agentmemory-agents
How agentmemory wires into host coding agents via the connect command. Use when installing agentmemory into a specific agent,…
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.
Claude Code
$ npx -y skills add rohitg00/agentmemory --skill recall --agent claude-code
Codex
$ npx skills add rohitg00/agentmemory --skill recall -a codex -y
Cursor
$ npx skills add rohitg00/agentmemory --skill recall -a cursor -y
Gemini CLI
$ npx skills add rohitg00/agentmemory --skill recall -a gemini-cli -y
GitHub Copilot
$ npx skills add rohitg00/agentmemory --skill recall -a github-copilot -y
OpenCode
$ npx skills add rohitg00/agentmemory --skill recall -a opencode -y
Windsurf
$ npx skills add rohitg00/agentmemory --skill recall -a windsurf -y
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
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)
Only surface what the tool returned. Never fabricate an observation, a session id, or an importance score. If nothing comes back, say so.
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. 2. 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. 3. Group expanded observations by session and show the returned type, title, and narrative. Include provenance only when the response supplies it. 4. Lead with the high-signal observations (importance >= 7). 5. 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. 6. If there are no matches, suggest 2-3 alternative search terms and stop. Do not guess.
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`."
See [TROUBLESHOOTING.md](TROUBLESHOOTING.md) if `memory_smart_search` is not available.
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