships	decision	global	Sebas non-negotiable: interpersonal relationships
mem_v1_legacy_bridge_status	decision	project	V1 legacy bridge policy
mem_codex_add_dir_agents_database	decision	project	Codex should launch with agents-database as writable extra dir
mem_runtime_agentic_refactor_priority	decision	project	Refactor runtime toward Codex-agentic orchestration
mem_phase2_agentic_runtime_task_eaf005df03fb441ab2b84df7ea05178d	decision	project	Phase 2 runtime continuation package
mem_6b468c8ed38a488392762d473ab20904	decision	project	TCN buyer QR uses on-screen display, not scanner hardware
mem_de96b3b04d544628b1ab1f6a33d270c8	decision	project	First machine rollout uses Ballbox and tenant collection modes
mem_94ec049a0b6345ad9e54746c62a51908	decision	global	Native tmux pi batch jobs for one-prompt subagents
mem_ebbca254ff484623b6d63073ee758d8d	decision	global	pi-tau-mux stale ctx fix in tau-client
mem_90f4bcce6d284ed0b6f6edb9a6ec6cc2	decision	global	Prefer session-end memory writes
mem_b161e2e3072a49099cabb17193a4fb15	decision	global	Server-side SSH idle timeout set to 4h
mem_02a8d3bf9ae04a85aa700eb4d5c045e9	decision	project	Prefer native tmux + pi sessions over the agent-start extension for side-agent workflows
mem_c636b2dc79794c57aded818ba6fdae2f	decision	project	Replace agent-start extension with native tmux+pi workflow
mem_fb6b4fa0a1534849a15949e2f17dc364	decision	global	ballbox-first uses home-first agent layout
mem_fc344ecfd47a4f1cb669306f791a26f1	decision	project	BB-004 EPUB-first offline pack
mem_b1fe3f813e97480487d2bae29b0a8418	decision	project	Vending web v1 scope and test notification
mem_caa17fc9013941b08d40188047b0958d	decision	project	Ballbox accessibility should follow html-first in Next
mem_2f2c6741e5994563ac317c35c2de5093	decision	project	OPS-1 validated only after real production payment flow completes
mem_b7c29c94c9aa44448e1a043e2740ab87	decision	project	Fix provider auth before validating memory ingest end-to-end
mem_5a157e5a8f1948899b22aaefe5f2d658	decision	global	Agent doctrine shifted toward completeness and validation
mem_276ab55db95f48ee93012e6a689cc289	decision	project	Ballbox TCN payment reality 2026-05-26
mem_4870951158a94c72ac1dd324c720731e	decision	project	rss-offline PDF uses reader-style print layout
mem_ballbox_summary_snapshot	episode	project	Ballbox snapshot March 2026
mem_v1_multi_repo_cross_reference	episode	project	V1 multi-repo cross-reference
legacy_run_9fdccb34-cf1e-47bd-b133-a224f363a6d4	episode	global	Research run: Investigate personal assistant patterns
legacy_run_a8512264-8cd5-4c3c-b62f-7528625227f1	episode	global	Research run: Verify capture-url flow
legacy_run_55b6eaa0-9ff5-438c-a375-50f0452079cb	episode	global	Research run: Drive Ballbox payment integration toward Volvox-style demo on vending machine Android flow
legacy_run_bfe3ad5d-ed7c-4727-bd72-7b9f5b7b0cc7	episode	global	Research run: Source 50+ inch China displays for Ballbox advertising in padel venues
legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0	episode	global	Research run: Test intake flow
legacy_run_b07bc538-5cab-4243-a1d3-c7a7fa55a0a7	episode	global	Research run: Drive ballbox-payment-integration to a demoable vending-machine QR payment flow
legacy_run_2c54c32b-3cf1-426b-98a6-9c43971573ff	episode	global	Research run: Find China-sourced 50+ inch displays for Ballbox advertising in covered padel clubs
legacy_run_fbe3fc0d-b05c-455e-9afe-1b17b4640d97	episode	global	Research run: Responder a Codex sin salir de una película en fullscreen, con UI mínima y poco intrusiva, y evaluar cómo implementarlo
legacy_run_a7fe5fbd-4892-4398-ab1a-71337f923ed7	episode	global	Research run: Analyze the best next steps to make ballbox-payment-integration production-ready
legacy_run_35bd54a1-0135-414e-9c6b-245fca772f54	episode	global	Research run: Production-readiness plan for ballbox-payment-integration
legacy_run_1f1a3fd4-eb28-4e99-891f-07c97243a06f	episode	global	Research run: Produce a production-readiness plan for ballbox-payment-integration
legacy_run_7e6517b3-759f-4063-8d98-121d9cba45c5	episode	global	Research run: Find online references for the GitHub organization Trading-Mastery
legacy_run_b12b10fb-c56e-4774-aaa6-c2088b2668ab	episode	global	Research run: Map named individuals to Humand engineering via public references
legacy_run_73698c1a-612d-456d-b178-6286ae9ab9cd	episode	global	Research run: Persist user/project facts from chat
mem_6485e21fbc354ebf98cea3fa5a1cc6e6	episode	global	agents-database maintenance wrapper fix
mem_4b3428254ffb442ca1762d1a5895100d	episode	global	Installed Vibes on ballbox-first
mem_2547c456e8d845ffad407ad5b606e24a	episode	project	rss-offline PDF pack stabilized for iPhone test
mem_250c2415e6cb4560a45ffc165052aed6	episode	global	Linux update space-recovery pass
mem_648aa9d0224b46fe85ebc08e41f75835	episode	global	Need to estimate memory yield from missed session-end hooks
mem_194dd7c3ce7941b7ae6b0ae57f28caac	episode	project	pi-job hello smoke test succeeded
mem_c8c7e1c8af7d4665aafe58baca242345	episode	global	Removed SSH session timeout at user request
mem_29757fd2758842dc9c3c0ae699258d79	episode	project	OPS-1 was still pending real production evidence at session time
mem_3b089c54e76d4a79a5bb8836551e9571	episode	global	Memory ingestion likely undercounts low-quality candidates
mem_7b096c8a2fca4c7ea123d778c32ef3ad	episode	global	Telegram session was probed with greetings and /new
mem_d3883db57b314d16a16355876dca66cc	episode	global	Requested delegated research handoff for free-model fallback
mem_c80220ae1130409b913a394727059731	episode	project	ballbox: ¿Qué herramientas tenemos hoy para navegar Internet?
mem_6831b78c9c964e3fb9db0c43afa2dfec	episode	global	sebas: Actualiza el agent dorandí que diga evitar a toda costa repetirse. Esto…
mem_282e57f1ffe6455e82fbe4d184445f2c	episode	global	sebas: [telegram] alo
mem_de64feafc920451eaa0c25ee1666f4af	episode	global	sebas: [telegram] start backlog tasks in parallel. ask them to run as much as…
mem_5764c637222e487cafc71928884bc1d5	episode	global	sebas: [telegram] Dame el link Arrival Guide que había creado para cuando lleg…
mem_af7ad5e49a1b4f4e92064fcfe9028efa	episode	global	sebas: [telegram] guarda en raw mis gastos europa (imagenes + texto extraido)…
mem_c765760853224345940d788c503b32d7	episode	global	sebas: [telegram] saca el proyecto freshrss (codigo, docs, links, todo) y para…
mem_a1f632320762487c8864dd45f2cbf394	episode	global	sebas: [telegram] hazme en inglés, un texto explicando con flechas, el flujo m…


**Considering analysis needs**

I’m thinking I need to improve my analysis, particularly by identifying any low-quality drops that are obvious. It might help to have more lines, maybe a look at different profiles, projects, or tasks. I could create a report file to organize my findings. Plus, I should inspect the profile titles to see if there’s anything that stands out or requires more attention. Let’s see how best to move forward with that!

python - <<'PY'
import json
mems=json.load(open('/tmp/memory_dryrun_all.json'))
for typ in ['profile','project','task_hint','procedural','task']:
    print('\nTYPE',typ)
    for m in sorted([x for x in mems if x['type']==typ], key=lambda x:x['title']):
        print(f"{m['id']}\t{m['scope']}\t{m['title']}")
PY


TYPE profile
mem_ballbox_company_overview	global	Ballbox company overview
mem_ballbox_market_focus	project	Ballbox initial market focus
mem_ballbox_operating_principle	project	Ballbox operating principle
mem_ballbox_alias_volvox	project	Ballbox speech-to-text alias: Volvox
mem_ballbox_team_roles	global	Ballbox team and roles
mem_c31126352498447c8cb92069cb167397	global	Durable operational preferences live in agents-database
mem_69278f6716654a3c8fc5db37f97d2a6c	global	Follow-up instructions go to todo first
mem_humand_negotiation_lesson	project	Humand promotion negotiation lesson
mem_57f96c24431c4d38b5123f37e66bdae8	global	Laptop access should avoid web auth
mem_ce0fd7c72bfd4127b4d5ae206b42da09	global	No approval needed for laptop-tailnet access
mem_cdac83f3c3004eaca99546346d0c90d0	global	Resolve ambiguous spoken project names via agents-database first
mem_cba4a83f17824b16ac1d2d1949e72c48	global	Resolve ambiguous terms via agents-database first
mem_07bec891ac99453388c2570402bbd256	global	Sebas anime taste and watch state
mem_sebas_apartment_interior_design_goal	global	Sebas apartment interior design goal
mem_sebas_bias_technical_overfocus	global	Sebas bias: can get lost in the technical
mem_sebas_big_decisions_heart_led	global	Sebas big decisions often go best when heart-led
mem_sebas_closing_block_external_judgment	global	Sebas closing block: external judgment
mem_sebas_current_priorities	global	Sebas current priorities
mem_sebas_definition_wasted_life	global	Sebas definition of a wasted life
mem_sebas_definition_finish_well	global	Sebas definition of finishing well
mem_sebas_definition_of_leverage	global	Sebas definition of leverage
mem_sebas_desired_agent_role	global	Sebas desired agent role
mem_sebas_money_relationship	global	Sebas desired relationship with money
mem_sebas_dislikes_premature_action	global	Sebas dislikes premature action without intent clarity
mem_sebas_energy_pattern_time_alone	global	Sebas energy pattern: challenge drains, solo time restores
mem_sebas_evidence_preference_public_consensus	global	Sebas evidence preference favors public-source aggregation
mem_sebas_feedback_signal_explicit	global	Sebas gives explicit feedback signals
mem_sebas_discipline_closing_is_hardest	global	Sebas hardest discipline phase is closing
mem_sebas_custom_ai_solutions_income_idea	global	Sebas idea: custom AI solutions as alternative income
mem_sebas_life_philosophy_shared_love_challenge	global	Sebas life philosophy: love and high-level challenges
mem_sebas_optimizes_correctness_leverage	global	Sebas optimizes for correctness and leverage
mem_sebas_pattern_starts_without_finishing	global	Sebas pattern: starts things and may not finish them
mem_sebas_agent_style_challenging	global	Sebas prefers challenging agents
mem_sebas_socioeconomic_baseline	global	Sebas socioeconomic baseline
mem_sebas_work_philosophy	global	Sebas work philosophy
mem_c24eb94053944d0d8847c565a2a6f65a	global	User priorities for agent improvement
mem_bb53229e06914ac4a5aa51fee72455b3	global	User priorities for agent improvement corrected
mem_c8d11a9d510d4a159a80cf183f2583b4	global	User spoke briefly in Spanish in this session
mem_be2fa9c2360848c9afbeec1b006e8a54	global	User wants minimal repetition

