rohitg00/agentmemory

recall

Search agentmemory for past observations, sessions, and learnings about a topic using hybrid BM25 plus vector plus graph search.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/rohitg00/agentmemory --skill recall

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

The user wants to recall past context about: $ARGUMENTS

Quick start

json
memory_smart_search { "query": "jwt refresh token rotation", "limit": 10 }

Expected output:

text
2 results across 2 sessions.
[importance 8] decision · "Rotate refresh tokens on every use" (session 7f3a9c21)
[importance 5] code · "limit.ts counts per-IP" (session b21d004e)

Why

Only surface what the tool returned. Never fabricate an observation, a session id, or an importance score. If nothing comes back, say so.

Workflow

  1. Call memory_smart_search with the user's text as query and limit: 10.

Pass project when the user scopes to a specific repo and agentId when they request one agent's history. Use targetLayer: "memory" for explicitly saved knowledge, or targetLayer: "observation" for captured activity. Omit it for mixed search.

  1. Search results are compact. Before quoting full content or describing

provenance, call memory_smart_search with the selected IDs as a comma-separated expandIds string and the same project, agent, and layer filters. If expansion fails or the record is no longer available, report that limitation; a title alone is not the full fact.

  1. Group expanded observations by session and show the returned type, title,

and narrative. Include provenance only when the response supplies it.

  1. Lead with the high-signal observations (importance >= 7).
  2. With memory_recall, inspect matched_count, excluded_by_budget, and

content_truncated before treating an empty or shortened response as absent knowledge. Recover full content with memory_smart_search using expandIds and the same project, agent, and layer filters. minimum_budget reports the estimated budget needed for a minimal preview when the budget is too small.

  1. If there are no matches, suggest 2-3 alternative search terms and stop. Do not guess.

Anti-patterns

WRONG: results are empty, so you write "We probably discussed token expiry last week" from assumption.

RIGHT: "No memories matched that query. Try refresh token, session expiry, or auth rotation."

Checklist

  • Every observation shown came from the tool response.
  • Results grouped by session, high-importance first.
  • Empty results trigger alternative-term suggestions, not invention.
  • No session id or score was paraphrased or rounded.

See also

  • remember: the write side; recall retrieves what it stores.
  • recap, handoff, session-history: session-scoped views of the same data.
  • memory-discipline: when to run this search unprompted.

Troubleshooting

See TROUBLESHOOTING.md if memory_smart_search is not available.

Verwandte Aufgaben

aus demselben Repository

Weitere Skills

Alle Skills
rohitg00
Community

agentmemory-agents

How agentmemory wires into host coding agents via the connect command. Use when installing agentmemory into a specific agent, when asked which agents are supported, or when a connect adapter writes the wrong config path.

Installationen / 1h
3
GitHub Stars
29.891
Aktualisiert
25. Okt.
rohitg00
Community

agentmemory-architecture

How agentmemory is built, the iii engine primitives it runs on, its storage model, ports, and the viewer. Use when reasoning about how memory is stored or retrieved end to end, when extending the system, or when answering how agentmemory works under the hood.

Installationen / 1h
3
GitHub Stars
29.891
Aktualisiert
25. Okt.
rohitg00
Community

agentmemory-hooks

The agentmemory plugin hooks that capture observations automatically across the agent session lifecycle. Use when explaining how memory gets captured without manual saves, when debugging missing observations, or when tuning what gets recorded.

Installationen / 1h
3
GitHub Stars
29.891
Aktualisiert
25. Okt.
rohitg00
Community

commit-context

Trace a file, function, or line back to the agent session that produced its current commit. Use when the user asks "why is this code here", "what was the agent doing when this changed", "who wrote this", or wants context on a specific location in the codebase.

Installationen / 1h
3
GitHub Stars
29.891
Aktualisiert
25. Okt.