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code-reviewer代码审查员

Agent Skill

code-reviewer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

423

周安装

18

GitHub Stars

8

下载量

148
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:code-reviewer(代码审查员)
来源仓库:https://github.com/womendefiningai/claude-code-skills
仓库路径:skills/code-reviewer
安装命令:
npx skills add https://github.com/womendefiningai/claude-code-skills --skill code-reviewer
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/womendefiningai/claude-code-skills --skill code-reviewer

简介

code-reviewer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 它可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 安装命令:npx skills add https://github.com/womendefiningai/claude-code-skills --skill code-reviewer
  • 来源仓库:https://github.com/womendefiningai/claude-code-skills

SKILL.md

Code Reviewer Skill

Comprehensive code review skill implementing 2025 research-backed best practices with automated security checks, performance analysis, and quality standards enforcement.

Core Philosophy

Balanced Quality + Security Approach:

  • 50% Security focus (OWASP Top 10, vulnerabilities, authentication)
  • 30% Code quality (maintainability, standards, duplication)
  • 20% Performance (N+1 queries, algorithm complexity, bundle size)

Research Finding: Teams with continuous code review fix vulnerabilities 92% faster than traditional batch reviews.


When to Use This Skill

Auto-invoked when user mentions:

  • "review this code"
  • "check for bugs"
  • "security audit"
  • "analyze this PR"
  • "code review"
  • "check code quality"
  • "review my changes"
  • "find vulnerabilities"
  • "performance check"

Manual invocation:

  • Before committing critical changes
  • Pre-deployment validation
  • After implementing security-sensitive features
  • When integrating SAST tool results

Core Review Workflow

NEW TO CODE REVIEW? See EXAMPLES.md for complete walkthrough examples showing good vs bad reviews.

Phase 1: Automated Analysis (Run First)

Step 1: Identify Code to Review

  • If reviewing specific files: Read those files
  • If reviewing PR/changes: Use git diff to see changes
  • If reviewing entire feature: Identify affected files via grep/glob

Step 2: Run Automated SAST Tools (If Available)

Use the scripts in scripts/ directory:

# Quick security audit
bash scripts/quick-audit.sh

# Or run individual tools:
npm audit                    # Dependency vulnerabilities
npm run lint                 # ESLint code quality
npx prettier --check .       # Code formatting

# Advanced (if installed):
sonar-scanner               # SonarQube
codeql database analyze     # CodeQL
snyk test                   # Snyk security

Step 3: Parse SAST Results

  • Categorize findings by severity (Critical/High/Medium/Low)
  • Filter false positives (document reasoning)
  • Cross-reference with manual checks

Phase 2: Manual Security Analysis

Check OWASP Top 10 2021 (Current Standard):

  1. A01:2021 – Broken Access Control

- Are authentication checks on all protected routes? - Is user input validated before authorization decisions? - Are direct object references protected (IDOR prevention)?

  1. A03:2021 – Injection (SQL, NoSQL, Command)

- Are parameterized queries used instead of string concatenation? - Is user input sanitized before database queries? - Are ORMs used correctly (no raw queries with user input)?

  1. A03:2021 – Cross-Site Scripting (XSS)

- Is user input escaped before rendering in HTML? - Are Content Security Policy headers configured? - Is dangerouslySetInnerHTML avoided or properly sanitized?

  1. A07:2021 – Identification and Authentication Failures

- Are passwords hashed with bcrypt/argon2 (not MD5/SHA1)? - Is session management secure (httpOnly cookies, CSRF tokens)? - Is rate limiting implemented on login endpoints?

  1. A02:2021 – Cryptographic Failures

- Is sensitive data encrypted at rest and in transit? - Are API keys/secrets stored in environment variables (not hardcoded)? - Is HTTPS enforced for all external communication?

See REFERENCE.md for complete OWASP Top 10 checklist

Phase 3: Performance Pattern Detection

Check for Common Performance Issues:

  1. N+1 Query Problem // 🔴 BAD: N+1 queries users.forEach(user => {db.query("SELECT * FROM posts WHERE user_id =?", user.id)}) // ✅ GOOD: Single query with JOIN db.query("SELECT * FROM users LEFT JOIN posts ON users.id = posts.user_id")
  2. O(n²) or Worse Algorithms

- Nested loops over large datasets - Inefficient sorting/searching - Recursive functions without memoization

  1. Missing Database Indexes

- Queries on unindexed columns - WHERE clauses without supporting indexes - JOIN operations on unindexed foreign keys

  1. Memory Leaks

- Event listeners not cleaned up - Closures holding large objects - Unbounded caches

