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Agent Skill · 研究检索

codebase-audit(代码库审计)

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。

codebase-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 45,360。

总安装 855周安装 36GitHub Stars 28下载 50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:codebase-audit(代码库审计)
来源仓库:https://github.com/majiayu000/claude-arsenal
仓库路径:skills/codebase-audit
安装命令:
npx skills add https://github.com/majiayu000/claude-arsenal --skill codebase-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/majiayu000/claude-arsenal --skill codebase-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。

用于辅助安全审计、权限检查和凭据风险排查。适合分析鉴权逻辑、依赖风险和常见漏洞。不能将工具输出直接作为最终结论。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。涉及密钥或用户数据时,需确认最小权限和操作边界。建议结合人工复核确保安全性。

codebase-audit 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/codebase-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/majiayu000/claude-arsenal --skill codebase-aud…;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

codebase-audit 怎么安装?

在终端执行 npx skills add https://github.com/majiayu000/claude-arsenal --skill codebase-audit。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codebase-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。

codebase-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。

codebase-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。

codebase-audit 用的人多吗?

公开数据是累计安装 855 次,近一周安装 36 次,下载 50 次,GitHub 28 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。

codebase-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
codebase-audit

代码库审计 · 本页

85528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

Codebase Audit — Adaptive Deep Analysis

A comprehensive codebase audit that adapts its agent configuration to the project's tech stack. Each agent uses opus for maximum thoroughness. Results are compiled into a unified report sorted by severity with a phased repair roadmap.

Core Principles

  1. Opus only — All audit agents MUST use model="opus". This is non-negotiable. Smaller models miss subtle cross-file issues.
  2. Depth over breadth — Fewer agents with broader scope and deeper analysis beats many shallow agents. Each agent should trace issues across file boundaries.
  3. Adaptive — Agent count and focus areas vary by project type. Don't waste an agent on "frontend rendering" for a backend-only project.

When to Use

  • User asks to audit/review/analyze an entire codebase
  • User wants to find hidden bugs, silent degradation, or design inconsistencies
  • User asks about technical debt, architecture health, or "what's broken"
  • Before a major refactor or after inheriting an unfamiliar codebase
  • Periodic health check (monthly/quarterly)

Workflow

Phase 0: Tech Stack Detection

Detect the project's tech stack to determine the agent configuration:

Detection checklist:
- package.json / tsconfig.json → TypeScript/JavaScript (React, Next.js, Vue, etc.)
- pyproject.toml / requirements.txt / setup.py → Python (FastAPI, Django, Pydantic, etc.)
- Cargo.toml → Rust (serde, axum, actix, etc.)
- go.mod → Go (gin, echo, gorm, etc.)
- Multiple stacks → Full-stack project (frontend + backend)

Phase 1: Launch Agents (Adaptive)

Based on the detected stack, choose the appropriate agent configuration below. Launch ALL agents in a SINGLE message with model="opus" for every agent.

Read references/agent-prompts.md for complete prompt templates.


Full-Stack Projects (5 agents)

When both frontend and backend exist (e.g., React + FastAPI, Next.js + Go).

#AgentTypeScope (merged dimensions)
1Frontend-Backend ContractreviewerType consistency (field names, types, missing fields) + Rendering pipeline (layout/block/card routing completeness, dead slots, unrendered fields) + Serialization boundaries (models that silently drop fields). This agent reads BOTH sides and traces data across the API boundary.
2Data Integrity & Flowcode-reviewerData pipeline end-to-end: from input through every transformation layer to output. Covers: field resolver filters, serialization/deserialization, model_validate/model_dump, cache read/write symmetry. Finds where fields get silently dropped. Also covers: declaration-execution gaps (registered but unwired handlers, enum without config).
3Error Handling & Securitysecurity-reviewerException patterns (bare except, debug-level errors, warning+fallback), security (hardcoded secrets, injection, unsafe deserialization), silent degradation (error paths that produce user-visible wrong output instead of failing).
4Architecture & Code QualityarchitectLayer violations, circular dependencies, god objects (files >800 lines), code duplication (parallel systems, scattered mapping tables), extension cost analysis (how many files to add a new type), DI pattern consistency.
5Config & Persistencedatabase-reviewerConfig completeness (template/schema vs code expectations, conflicting defaults), cache key completeness (missing code version dimension), DB schema consistency, temp file cleanup, state persistence across restarts.

Backend-Only Projects (4 agents)

When only backend exists (Python API, Rust service, Go microservice, etc.)

#AgentTypeScope
1API Contract & Data Integritycode-reviewerAPI schema vs internal models, serialization boundaries, data pipeline tracing, field dropping, declaration-execution gaps.
2Error Handling & Securitysecurity-reviewerSame as full-stack Agent 3.
3Architecture & Code QualityarchitectSame as full-stack Agent 4.
4Config & Persistencedatabase-reviewerSame as full-stack Agent 5.

Frontend-Only Projects (3 agents)

When only frontend exists (React SPA, Vue app, etc.)

#AgentTypeScope
1Component Architecture & RenderingreviewerType routing completeness, component registration gaps, dead props/slots, state management consistency, API consumption patterns.
2Error Handling & Code Qualitycode-reviewerUnhandled promise rejections, error boundaries, catch-and-ignore patterns, god components, code duplication.
3Config & BuildreviewerBuild config consistency, env variable management, bundle analysis, dead dependencies.

Phase 2: Compile Unified Report

After ALL agents complete, compile findings into a single report:

# [Project Name] Codebase Audit Report

> Audit date: YYYY-MM-DD
> Target: path
> Tech stack: detected stack
> Agents: N (list agent names)

## Summary
| Level | Count | Key Areas |
|-------|-------|-----------|
| Critical | N | ... |
| High/P1 | N | ... |
| Medium/P2 | N | ... |

## Critical (Fix Immediately)
| # | Problem | Agent | Impact |
|---|---------|-------|--------|
For each: file:line, code snippet, risk description, fix suggestion.

## High / P1 (Fix This Week)
### [Category]
| # | Problem | File(s) |
|---|---------|---------|
Details for each.

## Medium / P2 (Plan to Fix)
[Same structure]

## Repair Roadmap
| Phase | Scope | Est. Files |
|-------|-------|------------|
| Phase 0 (urgent) | Critical fixes | ~N files |
| Phase 1 (this week) | High priority | ~N files |
| Phase 2 (next week) | Medium priority | ~N files |
| Phase 3 (ongoing) | Architecture | ~N files |

Deduplication

Since agents have broader overlapping scopes, deduplication is simpler:

  • Same file + same line → merge
  • Same root cause found by multiple agents → keep the most detailed one, note cross-agent confirmation (this actually increases confidence)
  • Severity conflicts → use the highest

Severity Classification

LevelCriteria
CriticalData loss, rendering failure, security vulnerability, complete feature breakage affecting users NOW
High/P1Silent degradation (user sees wrong/incomplete output), type mismatches causing data truncation, missing config causing empty output, architectural violations blocking development
Medium/P2Code duplication, inconsistent patterns, suboptimal error handling, tech debt that slows development but doesn't break features

Stack-Specific Patterns

Read references/stack-patterns.md for technology-specific search patterns.

平台分布

Codex

36.92%
按下载量换算18

Claude

28.69%
按下载量换算14

Cursor

21.2%
按下载量换算11

Gemini CLI

8.94%
按下载量换算4

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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