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skill-audit技能审核

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

245

周安装

10

GitHub Stars

公开资料未说明

下载量

78
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:skill-audit(技能审核)
来源仓库:https://github.com/nayuta/agent-skills
仓库路径:skills/skill-audit
安装命令:
npx skills add https://github.com/nayuta/agent-skills --skill skill-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/nayuta/agent-skills --skill skill-audit

简介

skill-audit 用于辅助安全审计、权限检查和常见漏洞排查,适合让 Agent 梳理敏感配置或生成复核清单。

  • 适用于研究检索类任务,可协助分析鉴权逻辑与依赖风险。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装,具体路径为 skills/skill-audit。
  • 使用时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。
  • 建议结合原始 README 文档进一步核验功能细节与使用边界。

SKILL.md

Skill Audit

Purpose

Systematically validate Claude Code / Agent Skills directories for correctness, security, and quality. Combines static analysis (deterministic checks) with AI reasoning (judgment on trigger scope, coexistence, context efficiency).

Workflow

Step 1: Static Analysis

Run the bundled auditor from the repository root:

python skills/skill-audit/scripts/skill_audit.py <skill-path> --surface claude-code

For agent-api mode (strict, requires name and description):

python skills/skill-audit/scripts/skill_audit.py <skill-path> --surface agent-api

JSON output for programmatic use:

python skills/skill-audit/scripts/skill_audit.py <skill-path> --json

Exit code is non-zero when the worst score drops below 70.

Step 2: Read the Skill

Read SKILL.md and any directly referenced files (scripts, references, assets). Do not read files that are not referenced — they are background context only.

Step 3: AI Judgment Review

Assess four areas that static checks cannot cover:

Discovery problems

  • Is the description narrow enough to avoid false triggers?
  • Does it overlap significantly with adjacent skills in the same directory?
  • Would a model reliably select this skill for its intended use cases?

Isolation problems

  • Are all referenced files present and accessible?
  • Does the skill rely on environment assumptions not stated in compatibility?
  • Are external dependencies (APIs, CLIs, credentials) documented?

Coexistence problems

  • Does this skill's description overlap with other skills in the directory?
  • Could two skills be triggered simultaneously causing conflict?
  • Are trigger boundaries clear and mutually exclusive where needed?

Efficiency problems

  • Is SKILL.md under 500 lines? (warn above this threshold)
  • Is large reference content in separate files rather than inline?
  • Does the skill regenerate the same code on every run that could be a script?
  • Are volatile business rules or policies externalizable?

Step 4: Report

Present findings in three severity buckets:

## Skill Audit: <skill-name>

**Score**: <0-100> | **Surface**: <claude-code|agent-api>
**Static findings**: N errors, N warnings, N info

---

### Blockers

Issues that prevent safe use or deployment.

- [ERROR] <code> @ <file>:<line> — <message>
  **Why it matters**: <impact>
  **Fix**: <exact change>

### Important

Issues that reduce reliability or increase risk.

- [WARN] <code> @ <file>:<line> — <message>
  **Why it matters**: <impact>
  **Fix**: <exact change>

### Optional

Improvements that increase efficiency or clarity.

- [INFO] <code> — <message>
  **Suggestion**: <recommendation>

### Evaluation Gaps

Missing test cases for the eval suite:

- should-trigger: <prompt that should activate this skill>
- should-not-trigger: <prompt that should NOT activate this skill>
- ambiguous: <edge case worth tracking>

### Efficiency Notes

<Estimate where the skill wastes context, time, or tool calls>

If the score is 100 and no AI judgment issues are found, report:

## Skill Audit: <skill-name>

**Score**: 100 | No issues found. Safe to use as-is.

Static Checks Covered

CategoryChecks
StructureSKILL.md presence, YAML frontmatter parseable
Metadataname format (^[a-z0-9-]{1,64}$), reserved words, description length
BodyNon-empty, under 500 lines
LinksLocal markdown links resolve to existing files
SecretsHardcoded API keys, tokens, passwords
Network accessExternal network calls embedded in skill instructions
Path traversalDot-dot-slash escapes in skill instructions
Adversarial contentInstructions designed to conceal actions or circumvent safety controls
PortabilityWindows-style paths
PrivilegeWildcard allowed-tools
Time-sensitive wordingtoday, yesterday, latest, current policy

Bundled Resources

FilePurpose
scripts/skill_audit.pyStatic auditor — run directly or import as module
evals/example-evals.yamlExample evaluation schema for dynamic testing

Integration

  • Run in CI on every change to any skill directory
  • Add a Claude Code hook that triggers this audit after edits to .claude/skills/**
  • Gate new skill versions on a passing score (≥ 70)
  • Pair with validate-fix to automatically resolve discovered issues

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

按任务关键词查找相关 Skills

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

32.04%
按下载量换算25

Claude

29.99%
按下载量换算23

Cursor

20.03%
按下载量换算16

Gemini CLI

10%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。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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