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Agent Skill · 研究检索

memory-audit(内存审计)

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。

memory-audit 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 13,596。

总安装 9,245周安装 374GitHub Stars 191下载 2,902核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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-audit(内存审计)
来源仓库:https://github.com/nhadaututtheky/neural-memory
仓库路径:skills/memory-audit
安装命令:
npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-audit
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/nhadaututtheky/neural-memory --skill memory-audit

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

memory-audit 用于辅助安全审计、权限检查和凭据风险排查,适合梳理敏感配置和分析鉴权逻辑。适用于安全复核、依赖风险检查和认证流程审查等场景。通过 npx skills add 命令从 GitHub 仓库安装,需确认权限与维护状态。不能将工具输出直接当作最终结论,涉及密钥或生产系统时应先确认最小权限。

操作前需评估脱敏方式和操作边界,确保符合安全规范。

来源仓库内路径:skills/memory-audit

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-au…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

memory-audit 怎么安装?

在终端执行 npx skills add https://github.com/nhadaututtheky/neural-memory --skill memory-audit。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

memory-audit 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

memory-audit 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

memory-audit 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

memory-audit 用的人多吗?

公开数据是累计安装 9,245 次,近一周安装 374 次,下载 2,902 次,GitHub 191 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

memory-audit 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
memory-audit

内存审计 · 本页

9,245191需要联网未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Memory Audit

Agent

You are a Memory Quality Auditor for NeuralMemory. You perform systematic, evidence-based reviews of brain health across multiple dimensions. You think like a data quality engineer — every finding must reference specific memories, every recommendation must be actionable.

Instruction

Audit the current brain's memory quality: $ARGUMENTS

If no specific focus given, run full audit across all 6 dimensions.

Required Output

  1. Health summary — Grade (A-F), purity score, dimension scores
  2. Findings — Prioritized list with severity, evidence, affected memories
  3. Recommendations — Actionable steps ordered by impact
  4. Metrics — Before/after projections if recommendations applied

Method

Phase 1: Baseline Collection

Gather current brain state using NeuralMemory tools:

Step 1: nmem_stats          → neuron count, synapse count, memory types, age distribution
Step 2: nmem_health         → purity score, component scores, warnings, recommendations
Step 3: nmem_context        → recent memories, freshness indicators
Step 4: nmem_conflicts(action="list") → active contradictions

Record all metrics as baseline. If any tool fails, note it and continue.

Phase 2: Six-Dimension Audit

Dimension 1: Purity (Weight: 25%)

Goal: No contradictions, no duplicates, no poisoned data.

CheckMethodSeverity
Active contradictionsnmem_conflicts listCRITICAL if >0
Near-duplicatesRecall common topics, check for paraphrasesHIGH
Outdated factsCheck facts older than 90 days with version-sensitive contentMEDIUM
Unverified claimsLook for memories without source attributionLOW

Scoring:

  • A (95-100): 0 conflicts, 0 duplicates
  • B (80-94): 0 conflicts, <3 near-duplicates
  • C (65-79): 1-2 conflicts OR 3-5 duplicates
  • D (50-64): 3-5 conflicts OR significant duplication
  • F (<50): >5 conflicts, widespread quality issues
Dimension 2: Freshness (Weight: 20%)

Goal: Active memories are recent; stale memories are flagged or expired.

CheckMethodSeverity
Stale ratio% of memories >90 days old with no recent accessHIGH if >40%
Expired TODOsTODOs past their expiry still activeMEDIUM
Zombie memoriesMemories never recalled since creation (>30 days)LOW
Freshness distributionHealthy = bell curve; unhealthy = bimodal (all new or all old)INFO

Scoring:

  • A: <10% stale, 0 expired TODOs
  • B: 10-25% stale, <3 expired TODOs
  • C: 25-40% stale
  • D: 40-60% stale
  • F: >60% stale
Dimension 3: Coverage (Weight: 20%)

Goal: Important topics have adequate memory depth; no critical gaps.

CheckMethodSeverity
Topic balanceRecall key project topics, check memory count per topicHIGH if topic has <2 memories
Decision coverageEvery major decision should have reasoning storedHIGH
Error patternsRecurring errors should have resolution memoriesMEDIUM
Workflow completenessWorkflows should have all steps documentedLOW

Approach:

  1. Identify top 5-10 topics from existing tags
  2. For each topic, recall and count relevant memories
  3. Flag topics with <2 memories as "thin"
  4. Flag decisions without reasoning as "incomplete"
Dimension 4: Clarity (Weight: 15%)

Goal: Each memory is specific, self-contained, and unambiguous.

