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smart-memory-query

// Enforce proactive, query-optimized memory_search usage. Must run memory_search when (1) prior context is referenced, (2) a new task starts, or (3) a proper noun appears. Build short 2–4 token queries by splitting intent to avoid empty AND-based FTS results.

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updated:March 4, 2026
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namesmart-memory-query
descriptionEnforce proactive, query-optimized memory_search usage. Must run memory_search when (1) prior context is referenced, (2) a new task starts, or (3) a proper noun appears. Build short 2–4 token queries by splitting intent to avoid empty AND-based FTS results.
alwaystrue

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)

  1. Split intent — break search intent into 2–3 independent angles. Do not overpack one query.
  2. Extract core tokens — keep only 2–3 key nouns per angle; prioritize proper nouns.
  3. Run multi-query — call memory_search per angle, with 2–4 tokens per query.
  4. 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")