TYPE project
mem_d8269f8eb0104dc3961fd2fb9762a0f0	project	Agents-database memory service auto-promotes ingested memories
mem_ballbox_stage_and_goal	project	Ballbox current stage and immediate goal
mem_ballbox_feels_unreal_early_validation	project	Ballbox still feels unreal during early validation
mem_d33f08e0d2f1468fbb47a61f10c8cfb9	global	Fallback should rotate through models until first HTTP 200
mem_humand_career_goal_after_senior	project	Humand near-term career goal after senior promotion
mem_cda20c374a614e6ca531f9e9e121c5bd	global	Laptop helpers use dedicated SSH key on port 2222
mem_5be93517d726499fbdf0f614da57ef6e	project	Memory layer RFC approved; hierarchical promotion is the key design
mem_35031f7d2ae64415805676b6597362d2	global	Memory service promotes all ingested items; inbox not used much
mem_d5e70dce68174497a33371458d9c67b9	global	Memory validation blocked by OpenAI auth failure
mem_68d91c0d9b6244f384fac0abfff678e7	project	Mercado Pago split payments need club revenue share option
mem_931b6b5353fd4e86b454333eeb2928ef	project	OPS-1 closes payment-provider confidence, not full machine integration
mem_8c5c0ef5a6e3412289c6fbe2210108b1	project	OurVend real-ui migration finished with ads blocked hidden
mem_08b4efed55144d78af56bdd15821b61d	project	Root disk nearly full; /mnt/rpi has room and safe caches were moved there
mem_dcaa730515ae48b39eda5dcc5e38edd0	global	Root partition nearly full during Linux update
mem_4c13c21c3c514b669055da643e90049a	global	SSH server idle timeout disabled
mem_ballbox_personal_motivation_first_business	project	Sebas personal motivation in Ballbox
mem_812ea22ea06d4368bdb66fe531e64fdc	global	Server SSH idle timeout raised to 4h
mem_a943e01322a0428388b1e50cc4d619e1	global	Telegram /new rotates the Pi Telegram session
mem_75e46401481a40bdbda587e3dcc823ba	project	Three-tier confidence model for vending rollout
mem_c6371cbb4e92425ca123bbc8b1f304f3	global	Use /mnt/rpi for large user caches when root is tight
mem_b9dfde5e35a84944b86841b537be2b4c	global	Vibes service needs provider env
mem_93c0669e3d064fc29b8142d201f923af	global	ballbox-first no longer depends on /mnt/rpi for home symlinks and core services
mem_b2016fa04f8546389dc9caaa231b8268	global	ballbox-first work tree lives under home/work
mem_58309c3e69e444d7b15c377d18b6b960	project	gastos-europa stores raw receipts and published allocator app
mem_6d77b1a0123f491489990043b55e9962	global	pi CLI lives in ~/.npm-global but npm global prefix points to zed pi-acp
mem_f7f168513be944169a0a7790b25293f0	project	pi-tau-mux stale ctx crash on session replacement
mem_8008ca82485848cd9f5492c09c236fa4	project	rss-offline saves full local blog pages with mirrored assets

TYPE task_hint
legacy_task_79	global	Legacy task: Automatizar y documentar el arranque del sistema Raycast/Codex (reply + approval
legacy_task_34	global	Legacy task: Build a first supplier shortlist for Ballbox display deployment in covered padel
legacy_task_69	global	Legacy task: Build a production-readiness plan for ballbox-payment-integration grounded in th
legacy_task_12	global	Legacy task: Build a shortlist
legacy_task_6	global	Legacy task: Capture exact Android machine launcher payload and constraints from the Chinese
legacy_task_59	global	Legacy task: Capture or emulate the real Android launcher payload and browser constraints fro
legacy_task_24	global	Legacy task: Capture or emulate the real Android launcher query payload from the machine envi
legacy_task_36	global	Legacy task: Check Android/browser/fullscreen or kiosk-app path for each candidate
legacy_task_14	global	Legacy task: Check fullscreen browser path
legacy_task_71	global	Legacy task: Close security and configuration gaps: define production env vars, secret handli
legacy_task_35	global	Legacy task: Collect 5 candidate 50+ inch displays suitable for covered clubs
legacy_task_37	global	Legacy task: Compare brightness, connectivity, and likely installation fit for covered venues
legacy_task_15	global	Legacy task: Compare costs
legacy_task_5	global	Legacy task: Confirm target flow against current repo: machine launcher -> /pay page -> QR ->
legacy_task_48	global	Legacy task: Construir un prototipo funcional del input/overlay para uso personal
legacy_task_52	global	Legacy task: Current state confirmed: mock demo flow works end-to-end
legacy_task_4	global	Legacy task: Decide whether Ballbox needs outdoor sunlight-readable display or cheaper indoor
legacy_task_50	global	Legacy task: Decidir siguiente paso: endurecer producto, automatizar envío a Codex o descarta
legacy_task_62	global	Legacy task: Define a production test plan covering local, sandbox, machine-side, and go-live
legacy_task_74	global	Legacy task: Define deployment and observability: container/runtime config, structured logs i
legacy_task_46	global	Legacy task: Definir UX mínima: trigger, foco, transparencia, auto-hide y comportamiento al e
legacy_task_44	global	Legacy task: Diseñar y validar un sistema de respuesta mínima sobre películas fullscreen para
legacy_task_58	global	Legacy task: Document all gaps between the current mock demo and a production vending-machine
legacy_task_38	global	Legacy task: Draft supplier questions about boot behavior, remote management, and network sta
legacy_task_47	global	Legacy task: Evaluar arquitectura: app nativa, helper menubar, panel flotante o integración c
legacy_task_78	global	Legacy task: Evaluar mejora UX: después de responder desde Raycast, disparar Alt-Tab para vol
legacy_task_73	global	Legacy task: Expand verification: add integration tests for webhook-to-dispense flows, idempo
legacy_task_13	global	Legacy task: Find 3 indoor candidates
legacy_task_18	global	Legacy task: Goal is first a convincing demo to the user, not immediate production hardening
legacy_task_72	global	Legacy task: Harden runtime and data operations: decide migration strategy outside app boot,
legacy_task_25	global	Legacy task: Identify all gaps between the current mock bridge and the desired demo flow
legacy_task_26	global	Legacy task: Implement the highest-value demo improvements in priority order
legacy_task_45	global	Legacy task: Investigar restricciones y capacidades de macOS para mostrar input/overlay sobre
legacy_task_68	global	Legacy task: Key local sources reviewed: README.md, PLAN.md, src/config.ts, src/index.ts, src
legacy_task_67	global	Legacy task: Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.
legacy_task_70	global	Legacy task: Lock external contracts: validate MercadoPago QR Dynamic endpoints, webhook sign
legacy_task_56	global	Legacy task: Mini gap assessment: production still depends on real Android launcher payload,
legacy_task_19	global	Legacy task: Mini repo review: current repo already implements /pay, QR page, webhook handlin
legacy_task_20	global	Legacy task: Mini repo review: current repo is directionally aligned but still lacks real TCN
legacy_task_21	global	Legacy task: Mini repo review: likely next blocker for demo realism is capturing the real lau
legacy_task_54	global	Legacy task: Mini repo review: the bridge already supports /pay, session polling, webhooks, a
legacy_task_31	global	Legacy task: Mini research: Alibaba and Made-in-China already show multiple 55-inch Android/c
legacy_task_33	global	Legacy task: Mini research: browser/fullscreen support is plausible but still needs supplier-
legacy_task_11	global	Legacy task: Mini research: covered-club displays can use indoor commercial signage if bright
legacy_task_32	global	Legacy task: Mini research: for covered clubs, indoor commercial signage may be acceptable an
legacy_task_55	global	Legacy task: Mini validation: local Docker demo now reaches dispense_sent without manual curl
legacy_task_29	global	Legacy task: Minimum desired size: 50 inches or larger
legacy_task_65	global	Legacy task: No external production environment, MercadoPago account setup, or TCN/Yunshu cal
legacy_task_64	global	Legacy task: No extra scope constraints were provided in-thread, so the plan assumes a full f
legacy_task_66	global	Legacy task: No online research used; assessment based on local repo inspection and local ver
legacy_task_42	global	Legacy task: No se hizo research web todavía; pendiente relevar restricciones de macOS para o
legacy_task_53	global	Legacy task: Objective now is production path analysis, not immediate implementation of all p
legacy_task_61	global	Legacy task: Obtain and implement the real TCN/Yunshu dispense callback contract
legacy_task_43	global	Legacy task: Pendiente comparar enfoques: app nativa macOS, panel flotante, menubar helper, H
legacy_task_83	global	Legacy task: Possible committers for repository under investigation: Agustina Ini, Mariano Go
legacy_task_22	global	Legacy task: Prepare ballbox-payment-integration for a demoable machine payment flow
legacy_task_7	global	Legacy task: Prepare demo checklist: local dev flow, mock approved payment, production-like Q
legacy_task_3	global	Legacy task: Prepare supplier question list: browser fullscreen, remote management, autoplay
legacy_task_49	global	Legacy task: Probar el prototipo mientras se reproduce video en fullscreen y registrar límite
legacy_task_27	global	Legacy task: Produce a demo checklist with required environment, steps, and evidence to show
legacy_task_57	global	Legacy task: Produce a production-readiness plan for ballbox-payment-integration
legacy_task_39	global	Legacy task: Recommend whether to start with indoor commercial signage or semi-outdoor signag
legacy_task_8	global	Legacy task: Replace mocked TCN/Yunshu dispense callback with real contract once docs or real
legacy_task_51	global	Legacy task: Repo target confirmed: ballbox-payment-integration
legacy_task_77	global	Legacy task: Resolver rebotes del watcher de approvals de Raycast/Codex y evitar prompts dupl
legacy_task_80	global	Legacy task: Review public references for Trading-Mastery GitHub org and summarize confirmed
legacy_task_75	global	Legacy task: Run pre-prod certification: sandbox E2E with MercadoPago and a real or faithfull
legacy_task_2	global	Legacy task: Shortlist 5 display SKUs split by indoor vs direct-sunlight use case with size,
legacy_task_63	global	Legacy task: Si Sebas prioriza simplicidad, probar primero BetterTouchTool con floating menu
legacy_task_81	global	Legacy task: Track public Humand affiliation evidence for repo-commit names without storing u
legacy_task_82	global	Legacy task: Treat the named individuals as publicly announced Humand employees per user-prov
legacy_task_76	global	Legacy task: Turn the persisted production-readiness plan into an execution sequence with own
legacy_task_30	global	Legacy task: Use case: advertising playback pointing to Ballbox web page in fullscreen browse
legacy_task_10	global	Legacy task: User clarified: covered clubs first
legacy_task_17	global	Legacy task: User clarified: final target is the Android app flow integrated in the Chinese v
legacy_task_28	global	Legacy task: User clarified: prioritize covered padel clubs first, not direct-sunlight courts
legacy_task_16	global	Legacy task: User clarified: the correct repo is ballbox-payment-integration
legacy_task_41	global	Legacy task: Usuario aclaró: el comportamiento deseado es un input poco intrusivo, transparen
legacy_task_40	global	Legacy task: Usuario aclaró: quiere las dos cosas, construir una solución concreta y además i
legacy_task_60	global	Legacy task: Validate MercadoPago production QR flow, webhook signature verification, and acc
legacy_task_9	global	Legacy task: Validate MercadoPago real QR dynamic flow, webhook signature verification, and t
legacy_task_23	global	Legacy task: Verify current repo flow end-to-end in mock mode and document exact behavior
legacy_task_1	global	Legacy task: Verify whether shortlisted suppliers expose Android browser/fullscreen or altern

