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audit-code审计代码

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

190

周安装

8

GitHub Stars

2

下载量

67
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:audit-code(审计代码)
来源仓库:https://github.com/alvesrafa/dev-routine
仓库路径:skills/audit-code
安装命令:
npx skills add https://github.com/alvesrafa/dev-routine --skill audit-code
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/alvesrafa/dev-routine --skill audit-code

简介

audit-code 聚焦代码安全审计,识别凭据泄露、权限漏洞与认证流程缺陷等常见风险点。

  • 适用于生产环境部署前的合规检查、第三方依赖审查或敏感配置项复核等安全敏感任务。
  • 基于项目上下文自动加载 .claude 目录下规范文件,生成定制化安全复核清单。
  • 严禁将工具输出视为最终结论,涉及密钥或用户数据时必须二次确认脱敏处理方式。
  • 支持对开放文件或最近 diff 进行分析,但需人工介入判断高风险操作的实际影响范围。

SKILL.md

Skill: /audit-code

Trigger

The user triggers with:

/audit-code "description of what will be audited"

The description is optional. Without it, the audit is performed on the available general context (open files, recent diff, or conversation).

Reading project context

Before any analysis, search for and read the following files if they exist:

  • .claude/project.md — stack, environments, modules
  • .claude/conventions.md — team standards to check compliance
  • .claude/architecture.md — expected infrastructure and code patterns
  • .claude/known-issues.md — check if any documented problems are present

Stage 0: Clarification

Before auditing, check if the scope is clear enough to apply the right stages.

Ask up to 3 targeted questions if any of the following are true:

  • No description was provided AND no diff/files are visible in context
  • The deployment target is unknown (K8s, serverless, bare VM) and Stage 5 (Infrastructure) is relevant
  • The audit intent is unclear — full pre-deployment audit vs. targeted review of a specific change

Do not ask about code style or team preferences. Only ask when missing context would cause entire stages to be skipped or incorrectly applied.

After asking, wait for the user's reply before proceeding to Stage 1. If the user says "skip questions" or "audit everything", proceed with all 7 stages.

Stage execution

By default, all 7 stages execute in one response.

The user can restrict this: "audit only Stages 1 and 2", "stop after Stage 3", "skip to Stage 5". Respect this literally.

If the user asks for a targeted audit (e.g., "audit the jobs only"), map their request to the relevant stage(s) and run only those.

For each item in every stage, mark:

  • ✅ OK
  • ⚠️ Attention (doesn't block, but should be reviewed)
  • ❌ Critical (blocks deployment)
  • ➖ Not applicable

Stage 1: Security

  • No credentials, secrets, or API keys hardcoded in code
  • Sensitive environment variables read from .env / K8s secrets, never committed
  • Public endpoints with input validation (Form Request / middleware)
  • Authentication and authorization checked on new or modified routes
  • File uploads with type and size validation
  • Queries built with bindings (never direct interpolation of user input)
  • CORS correctly configured for the environment

If any Security item is marked ❌ Critical, after completing Stage 1 ask: "Found critical security issue(s). Proceed with remaining audit stages, or stop here to address security first?"

Stage 2: Database

  • Every migration has functional down()
  • Migrations that alter large tables have strategy to avoid lock (e.g., ADD COLUMN with null default)
  • New indexes created for fields used in frequent WHERE, JOIN, or ORDER BY
  • Soft deletes implemented where data should not be permanently lost
  • No DB::statement with DDL without transaction protection or environment check
  • Seeds and factories don't run in production (guard with App::environment)

Stage 3: Performance

  • No N+1 queries (relations eager-loaded where necessary)
  • Heavy operations outside request cycle (jobs, commands)
  • Jobs with appropriate chunk size for large volumes
  • Cache used where data is read frequently and changes infrequently
  • Pagination on listings that may return many records

Stage 4: Queues and Jobs

  • Jobs implement retry with appropriate backoff
  • Jobs are idempotent (reprocessing causes no side effect)
  • Job failures logged with sufficient context for debugging
  • Correct queue configured (not everything on default)
  • Job timeout explicitly set when operation can be long

Stage 5: Infrastructure and K8s

  • Required environment variables documented (.env.example updated)
  • New secrets added to Key Vault and corresponding K8s manifest
  • Pod CPU/memory resources adequate for expected load
  • Health checks (liveness/readiness) not broken by change
  • No new external service dependency without fallback or circuit breaker
  • New Ingress/routes documented if they affect DNS or TLS

Stage 6: Code quality

  • No unnecessary commented code
  • No forgotten console.log, dd(), dump(), var_dump()
  • Functions and classes with single responsibility
  • No obvious duplication that should be extracted
  • Error cases covered (try/catch where relevant, appropriate error responses)
  • Team conventions respected (.claude/conventions.md)

Stage 7: Tests and validation

  • Main flow tested manually (or automated)
  • Error cases tested (invalid input, service unavailable, permission denied)
  • Rollback planned if deployment needs reverting
  • Feature flag needed for gradual rollout (if applicable)

Check known-issues

After the stages, check if any item in .claude/known-issues.md is relevant to what is being audited. If yes, list which ones and confirm if they were addressed.

Register in known-issues

If the audit reveals a new problem with potential to be recurring, add to .claude/known-issues.md:

## [Category — short title]

Description: problem found.
Context: where it tends to appear.
Solution: how to prevent or fix.
Detected in: [audit-code]

Inform the user: *"⚠️ Recorded in known-issues: [title]"*

Final verdict

## Audit Summary

| Stage | Name | ❌ | ⚠️ | ✅ | ➖ |
|-------|------|----|----|----|-----|
| 1 | Security | N | N | N | N |
| 2 | Database | N | N | N | N |
| 3 | Performance | N | N | N | N |
| 4 | Queues/Jobs | N | N | N | N |
| 5 | Infrastructure | N | N | N | N |
| 6 | Code Quality | N | N | N | N |
| 7 | Tests | N | N | N | N |
| **Total** | | **N** | **N** | **N** | **N** |

## Critical Items (if any)
[numbered and actionable list]

## Attention Items (if any)
[list]

## Known Issues
[new records, or "No new issues recorded"]

## Verdict
✅ READY FOR DEPLOYMENT
⚠️ DEPLOY WITH CAVEATS — resolve attention items after
❌ BLOCKED — resolve critical items before deployment

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

37.58%
按下载量换算25

Claude

30.1%
按下载量换算20

Cursor

17.65%
按下载量换算12

Gemini CLI

10.18%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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。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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