/code-review-skill

name: code-review-skill
description: |
  Provides comprehensive code review guidance for React 19, Vue 3, Angular 17+, Svelte 5,
  Rust, TypeScript, Java, Java 8, PHP, Ruby, Rails, Python, Django, FastAPI, Go, C#/.NET, Kotlin, Swift,
  NestJS, C/C++, Zig, CSS/Less/Sass, Qt, and more.
  Covers architecture review, performance review, security audit, code quality anti-patterns,
  and common bugs across all ecosystems.
  Use when: reviewing pull requests, conducting PR reviews, code review, reviewing code changes,
  establishing review standards, mentoring developers, architecture reviews, security audits,
  performance reviews, checking code quality, finding bugs, giving feedback on code.
allowed-tools:
  - Read
  - Grep
  - Glob
  - Bash      # 运行 lint/test/build 命令验证代码质量
  - WebFetch  # 查阅最新文档和最佳实践

Code Review Skill

Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement.

When to Use This Skill

• Reviewing pull requests and code changes
• Establishing code review standards for teams
• Mentoring junior developers through reviews
• Conducting architecture reviews
• Creating review checklists and guidelines
• Improving team collaboration
• Reducing code review cycle time
• Maintaining code quality standards

Core Principles

1. The Review Mindset

**Goals of Code Review:**

• Catch bugs and edge cases
• Ensure code maintainability
• Share knowledge across team
• Enforce coding standards
• Improve design and architecture
• Build team culture

**Not the Goals:**

• Show off knowledge
• Nitpick formatting (use linters)
• Block progress unnecessarily
• Rewrite to your preference

2. Effective Feedback

**Good Feedback is:**

• Specific and actionable
• Educational, not judgmental
• Focused on the code, not the person
• Balanced (praise good work too)
• Prioritized (critical vs nice-to-have)

❌ Bad: "This is wrong."
✅ Good: "This could cause a race condition when multiple users
         access simultaneously. Consider using a mutex here."

❌ Bad: "Why didn't you use X pattern?"
✅ Good: "Have you considered the Repository pattern? It would
         make this easier to test. Here's an example: [link]"

❌ Bad: "Rename this variable."
✅ Good: "[nit] Consider `userCount` instead of `uc` for
         clarity. Not blocking if you prefer to keep it."

3. Review Scope

**What to Review:**

• Logic correctness and edge cases
• Security vulnerabilities
• Performance implications
• Test coverage and quality
• Error handling
• Documentation and comments
• API design and naming
• Architectural fit

**What Not to Review Manually:**

• Code formatting (use Prettier, Black, etc.)
• Import organization
• Linting violations
• Simple typos

Review Process

Phase 1: Context Gathering (2-3 minutes)

Before diving into code, understand: 1. Read PR description and linked issue 2. Check PR size (>400 lines? Ask to split) 3. Review CI/CD status (tests passing?) 4. Understand the business requirement 5. Note any relevant architectural decisions

> For large diffs, pipe the diff through [`scripts/pr-analyzer.py`](scripts/pr-analyzer.py) (`git diff main...HEAD | python scripts/pr-analyzer.py`) to triage complexity and get a suggested review approach before reading.

Phase 2: High-Level Review (5-10 minutes)

1. **Architecture & Design** - Does the solution fit the problem?

• For significant changes, consult [Architecture Review Guide](reference/architecture-review-guide.md)
• Check: SOLID principles, coupling/cohesion, anti-patterns

2. **Performance Assessment** - Are there performance concerns?

• For performance-critical code, consult [Performance Review Guide](reference/performance-review-guide.md)
• Check: Algorithm complexity, N+1 queries, memory usage

3. **File Organization** - Are new files in the right places? 4. **Testing Strategy** - Are there tests covering edge cases?

Phase 3: Line-by-Line Review (10-20 minutes)

For each file, check:

• **Logic & Correctness** - Edge cases, off-by-one, null checks, race conditions
• **Security** - Input validation, injection risks, XSS, sensitive data
• **Performance** - N+1 queries, unnecessary loops, memory leaks
• **Maintainability** - Clear names, single responsibility, comments
• **Reuse** - Before accepting new code, search for existing utilities/helpers that could replace it. Check adjacent files and shared modules for similar patterns. See [Universal Quality Guide](reference/code-quality-universal.md) for anti-patterns like parameter sprawl, leaky abstractions, nested conditionals, stringly-typed code, TOCTOU, and no-op updates.

Phase 4: Summary & Decision (2-3 minutes)

1. Summarize key concerns 2. Highlight what you liked 3. Make clear decision:

• ✅ Approve
• 💬 Comment (minor suggestions)
• 🔄 Request Changes (must address)

4. Offer to pair if complex

Review Techniques

Technique 1: The Checklist Method

Use checklists for consistent reviews. See [Security Review Guide](reference/security-review-guide.md) for comprehensive security checklist.

Technique 2: The Question Approach

Instead of stating problems, ask questions:

❌ "This will fail if the list is empty."
✅ "What happens if `items` is an empty array?"

❌ "You need error handling here."
✅ "How should this behave if the API call fails?"

Technique 3: Suggest, Don't Command

Use collaborative language:

❌ "You must change this to use async/await"
✅ "Suggestion: async/await might make this more readable. What do you think?"

❌ "Extract this into a function"
✅ "This logic appears in 3 places. Would it make sense to extract it?"

Technique 4: Differentiate Severity

Use labels to indicate priority:

• 🔴 `[blocking]` - Must fix before merge
• 🟡 `[important]` - Should fix, discuss if disagree
• 🟢 `[nit]` - Nice to have, not blocking
• 💡 `[suggestion]` - Alternative approach to consider
• 📚 `[le