TYPE procedural
mem_46bcc3518d504dc1ac0312c83390f8cb	global	Memory analysis should inspect database counts by source_ref/date and job outcomes
mem_1f9ea7b9e3fb4eea903f28ed961ccbe2	global	SSH timeout changes should be validated and reloaded
mem_3ff27df7bb94403c915ebcee665e338a	global	Safe /tmp cleanup policy
mem_7bd9f85afc174694af2ab2653786ca8e	project	Session-memory analysis should inspect job logs plus SQLite tables

TYPE task
mem_b3b2813ced47406babdc7c8f5b40ea36	project	Ballbox company handoff
mem_d7d13d0c108b4bd9ac634e9be66cfd0d	project	Personal handoff: Ballbox necesita fix en repo de pagos y abrir branch para QR
mem_70d2accc36c44e6caaf9eabe94b2240f	project	Personal handoff: Ballbox necesita fix en repo de pagos y abrir branch para QR


python - <<'PY'
import json, collections, re
mems=json.load(open('/tmp/memory_dryrun_all.json'))
classes=collections.Counter()
for m in mems:
    id=m['id']
    if id.startswith('legacy_task_'): classes['legacy_task']+=1
    elif id.startswith('legacy_run_'): classes['legacy_run']+=1
    elif id.startswith('legacy_source_'): classes['legacy_source']+=1
    elif id.startswith('legacy_claim_'): classes['legacy_claim']+=1
    elif m['title'].startswith('sebas:'): classes['raw_episode']+=1
    else: classes['normal']+=1
print(classes)
PY


Counter({'normal': 132, 'legacy_task': 83, 'raw_episode': 31, 'legacy_claim': 22, 'legacy_source': 22, 'legacy_run': 14})


**Considering episode titles**

I think I need to take a closer look at the raw episode titles to find ones that could be recommended for dropping. There might be some that don’t quite resonate or fit the overall theme. It feels important to ensure my recommendations are well-informed and thoughtful. Let's explore this more deeply, examining the titles to identify any potential candidates for removal that may not be serving their purpose effectively.

python - <<'PY'
import json
mems=json.load(open('/tmp/memory_dryrun_all.json'))
for m in mems:
    if m['title'].startswith('sebas:') or m['title'].startswith('Research run:') or m['title'].startswith('Legacy task:'):
        continue
for m in sorted([x for x in mems if x['title'].startswith('sebas:')], key=lambda x:x['updated_at'] or ''):
    print(m['id'], '\t', m['title'])
PY


mem_6831b78c9c964e3fb9db0c43afa2dfec 	 sebas: Actualiza el agent dorandí que diga evitar a toda costa repetirse. Esto…
mem_282e57f1ffe6455e82fbe4d184445f2c 	 sebas: [telegram] alo
mem_de64feafc920451eaa0c25ee1666f4af 	 sebas: [telegram] start backlog tasks in parallel. ask them to run as much as…
mem_5764c637222e487cafc71928884bc1d5 	 sebas: [telegram] Dame el link Arrival Guide que había creado para cuando lleg…
mem_af7ad5e49a1b4f4e92064fcfe9028efa 	 sebas: [telegram] guarda en raw mis gastos europa (imagenes + texto extraido)…
mem_c765760853224345940d788c503b32d7 	 sebas: [telegram] saca el proyecto freshrss (codigo, docs, links, todo) y para…
mem_a1f632320762487c8864dd45f2cbf394 	 sebas: [telegram] hazme en inglés, un texto explicando con flechas, el flujo m…
mem_90803c7909964e3a8c5ab856ae631d02 	 sebas: [telegram] te fijas por qué no están dando el Wi-Fi tracker?
mem_a4fe0023db78488788bbd8d9dc62e937 	 sebas: [telegram] antes en el backlog encaramos, tareas para accesibilidad en…
mem_c657e5149cf440e9a87470e1f794a96e 	 sebas: [telegram] backlog actual?
mem_17cc09268a3e43b5a381217ea7b28398 	 sebas: [telegram] que tareas hay?
mem_c1cd76a28d434774ad10b1507577bab3 	 sebas: [telegram] necesito para ballbox un entregable en pdf profesional para…
mem_8e4e732436404c64968fa03777dc5bbb 	 sebas: [telegram] pudiste?
mem_1c55c0a938eb4845a971aa25424c2c07 	 sebas: [telegram] agrega al proyecto de vending status, el próximo paso que se…
mem_d5b42c3f1f89464d8f765f141cf0c295 	 sebas: [telegram] if i gave you a free session to propose all the improvements…
mem_cb222aaef79b42b18598ae968aa3899d 	 sebas: [telegram] ya me lei todo el pdf de rss, me armas otro con lo que haya…
mem_9403ad4bf1c5435391d69c3c4d133ac7 	 sebas: [telegram] hay en /home/sebas/work/projects/ballbox/docs/tcn-maquinas-r…
mem_3bca1201a684427e87bca9e7cc806afc 	 sebas: [telegram] how do we set up a deepseek api key to pi?
mem_edf34d5e3b9a4dbe9276d288255bade7 	 sebas: [telegram] resume ftp investigation for ballbox. Since we need a passwo…
mem_165ae24535224d79b9e0370d64c1e7b4 	 sebas: [telegram] el zip que paso son los archivos en una máquina expendedora.…
mem_1e0572197f9048ba9f99f84fbd0a0592 	 sebas: [telegram] te llegaron?
mem_d45915de1d704362a10b78a4beb0a0b9 	 sebas: [telegram] dale hacelo
mem_a238b1334bbf4bba900d3d91b83f5174 	 sebas: hay una sesion de tmux abierta?
mem_0ffba9b736bf4c0aae1d3696fb36c65e 	 sebas: [telegram] hay una sesion de tmux abierta?
mem_f69a512f8b034dba821f31efc6b046db 	 sebas: [telegram] busca una conversación de una sesión de pi de hoy, en donde…
mem_4814b92ec95a4376a9927668421d8503 	 sebas: [telegram] te fijas que los links a pdfs en https://ballbox-first.emper…
mem_15c297bc9c334fed8e31075b26130378 	 sebas: [telegram] loved this repo’s idea https://github.com/workos/case and it…
mem_d356ae644c4f4f90982d6024a49085c0 	 sebas: [telegram] limpia la carparta de dropzone que te voy a pasar nuevos
mem_31a3021ad8f349e19bc839199ae6697d 	 sebas: [telegram] te animas a reproducir este logo a la perfeccion pero vector…
mem_c8667f8f64f747c7a7cc1407da9ff8bb 	 sebas: [telegram] en el pdf diario de rss podriamos agregar el titulo del feed…
mem_1bd596d2f0854d058b37e0a75d74587c 	 sebas: [telegram] hace poco hicimos en un repo modificacion de zips para hacer…


**Classifying topics for review**

I’m thinking about classifying by topic since the dry run seems to show clear buckets. It might be useful to produce counts for categories like keep, merge, rewrite, drop, and needs human input. I should probably include actual examples too. I wonder if I could programmatically identify duplicates based on title similarity, though it sounds like it might require some manual effort. I should inspect the contents to find good merge candidates!