  1. Large Bundle Sizes

- Importing entire libraries instead of specific functions - Unoptimized images - Missing code splitting

See REFERENCE.md for performance pattern catalog

Phase 4: Code Quality Standards

Check TypeScript/JavaScript Standards:

  • No any types without justification comment
  • Proper error handling (no empty catch blocks)
  • No console.log statements (use proper logging)
  • Functions < 50 lines (extract if larger)
  • Cyclomatic complexity < 10
  • No commented-out code
  • Import order follows convention (React → Third-party → Internal → Relative)

Check Naming Conventions:

  • Files: kebab-case (user-service.ts)
  • Components: PascalCase (UserProfile.tsx)
  • Functions/Variables: camelCase (getUserData)
  • Constants: UPPER_SNAKE_CASE (MAX_RETRIES)

See REFERENCE.md for complete standards checklist

Phase 5: Generate Review Report

Use templates from resources/templates/ to create structured output:

  • Comprehensive Review: Use resources/templates/code-review-report.md
  • Security Audit: Use resources/templates/security-review-template.md
  • Performance Review: Use resources/templates/performance-review-template.md
  • Quick Check: Use resources/templates/quick-checklist.md

Example report format:

# Code Review Report

**Verdict:** ✅ APPROVED | ⚠️ APPROVED WITH RESERVATIONS | ❌ REQUIRES REVISION
**Files Reviewed:** [List]
**Review Date:** [ISO Date]

## Critical Issues (Must Fix Before Merge)
[None or list with code snippets]

## High Priority Issues (Fix Within 48h)
[None or list with recommendations]

## Medium Priority Issues (Fix This Sprint)
[None or list]

## Low Priority / Suggestions
[Optional improvements]

## Strengths & Good Practices
[What was done well]

## Metrics
- **Lines Changed:** X
- **Files Modified:** Y
- **Estimated Risk:** Low/Medium/High
- **Test Coverage:** Z%

Integration with SAST Tools

SonarQube Integration

If SonarQube results available:

  1. Read sonar-report.json or access SonarQube API
  2. Focus manual review on issues SonarQube missed:

- Business logic vulnerabilities - Context-specific security issues - Authorization logic

  1. Validate SonarQube findings (check false positives)

Key SonarQube Metrics to Review:

  • Security Hotspots: Require manual validation
  • Code Smells: Maintainability issues (threshold: Grade A or B)
  • Duplications: Keep < 3%
  • Coverage: Target > 80%

CodeQL Integration

If CodeQL scan available:

  1. Review CodeQL alerts in GitHub Security tab
  2. Prioritize alerts by severity:

- Critical/High: Must fix before merge - Medium: Fix within sprint - Low: Backlog

  1. Use CodeQL's suggested fixes when available
  2. Manual review for:

- Authentication flows - Authorization decisions - Cryptographic operations

CodeQL Strengths (88% accuracy):

  • SQL injection detection
  • Path traversal vulnerabilities
  • Command injection
  • Insecure deserialization

Snyk Integration

If Snyk results available:

  1. Run snyk test for dependency vulnerabilities
  2. Run snyk code test for code-level issues
  3. Prioritize by:

- Critical: Fix immediately - High: Fix within 7 days - Medium: Fix within 30 days

  1. Check for available patches: snyk wizard

Snyk Strengths:

  • Dependency vulnerabilities (real-time CVE database)
  • License compliance
  • Container security
  • Infrastructure as Code (IaC) scanning

ESLint + Prettier + npm audit

Basic Security Stack (Always Run):

# Run these three commands ALWAYS
npm audit --audit-level=high    # Dependency vulnerabilities
npm run lint                    # Code quality (ESLint)
npx prettier --check .          # Code formatting

Interpretation:

  • npm audit: Fix all high/critical vulnerabilities
  • ESLint: Must pass with 0 errors (warnings acceptable if documented)
  • Prettier: Auto-fix with npx prettier --write.

Severity Classification

Use this framework to categorize all findings:

🔴 Critical (Blocks Deployment)

  • SQL injection vulnerabilities
  • XSS vulnerabilities (unescaped user input)
  • Authentication bypass
  • Hardcoded secrets/API keys
  • Remote code execution (RCE) risks
  • Sensitive data logged in plain text

Action: STOP. Must fix immediately before proceeding.

🟠 High (Fix Within 48 Hours)

  • Missing authentication checks
  • Insecure session management
  • CSRF vulnerabilities
  • Missing rate limiting on sensitive endpoints
  • Weak cryptography (MD5, SHA1)
  • N+1 query problems in critical paths
  • Memory leaks in production code

Action: Create blocker ticket. Fix before next deployment.

