| name | recall |
| description | Search agentmemory for past observations, sessions, and learnings about a topic using hybrid BM25 plus vector plus graph search. Use when the user says "recall", "what did we do about", "did we ever", "have we seen", or needs context from past sessions. |
| argument-hint | [search query] |
| user-invocable | true |
The user wants to recall past context about: $ARGUMENTS
Quick start
memory_smart_search { "query": "jwt refresh token rotation", "limit": 10 }
Expected output:
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
- Call
memory_smart_search with the user's text as query and limit: 10.
Pass project when the user scopes to a specific repo.
- Group results by session.
- For each observation show its type, title, and narrative.
- Lead with the high-signal observations (importance >= 7).
- If zero results, 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.
Troubleshooting
See ../_shared/TROUBLESHOOTING.md if memory_smart_search is not available.