ID mem_c24eb94053944d0d8847c565a2a6f65a
TITLE User priorities for agent improvement
TYPE profile
CONTENT Sebas prioritizes durable artifact creation, stronger product sense, faster repo adaptation, and tighter communication compression over parallelization. Parallel execution is low priority because time pressure is rare. Completeness/validation is the next target, with emphasis on pushing for clearer user intent before work starts.

ID mem_bb53229e06914ac4a5aa51fee72455b3
TITLE User priorities for agent improvement corrected
TYPE profile
CONTENT From the top improvement list, Sebas prioritizes: 12 better durable artifact creation, 15 better default product sense, 6 better autonomous validation, and 10 stronger communication compression. Parallelization is not a priority because time pressure is rare. Completeness is the next target, with stronger intent capture before work and more pressure from the agent to clarify done criteria early.

ID mem_cba4a83f17824b16ac1d2d1949e72c48
TITLE Resolve ambiguous terms via agents-database first
TYPE profile
CONTENT When Sebas uses any ambiguous term, remembered phrase, shorthand, nickname, or speech-to-text alias, agents must query ~/agents-database before guessing from local context, filesystem names, or recent conversation assumptions.

ID mem_cdac83f3c3004eaca99546346d0c90d0
TITLE Resolve ambiguous spoken project names via agents-database first
TYPE profile
CONTENT When Sebas uses an ambiguous spoken or remembered repo/project name, especially speech-to-text aliases like Volvox for Ballbox, agents must query ~/agents-database before guessing from local filesystem names or repo lists.

ID mem_57f96c24431c4d38b5123f37e66bdae8
TITLE Laptop access should avoid web auth
TYPE profile
CONTENT User wants laptop-* helpers and general laptop access over Tailnet to avoid interactive browser/web authentication prompts. Prefer non-interactive Tailscale SSH/SSH-based access when possible.

ID mem_ce0fd7c72bfd4127b4d5ae206b42da09
TITLE No approval needed for laptop-tailnet access
TYPE profile
CONTENT User allows use of laptop-* helpers and general Tailnet connectivity to the laptop without asking for approval just because access happens via web link or remote connection. Still require confirmation for irreversible/destructive actions.

ID mem_812ea22ea06d4368bdb66fe531e64fdc
TITLE Server SSH idle timeout raised to 4h
TYPE project
CONTENT Set server-side OpenSSH keepalives on ballbox-first via /etc/ssh/sshd_config.d/99-idle-4h.conf: ClientAliveInterval 60, ClientAliveCountMax 240. Restarted ssh and verified active values with sshd -T. This keeps idle SSH sessions alive longer for all clients connecting to this server, including laptop and phone.

ID mem_4c13c21c3c514b669055da643e90049a
TITLE SSH server idle timeout disabled
TYPE project
CONTENT SSH sessions on this Pi are configured not to expire from server idle timeout by setting ClientAliveInterval to 0 in /etc/ssh/sshd_config.d/99-idle-4h.conf.

ID mem_c8c7e1c8af7d4665aafe58baca242345
TITLE Removed SSH session timeout at user request
TYPE episode
CONTENT User asked to remove SSH timeout so sessions do not expire; the change was applied successfully on the server and confirmed to stop idle disconnects.

ID mem_dcaa730515ae48b39eda5dcc5e38edd0
TITLE Root partition nearly full during Linux update
TYPE project
CONTENT The root filesystem backing ~ was 14G total, 13G used, 494M free, 97% full. /mnt/rpi was around 40% used. This was the blocker while updating Linux.

ID mem_08b4efed55144d78af56bdd15821b61d
TITLE Root disk nearly full; /mnt/rpi has room and safe caches were moved there
TYPE project
CONTENT Root filesystem on ballbox-first was at 97% used with ~494M free. Safe large paths were moved off root to /mnt/rpi and symlinked back: ~/go, ~/.bun, ~/.zed_server, ~/venvs, ~/downloads, ~/.pnpm-store. Biggest wins were ~/go (721M), ~/.pnpm-store (668M), ~/.bun (142M). ~/.local/share/zed was left in place because active Zed-related processes were present.


**Identifying search limitations**

I need to address a retrieval blind spot. The API search doesn’t have a canonical list, and I used a wide wildcard sweep. While I have a near-complete result at 304, I can’t guarantee it’s 100%. It’s crucial to note this limitation as it's important for understanding the reliability of the data. So, let’s make sure to create a concise summary that acknowledges this aspect.


Updated #1 (pending → completed)


Sí. Hecho. Dry run only.
No escribí nada.

Leí memorias con barrido amplio de search.
Resultado: **304 memorias** encontradas.
Nota: como el API expone `search` y no un `list all`,
esto es **casi completo pero no matemáticamente
garantizado**.

### Veredicto
La base está **sobrefragmentada**.
Con la heurística nueva conviene:
- conservar memorias durables de alto valor
- fusionar duplicados/correcciones
- podar ruido de sesión
- colapsar research legacy en paquetes

### Corte propuesto
- **keep:** ~110
- **merge/rewrite:** ~60
- **drop:** ~134

### Buckets claros

#### 1. Drop casi seguro
- **83 `legacy_task_*`**
  - muy granulares
  - son historial de runs viejos, no memoria durable
- **14 `legacy_run_*`**
  - salvo que quieras archivo histórico explícito
- **31 episodios crudos tipo**
  `sebas: [telegram] ...`
  - ruido de sesión
  - poca reutilidad futura
- algunos episodios operativos menores
  tipo “alo”, “pudiste?”, etc.

#### 2. Merge / rewrite casi seguro
- **22 `legacy_claim_*`**
- **22 `legacy_source_*`**

Eso hoy está muy atomizado.
Mejor rehacerlos como pocos `artifact`:
- un artifact por research topic/run
- con claims confirmados + sources clave
- no una memoria por source/claim

#### 3. Keep con limpieza mínima
Gran parte de:
- `decision`
- `project`
- `profile`
- algunos `artifact`
- pocos `procedural`

Estos sí ya parecen alineados con la heurística.

---

## Duplicados / conflictos detectados

### Merge claros
1. **User priorities for agent improvement**
   - `mem_c24eb...`
   - `mem_bb532...`
   - dejar solo la versión corregida

2. **Ambiguous term resolution**
   - `mem_cba4...`
   - `mem_cdac...`
   - fusionar en una sola regla general

3. **Laptop access**
   - `mem_57f9...`
   - `mem_ce0f...`
   - una sola memoria: preferir laptop helpers,
     sin web auth, sin pedir permiso extra
     para acceso no destructivo

### Conflicto real
4. **SSH timeout**
   - `mem_812e...` = timeout 4h
   - `mem_4c13...` = timeout disabled
   - `mem_c8c7...` episodio de remoción
   - `mem_b161...` decisión 4h

Acá hay contradicción temporal.
La consolidación debería dejar:
- **1 memoria vigente**
- quizá **1 episodio** si querés historial
- no ambas políticas activas

### Solapamiento fuerte
5. **Disk/root storage**
   - varias memorias sobre root casi lleno,
     mover caches a `/mnt/rpi`,
     home-first layout, etc.
   - conviene agrupar en:
     - layout durable actual
     - episodio puntual de space recovery

---

## Heurística aplicada en el dry run

### Keep si:
- preferencia estable del usuario
- decisión vigente
- hecho durable del proyecto/máquina
- artifact reusable
- procedural reusable

### Drop si:
- mensaje crudo de sesión
- task transient
- research scratchpad muy granular
- episodio sin valor futuro claro
- duplicado corregido por otro

### Merge si:
- misma política en dos memorias
- topic único repartido en muchas
- contradicción por versión temporal
- source/claim split artificial

---

## Qué haría en la consolidación real

### A. Borrar/podar
- todos los `legacy_task_*`
- casi todos los `legacy_run_*`
- casi todos los episodios `sebas: ...`

### B. Reescribir en bundles
- payment integration legacy research
- display sourcing research
- fullscreen overlay research
- Trading Mastery / Humand public-reference research

### C. Unificar políticas vivas
- ambiguous-term lookup
- laptop access
- SSH timeout actual
- memory-service behavior
- storage/layout facts

---

## Riesgo principal
Si querés preservar trazabilidad histórica fina,
podar `legacy_run/source/claim/task` reduce audit trail.
Pero para **memoria operativa** nueva,
la consolidación mejora mucho señal/ruido.

## Recomendación
Hacer consolidación real en dos fases:
1. **safe pass**
   - merge duplicados
   - drop raw noise
   - leave legacy research mostly intact but flagged
2. **legacy collapse pass**
   - convertir claims/sources/runs en bundles temáticos

Si querés, siguiente paso:
te preparo **plan exacto de consolidación**
con lista por memoria:
- `keep`
- `merge_into`
- `drop`
- `rewrite`

Y ahí recién, si aprobás, se ejecuta.


[telegram] todo bien
4. a ssh le saque todo timeout
5. problema medio solucionado (reintalamls sistema en microsd mas grande)

ejecuta


**Considering memory consolidation**

I need to execute the real consolidation since the user approved and clarified two facts. I should write relevant memories, possibly using the API directly. I might need to check my memory-write abilities and consider updating my to-do list. It’s cross my mind to save durable memory during our conversation if it's relevant. I wonder if consolidation in the database is possible, but I don't have any information about a delete API. I might need to check the API status or documentation.

todo

Execute memory consolidation across all memories

Apply approved consolidation plan to all memories using current heuristic, incorporating user clarifications that SSH timeout is fully removed and storage issue was mostly solved by reinstalling to a larger microSD.


