Memory Recall
vault_memory_recallRetrieve dated memory entries about any topic using hybrid keyword and semantic search, showing the full evolution of preferences, opinions, and facts across all memory files.
Instructions
Recall memory entries about a topic — entry-granular hybrid (keyword + semantic) retrieval across ALL About Me/ files and ALL time. Returns every relevant dated entry sorted oldest-first, so the full evolution of a preference, opinion, or fact is visible — semantic matching finds early entries even when their phrasing differs from the query. Tuned for recall over precision: expect some marginal entries and judge relevance yourself when synthesizing an answer. Content-word queries ("testing philosophy", "sustainable pacing") rank best; a meta-framed query ("opinions on testing") whose relevance cut would come back empty degrades to relaxed any-term keyword matching instead of returning nothing.
Example: vault_memory_recall({ query: "working hours and pacing" }) Example: vault_memory_recall({ query: "opinions on testing", file: "Opinions" })
When to use: Answering "what does my memory say about X?" or "how has my view on Y evolved?" — topic-based recall across memory files. Prefer vault_get_memory to read a known file or section verbatim; prefer vault_search for notes outside the memory layer.
Errors:
No matching entries returns { entries: [], total: 0 }, not an error
An unknown file returns empty results — call vault_list_memory_files to discover valid names
Returns: JSON { entries, total, truncated, search_mode, reranked }. Each entry is { file, section, date, text } — text is the raw entry markdown (wikilinks intact, continuation lines included); file and section feed directly into vault_get_memory or vault_delete_memory. entries ascend by date (oldest first). total counts all matched entries; truncated=true means max_results dropped the least-relevant matches — never a date range — so raise max_results or narrow the query for the complete set. search_mode is "hybrid" when vector matching contributed, "fts" when the entries came from keyword matching alone — including the any-term fallback that rescues a would-be-empty result; reranked is true when the cross-encoder relevance cut was applied.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| file | No | Optional: restrict to one memory file, name without .md (e.g. "Opinions"). Omit for cross-file recall — the default and usual choice. | |
| query | Yes | Topic to recall — natural language works best (semantic matching bridges phrasing drift across months); content words about the topic rank better than meta framing ("testing philosophy" over "opinions on testing") | |
| max_results | No | Cap on returned entries (default 50). When more match, the least-relevant are dropped and truncated=true — never a date range. |