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Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines.
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npx skills add https://github.com/oimiragieo/agent-studio --skill memory-search명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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SOC 직업 분류 기준
Agent frontmatter enhancements — disallowedTools, mcpServers scoping, fork_eligible field
Context management — pre-compact persistence, threshold alignment, microcompact/circuit breaker detection
Hook enhancements — updatedInput for bash safety prefixes, suppressOutput for verbose blocks, denial-based routing feedback
SKILL.md 표시 중
| name | memory-search |
| description | Semantic search over global agent memory. Use to retrieve previously learned patterns, decisions, gotchas, and workarounds. Prevents stale-context errors across long sessions and multi-agent pipelines. |
| version | 2.0.0 |
| model | sonnet |
| invoked_by | both |
| user_invocable | true |
| tools | ["Bash"] |
| agents | ["developer","architect","planner","qa","code-reviewer","technical-writer","security-architect","devops","researcher"] |
| category | memory |
| tags | ["memory","search","semantic","context","rag","recall"] |
| verified | true |
| lastVerifiedAt | "2026-02-22T00:00:00.000Z" |
| best_practices | ["Run memory-search at the start of any non-trivial task","Use focused queries, not broad ones","Treat results as pointers to canonical sources, not ground truth","Pair high-similarity results with explicit file reads for critical decisions"] |
| error_handling | graceful |
| streaming | supported |
| source | builtin |
| trust_score | 100 |
| provenance_sha | b17fbd9a4c17f016 |
Identify the specific knowledge gap before invoking. Good queries target a concrete decision, pattern, or error — not a broad topic.
Good queries:
"JWT refresh token rotation pattern""Windows path normalization in hooks""BM25 index rebuild performance""agent spawning without task_id error"Bad queries (too broad):
"authentication" — too generic, returns noise"everything about routing" — unfocused"what have we done before" — meaningless for semantic searchInvoke via the Bash tool:
node .claude/lib/memory/memory-search.cjs "your focused search query"
Full invocation:
node .claude/lib/memory/memory-search.cjs "JWT refresh token rotation pattern"
The output format is:
Found N results for: "<query>"
[<source-file>] Similarity: XX.X%
<200-character content preview>...
[<source-file>] Similarity: YY.Y%
<200-character content preview>...
Example real output:
Found 3 results for: "JWT refresh token rotation pattern"
[learnings.md] Similarity: 87.3%
JWT refresh tokens must be stored in httpOnly cookies to prevent XSS. See ADR-045 for detailed rationale and trade-offs vs localStorage approach...
[decisions.md] Similarity: 74.1%
ADR-045: JWT over sessions chosen for stateless architecture. Refresh token rotation every 15 minutes. Invalidate on logout via token blocklist...
[issues.md] Similarity: 61.2%
Known issue: JWT expiry not propagated to frontend — workaround in auth.middleware.ts line 47 until ADR-045 Phase 2 is implemented...
| Similarity | Interpretation | Action |
|---|---|---|
| >80% | Highly relevant — directly matches the query | Read the full source file for complete context |
| 60–80% | Likely relevant — related topic or adjacent pattern | Skim and use if applicable |
| 40–60% | Possibly relevant — tangentially related | Use judgment, may be noise |
| <40% | Probably not relevant | Discard unless nothing better exists |
For results with similarity >60%, read the full source file to get untruncated content:
# Results showed [decisions.md] Similarity: 87.3%
# Follow up with:
Read({ file_path: '.claude/context/memory/decisions.md' })
Or search for the specific ADR/pattern by keyword:
node .claude/lib/memory/memory-search.cjs "ADR-045 JWT"
If Found 0 results, try:
"JWT authentication" instead of "JWT RS256 key rotation"Zero results means the knowledge is either not yet documented or the query was too specific.
</execution_process>
<best_practices>
Run early, not late: Memory search at the START of a task prevents wasted effort. Running it after you have already made decisions is too late to benefit.
One query per knowledge gap: Don't batch all your unknowns into one query. Run targeted queries for each specific gap.
Use the actual error message as the query: If you hit an error, search for the error message text verbatim — it often finds a documented workaround.
Results are pointers, not canonical sources: Always follow up by reading the full source file when similarity is >70%. The 200-char preview is not the complete record.
After a session gap or context compression: Always run memory-search to re-establish current state before proceeding. Context may have been lost.
Cross-agent knowledge sync: Before duplicating an analysis another agent might have done, search memory. The result may already be documented.