Created #2: Execute memory consolidation across all memories (pending)


---
name: memory-write
description: Save a durable high-signal memory into agents-database
---

# memory-write

## Use When

- new information is likely useful beyond current chat or task
- saving a decision, preference, project fact, reusable source/artifact, or handoff summary
- user asks to remember something durable

## Do Not Use When

- content is trivial, redundant, ephemeral, or likely useless later
- content is secret unless user explicitly asked to store it

## Required Workflow

1. If useful context may already exist, optionally check first:
   - `curl -fsSL "${AGENTS_DB_API:-http://100.116.176.16:8091}/api/search?q=<query>&scope=global&scope=project&limit=10"`
2. Choose best memory type:
   - `profile`: stable user preference, priority, recurring constraint
   - `decision`: chosen approach or operating rule
   - `project`: durable project fact or invariant
   - `artifact`: reusable source, claim, reference, output
   - `episode`: concise session summary, blocked state, handoff context
3. Build a concise payload with:
   - required: `type`, `scope`, `title`, `content`
   - recommended when known: `subtype`, `project_id`, `repo_id`, `task_id`, `run_id`, `source_ref`, `origin_agent`, `url`, `domain`, `metadata`
4. Save it with the helper:
   - `~/.agents/skills/memory-write/memory-write --type <type> --scope <scope> --title "<title>" --content "<content>"`
5. Confirm the created memory id and what was stored.

## Quick Examples

```bash
~/.agents/skills/memory-write/memory-write \
  --type profile \
  --subtype working_preference \
  --scope global \
  --title "User prefers concise status updates" \
  --content "Sebas prefers short, direct updates with business impact first." \
  --source-ref "conversation:2026-04-17" \
  --origin-agent personal-agent

~/.agents/skills/memory-write/memory-write \
  --type decision \
  --subtype operating_rule \
  --scope global \
  --title "Agents should save durable high-signal memory opportunistically" \
  --content "Treat agents-database as shared durable memory, not only search." \
  --metadata '{"source":"conversation"}'
```

## Rules

- prefer one strong memory over many weak ones
- keep `title` short and searchable
- keep `content` factual and compact
- use `episode` for summaries, not for every chat turn
- include `url` and `domain` for web-derived artifacts when known
- include `project_id`, `repo_id`, `task_id`, and `run_id` when context exists


bash

python - <<'PY'
import requests, json
for path in ['/api/status','/openapi.json','/docs','/api/search?q=ssh&limit=1']:
    url='http://100.116.176.16:8091'+path
    r=requests.get(url,timeout=20)
    print('\nPATH',path,'status',r.status_code,'ct',r.headers.get('content-type'))
    print(r.text[:500])
PY


PATH /api/status status 200 ct application/json; charset=utf-8
{"ok": true, "db_path": "/home/sebas/agents-database/data/shared-agent-memory.sqlite3", "dashboard": {"active_tasks": [{"id": "task_33d854e72d094660a2fb293a8723f5c5", "title": "Fix GitHub credential automation so repo pushes and PR creation use the intended account reliably", "intent": "The current credential helper flow can select the wrong GitHub identity during multi-repo push and PR automation. Investigate the root cause across gh auth git credential helper and repo remote handling, then des

PATH /openapi.json status 404 ct text/html;charset=utf-8
<!DOCTYPE HTML>

        <meta charset="utf-8">
        <title>Error response</title>

Error response

Error code: 404

Message: Not Found.

Error code explanation: 404 - Nothing matches the given URI.

PATH /docs status 404 ct text/html;charset=utf-8
<!DOCTYPE HTML>

        <meta charset="utf-8">
        <title>Error response</title>

Error response

Error code: 404

Message: Not Found.

Error code explanation: 404 - Nothing matches the given URI.

PATH /api/search?q=ssh&limit=1 status 200 ct application/json; charset=utf-8
{"retrieval_id": "ret_e7eb5f5dadff436cb0d4f1d20ab0c861", "results": [{"memory": {"id": "mem_cda20c374a614e6ca531f9e9e121c5bd", "type": "project", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Laptop helpers use dedicated SSH key on port 2222", "content": "Configured laptop access to avoid expiring Tailscale SSH browser auth: generated ~/.ssh/id_ed25519_laptop_agent on ballbox-first, installed its public key in lap


**Inspecting API endpoints**

I need to look into the helper script specifically for the API endpoints. It seems important to ensure everything is functioning correctly. I'm curious if there might be any issues lurking there or areas that need improvement. I'll pay attention to the structure and functionality to make sure it aligns with what we're aiming for. Finding and fixing any potential problems could help streamline our process!


#!/usr/bin/env python3
import argparse
import json
import sys
import urllib.request

def read_content(args):
    if args.content is not None:
        return args.content
    if args.content_file:
        with open(args.content_file, 'r', encoding='utf-8') as f:
            return f.read()
    if not sys.stdin.isatty():
        return sys.stdin.read()
    raise SystemExit('need --content, --content-file, or stdin')

def main():
    p = argparse.ArgumentParser(description='Write memory to agents-database')
    p.add_argument('--api', default=None)
    p.add_argument('--id')
    p.add_argument('--type', required=True)
    p.add_argument('--subtype')
    p.add_argument('--scope', required=True)
    p.add_argument('--status', default='active')
    p.add_argument('--source-kind', default='manual')
    p.add_argument('--title', required=True)
    p.add_argument('--content')
    p.add_argument('--content-file')
    p.add_argument('--summary')
    p.add_argument('--project-id')
    p.add_argument('--repo-id')
    p.add_argument('--task-id')
    p.add_argument('--run-id')
    p.add_argument('--source-ref')
    p.add_argument('--evidence-ref')
    p.add_argument('--origin-agent')
    p.add_argument('--url')
    p.add_argument('--domain')
    p.add_argument('--metadata', help='JSON object string')
    args = p.parse_args()

    content = read_content(args)
    metadata = json.loads(args.metadata) if args.metadata else None
    api = args.api or 'http://100.116.176.16:8091'
    payload = {
        'type': args.type,
        'scope': args.scope,
        'status': args.status,
        'source_kind': args.source_kind,
        'title': args.title,
        'content': content,
    }
    optional = {
        'id': args.id,
        'subtype': args.subtype,
        'summary': args.summary,
        'project_id': args.project_id,
        'repo_id': args.repo_id,
        'task_id': args.task_id,
        'run_id': args.run_id,
        'source_ref': args.source_ref,
        'evidence_ref': args.evidence_ref,
        'origin_agent': args.origin_agent,
        'url': args.url,
        'domain': args.domain,
        'metadata': metadata,
    }
    for k, v in optional.items():
        if v is not None:
            payload[k] = v

    req = urllib.request.Request(
        api.rstrip('/') + '/api/ingest',
        data=json.dumps(payload).encode('utf-8'),
        headers={'Content-Type': 'application/json'},
        method='POST',
    )
    with urllib.request.urlopen(req, timeout=30) as r:
        body = r.read().decode('utf-8')
        print(body)

if __name__ == '__main__':
    main()


**Exploring data updates**

I’m thinking about how to handle updates with an ID. I need to check if using the same ID might overwrite existing data. It seems there might not be a delete option, but perhaps marking the status as "deleted" while keeping the same ID could work. I’m considering testing this on a scratch setup to see if I can create temporary memory and change the status. Let's see how that goes!

python - <<'PY'
import json, subprocess, uuid, requests
mid='test_'+uuid.uuid4().hex[:8]
cmd=['/home/sebas/.agents/skills/memory-write/memory-write','--id',mid,'--type','episode','--scope','global','--title','tmp test','--content','one']
print(subprocess.check_output(cmd,text=True))
print(requests.get('http://100.116.176.16:8091/api/search?q=tmp%20test&limit=5').text)
cmd=['/home/sebas/.agents/skills/memory-write/memory-write','--id',mid,'--type','episode','--scope','global','--status','deleted','--title','tmp test','--content','one']
print(subprocess.check_output(cmd,text=True))
print(requests.get('http://100.116.176.16:8091/api/search?q=tmp%20test&limit=5').text)
PY


{"id": "test_feac4efd", "type": "episode", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "tmp test", "content": "one", "summary": "one", "confidence": 1.0, "freshness": 1.0, "created_at": "2026-06-04T12:54:52.328284+00:00", "updated_at": "2026-06-04T12:54:52.328284+00:00", "observed_at": "2026-06-04T12:54:52.328284+00:00", "source_ref": null, "evidence_ref": null, "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {}, "embedding": null}

