| name | mem-search |
| description | Search persistent memory using keyword or semantic (TF-IDF) search. Use when the user asks "do we have any notes on X", "what do we know about Y", "did we decide anything about Z", "search memory for", "recall anything about", "look up in memory", or any question about past decisions, errors, or context. Also trigger proactively when answering questions where past context would help.
|
mem-search: Smart Memory Search
Search cowork-mem with two complementary modes — keyword FTS5 and semantic TF-IDF.
Use both for important queries; keyword finds exact matches, semantic finds related ideas.
Quick Search
Keyword (FTS5 — fast, exact):
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --limit 10
Semantic (TF-IDF — finds related concepts):
COWORK_MEM_DB=~/mnt/.claude/.cowork-mem/memory.db \
python3 {SKILL_DIR}/scripts/vector_search.py "<query>" --limit 10
Fetch full detail on specific results:
python3 {SKILL_DIR}/scripts/memory_store.py get obs_abc123 obs_def456
When to Use Each Mode
| Mode | Best for |
|---|
| Keyword | Exact tool names, file paths, error messages |
| Semantic | "what did we decide about auth", "any DB issues", "deployment problems" |
Search Workflow
- Start with semantic search — it catches paraphrases
- If results are weak, run keyword search as a fallback
- For any result worth reading in full, call
get <id>
- Synthesize what you found into 1-2 sentences before acting on it
Filter by Type
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --type decision
python3 {SKILL_DIR}/scripts/memory_store.py search "<query>" --type error
Types: decision, file_edit, tool_use, insight, error, note, summary
