| name | remnic-recall |
| description | Search Remnic memories by natural-language query. Trigger phrases include "what do you remember about", "recall anything on", "have we discussed". |
| allowed-tools | ["remnic_recall"] |
When to use
Use when the user or the current task needs prior context from Remnic. This is the default first step for any non-trivial turn that could benefit from memory.
Triggers:
- "What do you remember about …"
- "Have we talked about …"
- "Recall anything on …"
- A new task begins and the agent wants background.
Inputs
query (required) — natural-language question or topic string.
- Optional budget hint from the caller (e.g., "brief", "deep").
Procedure
- Build a concise natural-language query from the user's request. Prefer the user's own wording over paraphrase.
- Call
remnic_recall with that query. Ask for 3–8 results unless the caller hinted otherwise.
- Skim the returned memories. Discard anything clearly off-topic.
- Present 1–5 relevant bullet points to the user, each attributed to its source memory when useful.
- If nothing relevant came back, say so plainly and suggest
remnic-remember if there is something worth storing now.
Efficiency plan
- One broad recall beats several narrow ones.
- Reuse results within the same turn — do not re-query for the same topic.
- Skip recall entirely for trivially local requests (formatting, arithmetic, mechanical refactors).
Pitfalls and fixes
- Pitfall: Quoting irrelevant recalls just because they came back. Fix: Filter by topical relevance before surfacing.
- Pitfall: Over-narrowing the query and missing useful context. Fix: Start broad; refine only if the first pass was noisy.
- Pitfall: Presenting raw memory blobs. Fix: Summarize in the user's own terms.
Verification checklist
Tool names: canonical name is remnic_recall. The legacy engram_recall alias remains accepted during v1.x.