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memory-quality-auditor记忆质量审核员

Agent Skill

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

总安装

1,152

周安装

48

GitHub Stars

25

下载量

384
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:memory-quality-auditor(记忆质量审核员)
来源仓库:https://github.com/oimiragieo/agent-studio
仓库路径:skills/memory-quality-auditor
安装命令:
npx skills add https://github.com/oimiragieo/agent-studio --skill memory-quality-auditor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/oimiragieo/agent-studio --skill memory-quality-auditor

简介

memory-quality-auditor 用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。

  • 它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。
  • 使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。
  • 该技能适用于研究检索类别,主要用于安全相关信息的检索与分析。
  • 使用时需特别注意权限控制和数据脱敏要求,避免对生产环境造成影响。

SKILL.md

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.8%
按下载量换算130

Claude

28.52%
按下载量换算110

Cursor

19.85%
按下载量换算76

Gemini CLI

8.87%
按下载量换算34

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/oimiragieo/agent-studio --skill memory-quality-auditor 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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