🟡 Medium (Fix This Sprint)

  • Missing input validation (non-critical fields)
  • Inefficient algorithms (O(n²) on small datasets)
  • Missing database indexes (< 1000 rows)
  • Code duplication (> 5 occurrences)
  • Missing error handling
  • Accessibility violations (WCAG AA)

Action: Create ticket. Fix within current sprint.

🔵 Low (Backlog / Nice-to-Have)

  • Code style violations (if not enforced by linter)
  • Missing comments on complex code
  • Minor performance optimizations
  • Refactoring opportunities
  • Documentation improvements

Action: Optional. Add to backlog for future improvement.


Key Metrics to Track

From 2025 Research:

  1. Mean Time to Remediate (MTTR)

- Target: < 7 days for high severity issues - Critical issues: < 24 hours

  1. Defect Density

- Formula: (# of bugs) / (1000 lines of code) - Target: < 1.0 defects per 1000 LOC

  1. Review Coverage

- Target: 100% of changed lines reviewed - Critical paths: 100% manual review (not just automated)

  1. False Positive Rate

- CodeQL: ~5% (best in class) - SonarQube: ~8-10% - Snyk: ~8% - Track your project's rate to calibrate trust


Common Pitfalls to Avoid

  1. Over-reliance on Automation

- Automated tools catch 60-70% of security issues - Manual review essential for business logic, authorization, context-specific issues

  1. Ignoring Performance for Security

- A secure but unusable app is not secure (DoS via performance) - Balance security checks with performance impact

  1. Blocking Every Minor Issue

- Use severity classification to prioritize - Don't let perfection block progress

  1. Missing the Forest for the Trees

- Step back and review overall architecture - Check if the approach is fundamentally sound

  1. Not Checking Test Coverage

- Untested code = unreviewed code - Require tests for all security-critical paths


Quick Reference Checklist

Before approving any code review:

Security:

  • No SQL injection vulnerabilities (parameterized queries)
  • No XSS vulnerabilities (user input escaped)
  • Authentication checks on protected routes
  • Secrets in environment variables (not hardcoded)
  • HTTPS enforced for external APIs
  • CSRF protection on state-changing endpoints

Performance:

  • No N+1 query patterns
  • No O(n²) or worse algorithms on large datasets
  • Database indexes present for queried columns
  • No memory leaks (event listeners cleaned up)
  • Images optimized and lazy-loaded

Code Quality:

  • TypeScript strict mode compliance (no any without justification)
  • Error handling present (no empty catch blocks)
  • No console.log statements
  • Functions < 50 lines
  • Test coverage > 80%
  • No commented-out code

Documentation:

  • Complex logic has explanatory comments
  • Public APIs have JSDoc comments
  • README updated if behavior changed
  • Environment variables documented

Next Steps After Review

If APPROVED (✅):

  1. Merge the PR
  2. Monitor deployment for issues
  3. Update test coverage metrics

If APPROVED WITH RESERVATIONS (⚠️):

  1. Create tickets for medium/low priority issues
  2. Merge if critical/high issues are fixed
  3. Schedule follow-up review

If REQUIRES REVISION (❌):

  1. Provide detailed feedback with code snippets
  2. Block merge until critical issues resolved
  3. Offer to pair-program on fixes if needed

Supporting Files

For detailed information, see:

  • EXAMPLES.md - Complete end-to-end code review examples (good, bad, security-focused)
  • REFERENCE.md - Complete OWASP Top 10 checklist, performance patterns, CWE references
  • FORMS.md - Review report templates overview and guidance
  • resources/templates/ - Ready-to-use review templates

- code-review-report.md - Comprehensive review template - security-review-template.md - Security-focused audit template - performance-review-template.md - Performance analysis template - quick-checklist.md - 3-minute rapid review checklist

  • resources/examples/ - Real-world review examples

- good-review-example.md - What a thorough review looks like - bad-review-example.md - What to avoid (rubber stamp reviews)

  • scripts/ - Automated SAST tool integration scripts

- quick-audit.sh - Quick security audit (Linux/Mac) - quick-audit.bat - Quick security audit (Windows)

Research Citations:


Remember: Code review is not about finding fault—it's about ensuring quality, security, and maintainability. Be constructive, specific, and always suggest solutions alongside identifying problems.

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

36.86%
按下载量换算55

Claude

32.72%
按下载量换算48

Cursor

17.08%
按下载量换算25

Gemini CLI

8.7%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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