</best_practices>
At the start of a long task or after a context compression event:
# What are the current known issues in this area?
node .claude/lib/memory/memory-search.cjs "hook execution errors"
# What patterns have been established for this domain?
node .claude/lib/memory/memory-search.cjs "routing table keyword patterns"
# Any decisions I should be aware of?
node .claude/lib/memory/memory-search.cjs "agent model selection ADR"
</usage_example>
<usage_example title="Debugging — check for known workarounds">
When stuck on an error:
# Search for the exact error message
node .claude/lib/memory/memory-search.cjs "Unable to locate module.exports insertion point"
# Or describe the symptom
node .claude/lib/memory/memory-search.cjs "routing table update fails silently"
If a result appears with >70% similarity, the error has been seen before and may have a documented fix. </usage_example>
<usage_example title="Before making an architectural decision">
Before choosing between two approaches:
# What was decided previously about this tradeoff?
node .claude/lib/memory/memory-search.cjs "ESM vs CJS module format decision"
# Are there ADRs for this pattern?
node .claude/lib/memory/memory-search.cjs "async hook pattern ADR"
If a relevant ADR is found, follow it rather than re-litigating the decision. </usage_example>
<usage_example title="Cross-agent knowledge retrieval">
When you need to know what another agent discovered:
# What did the reflection agent find recently?
node .claude/lib/memory/memory-search.cjs "reflection agent findings skills gap"
# What did the security audit reveal?
node .claude/lib/memory/memory-search.cjs "security audit prompt injection findings"
</usage_example>
ALWAYS run memory-search before assuming no prior context exists. Never claim "there's no documented pattern for this" without first running a targeted search.
NEVER use memory-search results as canonical ground truth. They are summaries and previews. Always read the full source for decisions with material consequences.
NEVER skip memory-search because "I already know about this." Stale in-session assumptions are the primary cause of inconsistent multi-agent behavior.
ALWAYS run multiple targeted queries, not one broad one. A single broad query misses specific matches. Two or three focused queries are more effective.
NEVER run memory-search with a query longer than ~10 words. Over-specified queries degrade similarity matching. Extract the key concept.
| Anti-Pattern | Why It Fails | Correct Approach |
|---|---|---|
"everything about auth" broad query | Too generic — returns unrelated noise | "JWT refresh token rotation" |
| Skipping search because "context is fresh" | In-session context is NOT the same as memory | Always search at task start |
| Treating 200-char preview as full record | Preview truncates at 200 chars — critical detail may be cut | Follow up with Read on the source file |
| Running search AFTER making the decision | Memory lookup must happen before your design choice | Search first, decide second |
| Single query for multiple unknowns | One query can't cover multiple semantic dimensions | Run one query per knowledge gap |
| Ignoring <60% results entirely | Sometimes tangential info is still actionable | Skim low-similarity results before discarding |
| Error | Cause | Resolution |
|---|---|---|
Usage: node .claude/lib/memory/memory-search.cjs "search query" | Query argument missing | Always pass a quoted query string |
Search failed: <error message> | Memory manager unavailable or index not built | Check .claude/lib/memory/memory-manager.cjs and ensure memory system is initialized |
Found 0 results | Query too specific or topic not yet documented | Rephrase query; fall back to direct file search |
| Very slow response (>3s) | Vector similarity computation on cold index | Expected on first call; subsequent calls are faster |
Every agent should run memory-search at task start for any non-trivial work:
# Pattern: topic-scoped recall before starting
node .claude/lib/memory/memory-search.cjs "known patterns for <your task domain>"
node .claude/lib/memory/memory-search.cjs "known issues in <your task area>"
When any tool or command fails unexpectedly:
# Paste the error message directly as the query
node .claude/lib/memory/memory-search.cjs "<exact error text>"
Before any architectural decision:
# Check for existing ADRs on this topic
node .claude/lib/memory/memory-search.cjs "ADR <decision topic>"
At the start of any continued session (especially after context compression):
node .claude/lib/memory/memory-search.cjs "recent decisions <project area>"
node .claude/lib/memory/memory-search.cjs "current known issues"
node .claude/lib/memory/memory-search.cjs "last session learnings"
| Trigger | Query Strategy | Expected Benefit |
|---|---|---|
| Long-running session — context may be stale | "<domain> recent decisions" | Re-sync with documented state |
| New error encountered | "<exact error message>" | Find documented workaround |
| Before architectural decision | "ADR <topic>" or "<decision> trade-off" | Avoid re-litigating settled decisions |
| After context compression | "<current task domain>" | Restore working context |
| Cross-agent handoff | "<previous agent task> findings" | Continue from where other agent left off |
| Before writing a new pattern | "<pattern name> existing" | Avoid duplicating documented guidance |
Before starting:
node .claude/lib/memory/memory-search.cjs "memory-search usage patterns"
After completing:
.claude/context/memory/learnings.md.claude/context/memory/issues.md.claude/context/memory/decisions.mdASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen. This skill exists to recover from exactly that situation.