dvcrn Smart Memory Query
Trigger: run memory_search when any of these apply
- T1 Prior context: user references previous decisions, agreements, or history (e.g., “we decided this before”).
- T2 New task: before starting a new topic/task, check prior preferences/decisions.
- T3 Proper noun: project, tool, service, or person name appears.
If unsure, search. Missed context costs more than one extra search. If multiple triggers fire, run separate searches per trigger.
Query-building rules (required)
- Split intent — break search intent into 2–3 independent angles. Do not overpack one query.
- Extract core tokens — keep only 2–3 key nouns per angle; prioritize proper nouns.
- Run multi-query — call
memory_searchper angle, with 2–4 tokens per query. - Merge results — if all are empty, retry once with a single key proper noun.
Examples
T1 “We changed to keep iCloud downloads before, right?”
- ❌
memory_search("user preference root-cause config first suggestion keep iCloud downloads") - ✅
memory_search("iCloud download setting")+memory_search("problem-solving preference")
T1 “Didn’t we plan to migrate to a better structure first?”
- ❌
memory_search("better structure migration FTS path title RRF exact tie-break") - ✅
memory_search("FTS structure migration")+memory_search("RRF tie-break design")
T2 “Let’s start Paddle payment integration.”
- ❌ no
memory_search - ✅
memory_search("Paddle payment")+memory_search("payment integration decision")
T3 “OpenClaw search quality is still poor.”
- ❌
memory_search("OpenClaw search quality is still poor") - ✅
memory_search("OpenClaw search")+memory_search("search quality tuning")
T1+T3 “What happened after switching to bge-m3?”
- ❌
memory_search("what happened after switching to bge-m3") - ✅
memory_search("bge-m3 migration result")+memory_search("embedding model change")
T2 “Set up the new project documentation structure.”
- ❌ no
memory_search - ✅
memory_search("documentation structure preference")+memory_search("project template")