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memory-audit

核心功能：以DDIA可靠性与DDD有界上下文双视角，从Schema、一致性等五大域诊断记忆系统问题，按P0-P4优先级逐步修复，配套脚本完成基线采集、诊断、验证全流程。典型场景：记忆文件超量、搜索结果异常、项目状态脱节或每月定期检查，适配OpenClaw风格工作区，输出审计报告与修复验证结果

milesnee
milesnee
热度 13.11
最近更新 2026-10-03 19:40:07
分类：知识依赖：代码执行 / 读写文件应用场景：数据处理 / 报告撰写 / 工作流 / 模板

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add memory-audit
Metadata
name
memory-audit
description
Audit and repair agent memory systems using DDIA reliability + DDD bounded-context analysis. Triggers when memory feels stale, bloated, inconsistent, or during periodic health checks.
metadata
{"category":"harness","author":"wheat","version":"1.0.0"}

Memory Audit — 记忆系统架构审计与修复

当记忆系统出现膨胀、不一致、查询质量差、架构耦合等问题时，用软件工程视角系统化诊断和修复。

When to Trigger

  • MEMORY.md 或 AGENTS.md 超过 500 行 / 15KB
  • 搜索返回重复结果或无关结果
  • 日志文件缺少 Front Matter
  • 项目状态与实际脱节
  • 定期健康检查（建议每月一次）

Core Framework

Dual lens:

  1. DDIA (Designing Data-Intensive Applications) — 可靠性/可扩展性/可维护性
  2. DDD (Domain-Driven Design) — 有界上下文/聚合根/防腐层

Five problem domains:

域 核心问题 典型症状
Schema 无Schema约束，自由文本退化 字段不一致，无法程序化解析
Consistency 多存储间状态脱节 MEMORY.md写了旧模型，实际已换
Query 无去重、无联合搜索 搜出重复，漏掉归档
Lifecycle 无GC、无过期标记 历史项目堆积，噪音淹没信号
Coupling 配置/运维/理论混杂 改一处牵一片，token浪费

Workflow

Phase 0: Scope & Baseline

python3 scripts/audit_baseline.py --workspace . --report /tmp/audit-baseline.json

Collect: file counts, line counts, Front Matter coverage, duplication rate, staleness score.

Phase 1: Diagnosis (5 domains × N checks)

python3 scripts/audit_diagnose.py --baseline /tmp/audit-baseline.json --output /tmp/audit-report.md

Each finding → priority bucket (P0-P4):

  • P0 data integrity (broken/dangerous)
  • P1 consistency (drift/misalignment)
  • P2 query capability (search quality)
  • P3 architecture decoupling (coupling/bloat)
  • P4 knowledge systematization (advanced)

Phase 2: Execute Fixes (by priority)

Work P0 → P4 sequentially. Each fix:

  1. Write script/tool
  2. Execute
  3. Verify (must pass before next)
  4. Record trace

Phase 3: Validate

python3 scripts/audit_validate.py --report /tmp/audit-report.md

Phase 4: Handoff

  • Update IMPLEMENT.md with completed items
  • Update MEMORY.md if project status changed
  • Log to daily memory
  • Record trace via trace_logger

Key Scripts

Script Source Purpose
audit_baseline.py this skill Collect workspace metrics
audit_diagnose.py this skill Generate prioritized findings
audit_validate.py this skill Verify fixes passed
memory_gc.py workspace Semi-auto GC scan → suggestions
staleness_check.py workspace Detect stale entries (>60d)
unified_search.py workspace Cross-store federated search
knowledge_graph.py workspace Node/edge graph from memory
gen_references_index.py workspace Auto-generate INDEX.md

Adapting to Other Workspaces

This skill assumes an OpenClaw-style workspace:

workspace/
  MEMORY.md          # long-term semantic memory
  AGENTS.md          # operational handbook
  SOUL.md            # persona/behavior rules
  TOOLS.md           # ops reference
  IMPLEMENT.md       # task tracker
  memory/*.md        # daily episodic logs
  references/*.md    # archived source materials
  traces/            # agent execution traces
  docs/              # migrated detailed docs

For other layouts, adapt audit_baseline.py path constants.

See Also