{"retrieval_id": "ret_7c03fb7021fd42fb970dbc3a0201bdd9", "results": [{"memory": {"id": "test_feac4efd", "type": "episode", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "tmp test", "content": "one", "summary": "one", "confidence": 1.0, "freshness": 1.0, "created_at": "2026-06-04T12:54:52.328284+00:00", "updated_at": "2026-06-04T12:54:52.328284+00:00", "observed_at": "2026-06-04T12:54:52.328284+00:00", "source_ref": null, "evidence_ref": null, "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {}, "embedding": null}, "score": 0.39999999999999997, "score_breakdown": {"facet": 0.0, "lexical": 1.0, "semantic": 0.0, "confidence": 1.0, "freshness": 1.0}, "matched_scope": "global", "evidence_ref": null, "explanation": "facets=0.00 lexical=1.00 semantic=0.00 confidence=1.00 freshness=1.00"}, {"memory": {"id": "legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0", "type": "episode", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "run", "title": "Research run: Test intake flow", "content": "Goal: Test intake flow\nScope: demo\nAssumptions: none\nSummary: Test intake flow", "summary": "Test intake flow", "confidence": 0.85, "freshness": 0.8, "created_at": "2026-03-13T14:01:39.636174+00:00", "updated_at": "2026-04-30T17:32:27.368568+00:00", "observed_at": "2026-03-11T03:03:04.117688+00:00", "source_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "evidence_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "schema_version": "shared-agent-memory-v2", "subtype": "research_run", "run_id": "8248124f-5145-475f-a3c7-a37b619abfa0", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"assumptions": "none", "goal": "Test intake flow", "run_status": "active", "schema": "shared-agent-memory-v2", "scope": "demo", "subtype": "research_run", "summary": "Test intake flow"}, "embedding": [0.47697552502965085, 0.47868266720942765, 0.49507123213528537, 0.47117124161840956, 0.19768706441815878, 0.16593421987430945, 0.08091853932142251, 0.055652835060725186]}, "score": 0.3735599958502105, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9370666390014037, "confidence": 0.85, "freshness": 0.8}, "matched_scope": "global", "evidence_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "explanation": "facets=0.00 lexical=0.50 semantic=0.94 confidence=0.85 freshness=0.80"}, {"memory": {"id": "legacy_task_67", "type": "task_hint", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Legacy task: Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.", "content": "Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.\nkind=research_note\nstatus=noted\nnotes=", "summary": "Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.", "confidence": 0.65, "freshness": 0.6, "created_at": "2026-03-13T14:01:39.775634+00:00", "updated_at": "2026-04-30T17:32:27.374539+00:00", "observed_at": "2026-03-13T14:01:39.775634+00:00", "source_ref": "personal-agent:task:67", "evidence_ref": "personal-agent:task:67", "schema_version": "shared-agent-memory-v2", "subtype": "task", "run_id": "1f1a3fd4-eb28-4e99-891f-07c97243a06f", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"legacy_task_id": 67, "schema": "shared-agent-memory-v2", "subtype": "task", "task_kind": "research_note", "task_status": "noted"}, "embedding": [0.5438375749309828, 0.5000467850467516, 0.45625599516252047, 0.32512826679409634, 0.2331431439087839, 0.20598796135487518, 0.15363472652121332, 0.14115802102347147]}, "score": 0.3514217524307522, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9228116828716815, "confidence": 0.65, "freshness": 0.6}, "matched_scope": "global", "evidence_ref": "personal-agent:task:67", "explanation": "facets=0.00 lexical=0.50 semantic=0.92 confidence=0.65 freshness=0.60"}, {"memory": {"id": "mem_ballbox_stage_and_goal", "type": "project", "scope": "project", "status": "active", "project_id": "ballbox", "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Ballbox current stage and immediate goal", "content": "Ballbox is still at validation stage. There are no customers yet, only interested people. Five vending machines are being brought from China for testing. The immediate goal is to start generating a real business.", "summary": "Validation stage; no customers yet; five machines coming from China; immediate goal is real business generation.", "confidence": 0.98, "freshness": 1.0, "created_at": "2026-03-13T21:19:16.033820+00:00", "updated_at": "2026-03-13T21:19:16.033820+00:00", "observed_at": "2026-03-13T21:19:16.033820+00:00", "source_ref": "conversation:2026-03-13:user-questionnaire-followup", "evidence_ref": "conversation:2026-03-13:user-questionnaire-followup", "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {"kind": "project_fact", "project": "ballbox"}, "embedding": [0.5488541861108049, 0.4939265154453664, 0.41280257107794954, 0.3616775853047337, 0.2585825726711414, 0.18041627210878655, 0.1850639980881698, 0.141121861555819]}, "score": 0.3850864725944328, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9085764839628854, "confidence": 0.98, "freshness": 1.0}, "matched_scope": "project", "evidence_ref": "conversation:2026-03-13:user-questionnaire-followup", "explanation": "facets=0.00 lexical=0.50 semantic=0.91 confidence=0.98 freshness=1.00"}, {"memory": {"id": "legacy_task_7", "type": "task_hint", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Legacy task: Prepare demo checklist: local dev flow, mock approved payment, production-like Q", "content": "Prepare demo checklist: local dev flow, mock approved payment, production-like QR flow, and machine-side screen recording or live test\nkind=task\nstatus=open\nnotes=", "summary": "Prepare demo checklist: local dev flow, mock approved payment, production-like QR flow, and machine-side screen recording or live test", "confidence": 0.65, "freshness": 0.6, "created_at": "2026-03-13T14:01:39.722966+00:00", "updated_at": "2026-04-30T17:32:27.371784+00:00", "observed_at": "2026-03-13T14:01:39.722966+00:00", "source_ref": "personal-agent:task:7", "evidence_ref": "personal-agent:task:7", "schema_version": "shared-agent-memory-v2", "subtype": "task", "run_id": "55b6eaa0-9ff5-438c-a375-50f0452079cb", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"legacy_task_id": 7, "schema": "shared-agent-memory-v2", "subtype": "task", "task_kind": "task", "task_status": "open"}, "embedding": [0.5331450704609046, 0.4796898918922651, 0.4248279980981351, 0.37735135923783025, 0.25443961641059665, 0.22296436324024638, 0.17654276079905945, 0.13100035537380406]}, "score": 0.3485111356182175, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9034075707881165, "confidence": 0.65, "freshness": 0.6}, "matched_scope": "global", "evidence_ref": "personal-agent:task:7", "explanation": "facets=0.00 lexical=0.50 semantic=0.90 confidence=0.65 freshness=0.60"}]}
{"id": "test_feac4efd", "type": "episode", "scope": "global", "status": "deleted", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "tmp test", "content": "one", "summary": "one", "confidence": 1.0, "freshness": 1.0, "created_at": "2026-06-04T12:54:52.470338+00:00", "updated_at": "2026-06-04T12:54:52.470338+00:00", "observed_at": "2026-06-04T12:54:52.470338+00:00", "source_ref": null, "evidence_ref": null, "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {}, "embedding": null}

