Code Review Skill

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 (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
   • Check: SOLID principles, coupling/cohesion, anti-patterns
2. Performance Assessment - Are there performance concerns?
   • For performance-critical code, consult Performance Review Guide
   • 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 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 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
• 📚 [learning] - Educational comment, no action needed
• 🎉 [praise] - Good work, keep it up!

Severity levels: 🔴 / 🟡 / 🟢 are the three severity tiers used as the standard across all guides in this skill — 🔴 blocks the merge, 🟡 should be addressed, 🟢 is optional. The remaining markers (💡 / 📚 / 🎉) are non-blocking annotations.

Language-Specific Guides

根据审查的代码语言，查阅对应的详细指南：

Cross-Cutting Guides

Language-agnostic patterns applicable to all code reviews:

Additional Resources

• PR Review Template - PR 审查评论模板
• Review Checklist - 快速参考清单