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memory-quality-auditor

Audit memory retrieval quality (drift, staleness, citation-groundedness) and produce remediation backlog.

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설치 방법 보기

포함된 파일(10)

  • SKILL.md4.1 KB
  • commands/memory-quality-auditor.md122 B
  • hooks/post-execute.cjs322 B
  • hooks/pre-execute.cjs439 B
  • references/research-requirements.md400 B
  • rules/memory-quality-auditor.md297 B
  • schemas/input.schema.json582 B
  • schemas/output.schema.json266 B
  • scripts/main.cjs3.9 KB
  • templates/implementation-template.md196 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Memory Quality Auditor

Audit the memory system as a unified retrieval layer (STM/MTM/LTM files + index + spawn citation outcomes).

Scope

  • Retrieval drift signals
  • stale memory ratio
  • evidence injection coverage
  • citation usage/groundedness continuity

Workflow

  1. Read memory artifacts and latest eval reports.
  2. Compute quality metrics and threshold status.
  3. Emit remediation backlog with TDD checks.
  4. Record findings in memory and optional evolution recommendation.

Iron Laws

  1. ALWAYS establish a baseline metric snapshot before auditing — drift is only meaningful relative to a prior measurement; auditing without a baseline produces absolute numbers that cannot identify regression.
  2. NEVER close a memory finding without re-running the affected retrieval query — closing without verification creates false improvement metrics and masks persistent degradation.
  3. ALWAYS include citation-groundedness checks in every audit run — uncited memory injections are the primary source of hallucination in agent spawns; skipping this check leaves the highest-risk failure mode undetected.
  4. NEVER audit only the STM tier — degradation often originates in MTM/LTM promotion corruption; all three tiers must be sampled in every full audit cycle.
  5. ALWAYS emit TDD-ready remediation items with a failing-test condition and expected metric threshold — vague findings ("memory quality is low") cannot be actioned by any agent.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
Auditing without a baselineCannot distinguish regression from steady-state; all findings are ambiguousSnapshot current metrics at session start; compute delta against the previous run
Closing findings without re-checkProduces false-positive resolution; degradation persists silently behind green metricsRe-run the specific retrieval query after each remediation; close only on confirmed green metric
Skipping citation groundednessCitation failures are the leading cause of agent hallucination; missing this check omits the highest-severity defect classInclude citation_coverage and grounded_ratio metrics in every audit report
Full-mode audit on every spawnFull audit is expensive; running it unconditionally inflates cost and slows workflowsUse --mode summary for routine checks; reserve --mode full for scheduled or triggered audits
Auditing STM onlyMTM/LTM corruption is invisible in STM-only scans; stale LTM entries contaminate future sessionsSample all three tiers: STM (current session), MTM (last 10 sessions), LTM (permanent summaries)

Memory Protocol (MANDATORY)

Before starting: Read .claude/context/memory/learnings.md

After completing:

  • New pattern → .claude/context/memory/learnings.md
  • Issue found → .claude/context/memory/issues.md
  • Decision made → .claude/context/memory/decisions.md

ASSUME INTERRUPTION: If it's not in memory, it didn't happen.

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