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Agent Skill · 开发

skill-audit-framework(技能审核框架)

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。

skill-audit-framework 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,594。

总安装 4,533周安装 187GitHub Stars 公开资料未说明下载 1,481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
MIT-0
版本
1.2.0

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-framework(技能审核框架)
来源仓库:https://github.com/enawareness/skill-audit-framework
安装命令:
openclaw skills install skill-audit-framework
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install skill-audit-framework

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

针对AI Agent技能的结构化安全和质量审计框架。教您在安装任何技能之前要检查的内容。

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 OpenClaw;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 openclaw skills install skill-audit-framework;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

    它需要接触敏感数据,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

skill-audit-framework 怎么安装?

在终端执行 openclaw skills install skill-audit-framework。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

skill-audit-framework 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

skill-audit-framework 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

skill-audit-framework 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

skill-audit-framework 用的人多吗?

公开数据是累计安装 4,533 次,近一周安装 187 次,下载 1,481 次。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。

skill-audit-framework 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
skill-audit-framework

技能审核框架 · 本页

4,533—接触敏感数据MIT-0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

name
skill-audit-framework
description
Structured security and quality audit framework for AI agent skills. Teaches you what to check before installing any skill.
homepage
https://github.com/ENAwareness/skill-auditor
metadata
openclaw
emoji
🔍
tags

Skill Auditor 🔍

A structured framework that teaches your agent how to audit ClawHub and MCP skills before you install them. Not a scanner — a systematic review methodology.

Unlike automated scanners that give false confidence, Skill Auditor walks through what matters: permissions, behavior, credentials, and persistence — so you understand exactly what a skill will do on your system.

Why this exists

  • 13.4% of ClawHub skills have critical security issues (Snyk ToxicSkills study)
  • 341 malicious skills were found in a single campaign (ClawHavoc incident, Feb 2026)
  • Automated scanners can miss context-dependent threats and provide false security
  • Understanding what you're installing is better than trusting a green checkmark

How to use

Ask your agent to audit any skill before installing:

Audit this skill before I install it: [skill-name or URL]
Review the security of @author/skill-name on ClawHub
I want to install [skill]. Is it safe?

Audit Framework

The agent follows a 6-domain checklist. Each domain produces a PASS / WARN / FAIL verdict.

1. Identity & Provenance

  • [ ] Author has a GitHub profile with other projects
  • [ ] Skill has a public source repository (not ClawHub-only)
  • [ ] Repository has commit history (not a single-commit dump)
  • [ ] Author identity is consistent across platforms
  • FAIL if: No source repo, no author history, single-commit repo

2. Permission & Scope Analysis

  • [ ] requires.env only lists credentials the skill actually uses
  • [ ] No credentials unrelated to the skill's purpose
  • [ ] File access limited to workspace directory
  • [ ] No requests for system-wide permissions
  • FAIL if: Requests credentials beyond stated purpose, accesses files outside workspace

3. Behavior vs Description Match

  • [ ] Every file in the skill serves the stated purpose
  • [ ] No network calls to undeclared endpoints
  • [ ] No data exfiltration patterns (sending user data to external URLs)
  • [ ] Script behavior matches what SKILL.md describes
  • FAIL if: Hidden functionality, undeclared network calls, description mismatch

4. Credential & Secret Handling

  • [ ] API keys stored in env vars, not hardcoded
  • [ ] No credentials logged or written to non-protected files
  • [ ] OAuth tokens have minimal required scopes
  • [ ] Cached tokens stored in workspace, not system-wide
  • FAIL if: Hardcoded secrets, credentials in logs, excessive OAuth scopes

5. Persistence & Side Effects

  • [ ] Files written only within workspace boundaries
  • [ ] No system-level modifications (crontab, /etc/, systemd)
  • [ ] No auto-start or background processes installed
  • [ ] Uninstall is clean (no orphaned files or processes)
  • FAIL if: System modifications, persistent background processes, dirty uninstall

6. Dependency & Supply Chain

  • [ ] Dependencies are well-known packages (not obscure single-author libs)
  • [ ] No curl | bash or curl | python install patterns
  • [ ] No post-install scripts that download additional code
  • [ ] Package versions are pinned (not latest)
  • FAIL if: Unknown dependencies, pipe-to-shell installs, unpinned versions

Output Format

The agent produces a structured report:

## Skill Audit Report: [skill-name]

Author: [name] | Source: [repo URL or "ClawHub only"]
Version: [X.Y.Z] | Files: [count] | Scripts: [count]

### Verdicts

| Domain                    | Verdict | Notes                |
|---------------------------|---------|----------------------|
| Identity & Provenance     | PASS    |                      |
| Permission & Scope        | WARN    | Requests broad perms |
| Behavior vs Description   | PASS    |                      |
| Credential Handling       | PASS    |                      |
| Persistence & Side Effects| FAIL    | Writes to /etc/      |
| Dependency & Supply Chain | PASS    |                      |

### Overall: ⚠️ WARN — Review flagged items before installing

### Flagged Items
1. [Domain]: [Specific issue and recommendation]

### What to Ask the Author
1. Why does the skill need [permission X]?
2. Can [flagged behavior] be made opt-in?

Limitations

  • This is a review framework, not a deterministic scanner
  • The agent reads and reasons about skill files — it cannot execute or sandbox them
  • Always read the source code yourself for high-privilege skills
  • A PASS verdict means no issues were found, not that the skill is guaranteed safe

Trust Hierarchy

When evaluating skill trust, consider this hierarchy:

  1. Highest trust: Open-source on GitHub + active maintainer + ClawHub Benign scan + you read the code
  2. Moderate trust: GitHub repo exists + ClawHub Benign scan + reasonable permissions
  3. Low trust: ClawHub-only (no source repo) + Suspicious scan + broad permissions
  4. No trust: No source, no author history, requests unrelated credentials

平台分布

OpenClaw

77.81%
按下载量换算1,152

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。目前只有一个公开来源,建议同时核对源仓库。

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