--- name: recall description: > Search Origin's local memory by query. Targeted lookup, not orientation. Invoked as `/recall `. Use when the user asks "do you remember", "what do you know about", "look up". argument-hint: "" allowed-tools: ["mcp__plugin_origin_origin__recall"] --- # /recall Search Origin's memory by natural-language query. Returns matching memories ranked by hybrid vector + FTS search, then re-ordered by the agent if it helps. ## Two phases When a local model or API key is configured, the daemon can rerank and expand server-side. In local memory mode it cannot. The skill always does **agent-side expansion and rerank** itself — cheap, makes results good in both modes. ### Phase 1 — expand the query (agent-side) Before calling `recall`, rewrite the user's query into a more search-friendly form: - Replace pronouns with the referent ("it" → the actual thing). - Expand abbreviations the embedder is unlikely to know. - Add the obvious synonym when the original term is too narrow (e.g. "auth" → "auth OR authentication"). Don't over-expand. If the query is already specific, leave it alone. One recall call per `/recall` invocation — duplicate calls double embedding load and the merge step is rarely worth it. The daemon's own `search_memory_expanded` exists for the multi-query case; if it matters, use that endpoint instead of issuing parallel calls here. ### Phase 2 — call the MCP tool ``` recall(query="", space=, memory_type=) ``` Inferences (do not ask the user): - `space`: current working directory (e.g. `~/Repos/origin/...` → `"origin"`), the topic being discussed, or whatever space was mentioned in recent turns. Always pass when scope is known; if uncertain, run `list_spaces` later (post-PR-C) or omit. - `memory_type`: only when the query itself names a type ("decision on X", "lesson about Y", "preference for Z"). Otherwise omit and let hybrid search rank. - `limit`: default 10. Use 3-5 for quick lookups, 10-20 for exploration. ### Phase 3 — rerank (agent-side) The daemon returns hits ranked by hybrid search. That ranking is good but not perfect — it doesn't know the user's exact intent. Re-read the returned memories against the *original* query. Promote the ones that directly answer the question; demote ones that just share keywords. Show the user the top 3-5 reranked hits. Surface the rest only if asked. ### Phase 4 — render revision context (per result) Each memory may carry revision fields: `version`, `pending_revision`, `merged_from`, `last_delta_summary`. Most memories are fresh (v1, none set) — render nothing extra for those. Only add a tag line when something meaningful is present. **Condition:** emit the tag line when any of these holds: - `version > 1` - `merged_from` is non-empty - `pending_revision == true` **Format** — one compact line above the memory body: ``` v (merged memories) ← merged_from has K entries v, pending revision against ← pending_revision true v — ← version > 1, delta populated v ← version > 1, no delta ``` Rules: - Merged takes precedence over pending_revision in the label. - Omit `— ` when `last_delta_summary` is empty or null. - Skip the tag line entirely when version == 1 (or null) and no other flag is set. Preserves current output for fresh memories. ## When to use - "What did I say about X?" - "Do you remember the decision on Y?" - Need a specific fact before continuing. ## When NOT to use - Broad session orientation → use `/brief` instead. - Storing a new memory → use `/capture`. ## Hint: write specific queries "Alice database preference" finds more than "database stuff". The semantic matcher rewards specificity. If too many results return, add filters rather than making the query longer.