{"retrieval_id": "ret_4ee188e3ea6e4aff87a2ad0300ef6b57", "results": [{"memory": {"id": "legacy_run_8248124f-5145-475f-a3c7-a37b619abfa0", "type": "episode", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "run", "title": "Research run: Test intake flow", "content": "Goal: Test intake flow\nScope: demo\nAssumptions: none\nSummary: Test intake flow", "summary": "Test intake flow", "confidence": 0.85, "freshness": 0.8, "created_at": "2026-03-13T14:01:39.636174+00:00", "updated_at": "2026-04-30T17:32:27.368568+00:00", "observed_at": "2026-03-11T03:03:04.117688+00:00", "source_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "evidence_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "schema_version": "shared-agent-memory-v2", "subtype": "research_run", "run_id": "8248124f-5145-475f-a3c7-a37b619abfa0", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"assumptions": "none", "goal": "Test intake flow", "run_status": "active", "schema": "shared-agent-memory-v2", "scope": "demo", "subtype": "research_run", "summary": "Test intake flow"}, "embedding": [0.47697552502965085, 0.47868266720942765, 0.49507123213528537, 0.47117124161840956, 0.19768706441815878, 0.16593421987430945, 0.08091853932142251, 0.055652835060725186]}, "score": 0.3735599958502105, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9370666390014037, "confidence": 0.85, "freshness": 0.8}, "matched_scope": "global", "evidence_ref": "personal-agent:run:8248124f-5145-475f-a3c7-a37b619abfa0", "explanation": "facets=0.00 lexical=0.50 semantic=0.94 confidence=0.85 freshness=0.80"}, {"memory": {"id": "legacy_task_67", "type": "task_hint", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Legacy task: Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.", "content": "Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.\nkind=research_note\nstatus=noted\nnotes=", "summary": "Local verification run on 2026-03-11: npm run typecheck passed; npm test passed.", "confidence": 0.65, "freshness": 0.6, "created_at": "2026-03-13T14:01:39.775634+00:00", "updated_at": "2026-04-30T17:32:27.374539+00:00", "observed_at": "2026-03-13T14:01:39.775634+00:00", "source_ref": "personal-agent:task:67", "evidence_ref": "personal-agent:task:67", "schema_version": "shared-agent-memory-v2", "subtype": "task", "run_id": "1f1a3fd4-eb28-4e99-891f-07c97243a06f", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"legacy_task_id": 67, "schema": "shared-agent-memory-v2", "subtype": "task", "task_kind": "research_note", "task_status": "noted"}, "embedding": [0.5438375749309828, 0.5000467850467516, 0.45625599516252047, 0.32512826679409634, 0.2331431439087839, 0.20598796135487518, 0.15363472652121332, 0.14115802102347147]}, "score": 0.3514217524307522, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9228116828716815, "confidence": 0.65, "freshness": 0.6}, "matched_scope": "global", "evidence_ref": "personal-agent:task:67", "explanation": "facets=0.00 lexical=0.50 semantic=0.92 confidence=0.65 freshness=0.60"}, {"memory": {"id": "mem_ballbox_stage_and_goal", "type": "project", "scope": "project", "status": "active", "project_id": "ballbox", "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Ballbox current stage and immediate goal", "content": "Ballbox is still at validation stage. There are no customers yet, only interested people. Five vending machines are being brought from China for testing. The immediate goal is to start generating a real business.", "summary": "Validation stage; no customers yet; five machines coming from China; immediate goal is real business generation.", "confidence": 0.98, "freshness": 1.0, "created_at": "2026-03-13T21:19:16.033820+00:00", "updated_at": "2026-03-13T21:19:16.033820+00:00", "observed_at": "2026-03-13T21:19:16.033820+00:00", "source_ref": "conversation:2026-03-13:user-questionnaire-followup", "evidence_ref": "conversation:2026-03-13:user-questionnaire-followup", "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {"kind": "project_fact", "project": "ballbox"}, "embedding": [0.5488541861108049, 0.4939265154453664, 0.41280257107794954, 0.3616775853047337, 0.2585825726711414, 0.18041627210878655, 0.1850639980881698, 0.141121861555819]}, "score": 0.3850864725944328, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9085764839628854, "confidence": 0.98, "freshness": 1.0}, "matched_scope": "project", "evidence_ref": "conversation:2026-03-13:user-questionnaire-followup", "explanation": "facets=0.00 lexical=0.50 semantic=0.91 confidence=0.98 freshness=1.00"}, {"memory": {"id": "legacy_task_7", "type": "task_hint", "scope": "global", "status": "active", "project_id": null, "repo_id": null, "agent_id": null, "source_kind": "manual", "title": "Legacy task: Prepare demo checklist: local dev flow, mock approved payment, production-like Q", "content": "Prepare demo checklist: local dev flow, mock approved payment, production-like QR flow, and machine-side screen recording or live test\nkind=task\nstatus=open\nnotes=", "summary": "Prepare demo checklist: local dev flow, mock approved payment, production-like QR flow, and machine-side screen recording or live test", "confidence": 0.65, "freshness": 0.6, "created_at": "2026-03-13T14:01:39.722966+00:00", "updated_at": "2026-04-30T17:32:27.371784+00:00", "observed_at": "2026-03-13T14:01:39.722966+00:00", "source_ref": "personal-agent:task:7", "evidence_ref": "personal-agent:task:7", "schema_version": "shared-agent-memory-v2", "subtype": "task", "run_id": "55b6eaa0-9ff5-438c-a375-50f0452079cb", "task_id": null, "url": null, "domain": null, "origin_agent": "personal-agent", "metadata": {"legacy_task_id": 7, "schema": "shared-agent-memory-v2", "subtype": "task", "task_kind": "task", "task_status": "open"}, "embedding": [0.5331450704609046, 0.4796898918922651, 0.4248279980981351, 0.37735135923783025, 0.25443961641059665, 0.22296436324024638, 0.17654276079905945, 0.13100035537380406]}, "score": 0.3485111356182175, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.9034075707881165, "confidence": 0.65, "freshness": 0.6}, "matched_scope": "global", "evidence_ref": "personal-agent:task:7", "explanation": "facets=0.00 lexical=0.50 semantic=0.90 confidence=0.65 freshness=0.60"}, {"memory": {"id": "mem_807edebd292b4f86a344f5674f7685c8", "type": "episode", "scope": "agent", "status": "active", "project_id": "proj_personal_agent", "repo_id": "repo_personal_agent", "agent_id": null, "source_kind": "manual", "title": "Task completed: Fresh CLI smoke task: summarize current system readiness and suggest one safe internal coordinati...", "content": "## Findings\n- Confirmed locally on 2026-03-15: `python3 scripts/personal.py --json status` works and returns live task/run state. Current snapshot shows `active_task_count=19`, `blocked_task_count=2`, `pending_approval_count=0`.\n- Confirmed locally on 2026-03-15: `codex exec --help` matches the newer CLI shape and supports `-C/--cd`, `--add-dir`, `--output-last-message`; it does not advertise the older `--ask-for-approval` flow.\n- Confirmed from repo state: local edits in `personal_agent/planner.py`, `personal_agent/runtime.py`, and `tests/test_personal.py` replace the obsolete `--ask-for-approval` and `--search` flags with `-C`, and add test coverage for that command shape.\n- Confirmed from runtime evidence: recent stored runs failed with exact error `unexpected argument '--ask-for-approval' found`, so the earlier smoke failures were real and explainable.\n- Confirmed from docs/scripts: the only declared repo gate is `./scripts/run-checks.sh`, which runs `python3 -m unittest discover -s tests`.\n- Not confirmed: full repo test pass. In this read-only sandbox, the test suite fails before exercising app behavior because Python cannot create temp dirs: `FileNotFoundError: No usable temporary directory found`.\n- Not confirmed: shared-memory operational readiness under this sandbox. Targeted memory search failed with `sqlite3.OperationalError: attempt to write a readonly database`, so shared DB interaction is not proven here.\n- Not confirmed: production readiness. Docs still describe dashboard, daemon, worker, approvals, and multi-repo handoff topology, but this run did not validate dashboard serving, worker completion, or end-to-end shared-memory writes.\n\n## Risks\n- Main near-term risk is false confidence from static docs plus partial command success while writable-path and temp-dir assumptions remain unverified.\n- Working tree is dirty, so the codex CLI fix appears in progress but not yet fully validated by a successful full gate.\n\n## Recommended Next Action\n- Queue one internal follow-up task: rerun the full local smoke gate in a writable environment after the current codex CLI flag fix lands, with focus on two proofs only: tests pass and shared-memory-backed worker flow completes without the old CLI error.", "summary": "## Findings\n- Confirmed locally on 2026-03-15: `python3 scripts/personal.py --json status` works and returns live task/run state. Current snapshot shows `active_task_count=19`, `bl", "confidence": 1.0, "freshness": 1.0, "created_at": "2026-03-15T14:22:58.677648+00:00", "updated_at": "2026-03-15T14:22:58.677648+00:00", "observed_at": "2026-03-15T14:22:58.677648+00:00", "source_ref": "personal-agent", "evidence_ref": "art_f2e3c950a9b8427e89e083457683077e", "schema_version": "shared-agent-memory-v2", "subtype": null, "run_id": null, "task_id": null, "url": null, "domain": null, "origin_agent": null, "metadata": {"task_id": "task_3d7271f7d19e456791b5796695fbe2fa", "task_run_id": "run_d37c8577c9674333b7157a945274385a"}, "embedding": [0.5224428985589578, 0.48152433076703893, 0.42973718009413725, 0.35778057440210237, 0.27926329686191054, 0.2267515739969433, 0.18020769118662489, 0.14362338250724355]}, "score": 0.3843020158442094, "score_breakdown": {"facet": 0.0, "lexical": 0.5, "semantic": 0.8953467722947295, "confidence": 1.0, "freshness": 1.0}, "matched_scope": "agent", "evidence_ref": "art_f2e3c950a9b8427e89e083457683077e", "explanation": "facets=0.00 lexical=0.50 semantic=0.90 confidence=1.00 freshness=1.00"}]}


**Considering memory updates**

I’m thinking about cleaning up some test data that needs to be deleted. For sure, I can exclude any deleted memories from my search. It seems like I might want to create some consolidated memories too. The user mentioned execution, so I’m looking to make real changes, but not overwhelm with too many deletions — maybe all 304 is too broad. I'll aim for clear cases, update duplicates, and possibly preserve some artifacts as well. User approved this plan!

**Creating consolidated artifacts**

I’m focusing on SSH and disk facts, considering the need for consolidated artifacts related to legacy research topics. Even if I'm deleting all sources and claims, preserving themes could be valuable. I’m thinking about summarizing the research into four different artifacts around payment integration, display sourcing, fullscreen overlay, and public reference. I might also consolidate storage by updating the current state of memories and marking conflicting ones as deleted while creating new project memories. I'll use a script to help with this process!

python - <<'PY'
import json, subprocess, textwrap
from pathlib import Path
mems=json.load(open('/tmp/memory_dryrun_all.json'))
by_id={m['id']:m for m in mems}

def upd(mid, **kw):
    m=by_id[mid].copy()
    m.update(kw)
    args=['/home/sebas/.agents/skills/memory-write/memory-write','--id',mid,'--type',m['type'],'--scope',m['scope'],'--status',m['status'],'--title',m['title'],'--content',m['content']]
    opt_map={
      'subtype':'--subtype','project_id':'--project-id','repo_id':'--repo-id','task_id':'--task-id','run_id':'--run-id',
      'source_ref':'--source-ref','evidence_ref':'--evidence-ref','origin_agent':'--origin-agent','url':'--url','domain':'--domain'
    }
    for k,flag in opt_map.items():
        v=m.get(k)
        if v is not None:
            args += [flag, str(v)]
    md=m.get('metadata')
    if md:
        args += ['--metadata', json.dumps(md)]
    subprocess.run(args, check=True, stdout=subprocess.DEVNULL)

# delete clear-noise groups
ids_to_delete=[]
for m in mems:
    mid=m['id']
    title=m['title']
    if mid.startswith(('legacy_task_','legacy_run_','legacy_claim_','legacy_source_')):
        ids_to_delete.append(mid)
    elif title.startswith('sebas:'):
        ids_to_delete.append(mid)

# duplicate/conflict drops
ids_to_delete += [
    'mem_c24eb94053944d0d8847c565a2a6f65a', # corrected by bb53
    'mem_cdac83f3c3004eaca99546346d0c90d0', # covered by general ambiguous term rule
    'mem_57f96c24431c4d38b5123f37e66bdae8', # covered by merged laptop access rule
    'mem_812ea22ea06d4368bdb66fe531e64fdc', # old 4h ssh timeout
    'mem_dcaa730515ae48b39eda5dcc5e38edd0', # old root full state
    'mem_08b4efed55144d78af56bdd15821b61d', # old root full state
    'mem_c8c7e1c8af7d4665aafe58baca242345', # old ssh change episode
    'mem_d7d13d0c108b4bd9ac634e9be66cfd0d', # duplicate handoff task
]
ids_to_delete=sorted(set(ids_to_delete))
for mid in ids_to_delete:
    if mid in by_id:
        upd(mid, status='deleted')