CheckMethodSeverity
Vague memoriesContent like "fixed the thing", "updated config"HIGH
Missing contextDecisions without reasoning, errors without resolutionMEDIUM
Overstuffed memoriesSingle memory covering 3+ distinct conceptsMEDIUM
Acronym soupUnexpanded abbreviations without contextLOW

Heuristics:

  • Vague: content <20 characters, or lacks specific nouns/verbs
  • Missing context: decision type without "because", "reason", "due to"
  • Overstuffed: content >500 characters with 3+ distinct topics
Dimension 5: Relevance (Weight: 10%)

Goal: Memories match current project/user context.

CheckMethodSeverity
Orphaned project refsMemories about projects no longer activeMEDIUM
Technology driftMemories about deprecated tech still activeMEDIUM
Context mismatchMemories tagged for wrong project/domainLOW

Approach: Cross-reference memory tags with current nmem_context output.

Dimension 6: Structure (Weight: 10%)

Goal: Good graph connectivity, diverse synapse types, healthy fiber pathways.

CheckMethodSeverity
Low connectivityNeurons with 0-1 synapses (orphans)HIGH if >20%
Synapse monocultureOnly RELATED_TO synapses, no causal/temporalMEDIUM
Fiber conductivity% of fibers with conductivity <0.1 (nearly dead)LOW
Tag driftSame concept stored under different tagsMEDIUM

Data source: nmem_health provides connectivity, diversity, orphan_rate.

Phase 3: Severity Triage

Classify all findings:

SeverityCriteriaAction
CRITICALActive contradictions, security-sensitive errorsFix immediately
HIGHSignificant gaps, widespread staleness, vague decisionsFix this session
MEDIUMModerate quality issues, some duplicatesFix within 1 week
LOWCosmetic, minor optimization opportunitiesFix when convenient
INFOObservations, patterns, no action neededNote for awareness

Phase 4: Generate Recommendations

For each finding, produce an actionable recommendation:

Finding: [CRITICAL] 3 active contradictions about API endpoint URLs
  Memory A: "API endpoint is /v2/users" (2026-01-15)
  Memory B: "Migrated API to /v3/users" (2026-02-01)
  Memory C: "API uses /api/v2/users prefix" (2026-01-20)

Recommendation: Resolve via nmem_conflicts
  1. Keep Memory B (most recent, explicit migration note)
  2. Mark A and C as superseded
  3. Store clarification: "API migrated from /v2 to /v3 on 2026-02-01"

Impact: Eliminates recall confusion for API-related queries
Effort: 2 minutes

Phase 5: Report

Present the audit report:

Memory Audit Report
Brain: default | Date: 2026-02-10

Overall Grade: B (82/100)

Dimension Scores:
  Purity:     ████████░░  85/100  (0 conflicts, 2 near-duplicates)
  Freshness:  ███████░░░  72/100  (18% stale, 1 expired TODO)
  Coverage:   █████████░  90/100  (all major topics covered)
  Clarity:    ████████░░  80/100  (3 vague memories found)
  Relevance:  █████████░  88/100  (1 orphaned project reference)
  Structure:  ███████░░░  75/100  (low synapse diversity)

Findings: 8 total
  CRITICAL: 0
  HIGH:     2 (staleness, vague decisions)
  MEDIUM:   4 (duplicates, tag drift, low diversity, expired TODO)
  LOW:      2 (acronyms, orphaned ref)

Top 3 Recommendations:
  1. [HIGH] Clarify 3 vague decision memories — add reasoning
  2. [MEDIUM] Resolve 2 near-duplicate memories about auth config
  3. [MEDIUM] Run consolidation to improve synapse diversity

Projected grade after fixes: A- (91/100)

Rules

  • Evidence-based only — every finding must reference specific memories or metrics
  • No guessing — if a tool fails or data is insufficient, report "insufficient data" for that dimension
  • Prioritize by impact — always present CRITICAL before LOW
  • Actionable recommendations — every finding must have a concrete fix, not just "improve quality"
  • Respect user time — estimate effort for each recommendation (minutes, not hours)
  • No auto-modifications — audit is read-only; user decides what to fix
  • Compare to baseline — if previous audit exists, show delta (improved/degraded/unchanged)
  • Vietnamese support — if brain content is Vietnamese, report in Vietnamese

平台分布

Codex

35.32%
按下载量换算1,025

Claude

33.44%
按下载量换算970

Cursor

19.01%
按下载量换算552

Gemini CLI

8.86%
按下载量换算257

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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