# create/replace consolidated active memories
create_cmd='/home/sebas/.agents/skills/memory-write/memory-write'
new_memories=[
    [
        '--id','mem_laptop_tailnet_access_policy',
        '--type','profile','--scope','global',
        '--title','Laptop Tailnet access policy',
        '--content','Prefer laptop-* helpers and SSH-based Tailnet access over browser/web auth. No extra approval is needed for non-destructive laptop access; confirmation is still required for irreversible actions.',
        '--subtype','working_preference','--source-ref','conversation:2026-06-04:memory-consolidation','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_ssh_idle_timeout_disabled',
        '--type','project','--scope','global',
        '--title','SSH server idle timeout disabled on ballbox-first',
        '--content','Current server policy on ballbox-first: SSH idle timeout is disabled, so sessions should not expire due to server-side idle timeout. This supersedes earlier 4h-timeout memories.',
        '--source-ref','conversation:2026-06-04:memory-consolidation','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_ballbox_first_storage_after_microsd_reinstall',
        '--type','project','--scope','global',
        '--title','ballbox-first storage pressure mostly resolved by larger microSD reinstall',
        '--content','Earlier root-disk pressure on ballbox-first was mostly resolved by reinstalling the system onto a larger microSD. Old memories about emergency cache moves and near-full root state are mainly historical, not current operating state.',
        '--source-ref','conversation:2026-06-04:memory-consolidation','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_legacy_ballbox_payment_research_bundle',
        '--type','artifact','--scope','global',
        '--title','Legacy Ballbox payment-integration research bundle',
        '--content','Consolidated legacy research outcome: the ballbox-payment-integration repo was directionally aligned for a vending QR flow but not production-safe. Key blockers identified across the old run set were real MercadoPago account/contract validation, correct webhook authenticity handling, real TCN/Yunshu dispense callback contract capture, production env/config hardening, and end-to-end validation against a real or faithful machine path.',
        '--subtype','research_bundle','--source-ref','memory-consolidation:legacy-ballbox-payment','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_legacy_display_sourcing_research_bundle',
        '--type','artifact','--scope','global',
        '--title','Legacy Ballbox display sourcing research bundle',
        '--content','Consolidated legacy research outcome: there were multiple viable 50-55 inch China-sourced signage options for Ballbox, and covered padel clubs likely allow cheaper indoor commercial signage before direct-sunlight outdoor hardware. The durable takeaway is to start from covered-club deployment assumptions, compare brightness/connectivity/remote-management constraints, and only pay for high-brightness outdoor units when the venue reality requires it.',
        '--subtype','research_bundle','--source-ref','memory-consolidation:legacy-display-sourcing','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_legacy_fullscreen_overlay_research_bundle',
        '--type','artifact','--scope','global',
        '--title','Legacy fullscreen overlay research bundle',
        '--content','Consolidated legacy research outcome: for replying to Codex without leaving fullscreen media, the viable solution space was lightweight overlay tooling rather than invasive native app scope. Raycast, BetterTouchTool, and Hammerspoon were the main candidates; the durable product takeaway was to optimize for minimal intrusion, quick trigger/response, and preserving fullscreen context.',
        '--subtype','research_bundle','--source-ref','memory-consolidation:legacy-fullscreen-overlay','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_legacy_public_reference_research_bundle',
        '--type','artifact','--scope','global',
        '--title','Legacy public-reference research bundle',
        '--content','Consolidated legacy public-reference outcome: Trading Mastery appears to be a real public business with a public website and GitHub organization presence, while Humand affiliation research should be treated as public-reference tracking only and handled carefully. Durable rule: keep only high-level public-reference conclusions, not granular source-by-source research shards, unless a live task needs them again.',
        '--subtype','research_bundle','--source-ref','memory-consolidation:legacy-public-reference','--origin-agent','personal-agent'
    ],
    [
        '--id','mem_memory_consolidation_2026_06_04',
        '--type','episode','--scope','global',
        '--title','Memory consolidation pass 2026-06-04',
        '--content','Applied one-time consolidation across existing memories using the newer high-signal heuristic. Deleted raw session snippets, legacy task/run/source/claim shards, and several superseded duplicates. Added consolidated bundle memories for older research themes. User clarified that SSH idle timeout is now fully removed and storage pressure was mostly solved by reinstalling onto a larger microSD.',
        '--source-ref','conversation:2026-06-04:memory-consolidation','--origin-agent','personal-agent'
    ],
]
for extra in new_memories:
    subprocess.run([create_cmd]+extra, check=True, stdout=subprocess.DEVNULL)
print('deleted',len(ids_to_delete))
print('created_or_updated',len(new_memories))
PY


deleted 180
created_or_updated 8


**Checking updates and verification**

I need to consider updating my to-do list for completed tasks. I think it’s important to ensure that everything is verified correctly, especially the counts. It feels like a responsible step to take, but I’m double-checking to make sure I haven’t missed anything. It's so easy to overlook details, and I want to be thorough. Okay, let me go ahead and do that!

python - <<'PY'
import requests, json
queries=['memory consolidation pass 2026-06-04','SSH server idle timeout disabled on ballbox-first','Legacy Ballbox payment-integration research bundle','sebas: [telegram] alo','Legacy task: Build a shortlist']
for q in queries:
    url='http://100.116.176.16:8091/api/search?q='+requests.utils.quote(q,safe='')+'&scope=global&scope=project&limit=5'
    r=requests.get(url,timeout=30).json()['results']
    print('\nQ',q)
    for item in r[:3]:
        m=item['memory']
        print(m['id'], m['status'], m['title'])
PY


Q memory consolidation pass 2026-06-04
mem_memory_consolidation_2026_06_04 active Memory consolidation pass 2026-06-04
mem_5be93517d726499fbdf0f614da57ef6e active Memory layer RFC approved; hierarchical promotion is the key design
mem_v1_legacy_bridge_status active V1 legacy bridge policy

Q SSH server idle timeout disabled on ballbox-first
mem_ssh_idle_timeout_disabled active SSH server idle timeout disabled on ballbox-first
mem_b161e2e3072a49099cabb17193a4fb15 active Server-side SSH idle timeout set to 4h
mem_4c13c21c3c514b669055da643e90049a active SSH server idle timeout disabled

Q Legacy Ballbox payment-integration research bundle
mem_legacy_ballbox_payment_research_bundle active Legacy Ballbox payment-integration research bundle
mem_legacy_display_sourcing_research_bundle active Legacy Ballbox display sourcing research bundle
mem_memory_consolidation_2026_06_04 active Memory consolidation pass 2026-06-04

Q sebas: [telegram] alo
mem_c089dddd4e6742e388b77447978d883c active sebas: [telegram] how many new rss feeds are available since last merged pdf g…
mem_sebas_custom_ai_solutions_income_idea active Sebas idea: custom AI solutions as alternative income
mem_sebas_work_philosophy active Sebas work philosophy

Q Legacy task: Build a shortlist
mem_sebas_custom_ai_solutions_income_idea active Sebas idea: custom AI solutions as alternative income
mem_v1_legacy_bridge_status active V1 legacy bridge policy
mem_ballbox_personal_motivation_first_business active Sebas personal motivation in Ballbox


**Investigating memory issues**

I’m checking the search results, and it looks like deleted memories aren’t appearing. Wait, is mem_4c13 still active? If we deleted it, why is it showing active? Maybe it’s because writing after deletion created a new row? Hmm, it could also be stale results. I’m thinking I need to use the exact ID query. Let’s inspect to see if the search can still return deleted entries.

python - <<'PY'
import requests, json
for mid in ['mem_4c13c21c3c514b669055da643e90049a','mem_b161e2e3072a49099cabb17193a4fb15','mem_c24eb94053944d0d8847c565a2a6f65a']:
    url='http://100.116.176.16:8091/api/search?q='+mid+'&limit=5'
    r=requests.get(url,timeout=30).json()['results']
    print('\nID',mid)
    for item in r:
        m=item['memory']
        print(m['id'],m['status'],m['updated_at'],m['title'])
PY


ID mem_4c13c21c3c514b669055da643e90049a
mem_ballbox_payment_repo active 2026-03-13T14:42:32.069202+00:00 Ballbox payment integration repo purpose
mem_ballbox_cost_over_elegance active 2026-03-13T21:19:16.035314+00:00 Ballbox decision priority: cost and business impact over elegance
mem_sebas_confirm_irreversible_actions active 2026-03-13T21:19:16.031012+00:00 Require confirmation for irreversible actions
mem_runtime_agentic_refactor_priority active 2026-03-14T21:46:12.297151+00:00 Refactor runtime toward Codex-agentic orchestration
mem_ballbox_alias_resolution_rule active 2026-03-13T20:18:43.250199+00:00 Ballbox alias resolution rule for Volvox mentions

ID mem_b161e2e3072a49099cabb17193a4fb15
mem_sebas_definition_of_leverage active 2026-03-13T21:26:33.704753+00:00 Sebas definition of leverage
mem_ballbox_payment_repo active 2026-03-13T14:42:32.069202+00:00 Ballbox payment integration repo purpose
mem_sebas_pattern_starts_without_finishing active 2026-03-13T21:36:20.595356+00:00 Sebas pattern: starts things and may not finish them
mem_ballbox_marketing_repo active 2026-03-13T14:42:32.068103+00:00 Ballbox marketing repo purpose
mem_sebas_dislikes_premature_action active 2026-03-13T21:19:16.030296+00:00 Sebas dislikes premature action without intent clarity

ID mem_c24eb94053944d0d8847c565a2a6f65a
mem_sebas_definition_of_leverage active 2026-03-13T21:26:33.704753+00:00 Sebas definition of leverage
mem_ballbox_payment_repo active 2026-03-13T14:42:32.069202+00:00 Ballbox payment integration repo purpose
mem_ballbox_cost_over_elegance active 2026-03-13T21:19:16.035314+00:00 Ballbox decision priority: cost and business impact over elegance
mem_runtime_agentic_refactor_priority active 2026-03-14T21:46:12.297151+00:00 Refactor runtime toward Codex-agentic orchestration
mem_sebas_apartment_interior_design_goal active 2026-03-13T22:11:51.271332+00:00 Sebas apartment interior design goal


**Considering database access**

Searching by ID isn't working out well. I'm thinking maybe if something is deleted, it could be hidden, so I might need to use the exact context. It could be better to use the API database or possibly access SQLite directly. Since there's a local path from the status, inspecting SQLite seems like the easiest option. I need to know if any deleted states apply since the write operation returned no output. I'll inspect the database using the sqlite3 command.

python - <<'PY'
import sqlite3, json
conn=sqlite3.connect('/home/sebas/agents-database/data/shared-agent-memory.sqlite3')
cur=conn.cursor()
for mid in ['mem_4c13c21c3c514b669055da643e90049a','mem_b161e2e3072a49099cabb17193a4fb15','mem_c24eb94053944d0d8847c565a2a6f65a','legacy_task_12','mem_282e57f1ffe6455e82fbe4d184445f2c']:
    rows=cur.execute('select id,status,title,updated_at from memories where id=?',(mid,)).fetchall()
    print(mid, rows)
print('active', cur.execute("select count(*) from memories where status='active'").fetchone()[0])
print('deleted', cur.execute("select count(*) from memories where status='deleted'").fetchone()[0])
PY