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gquthiergquthier/CLAWG/skills/software-development/requesting-code-review/SKILL.md

requesting-code-review

Skill16 starsChanged 8 months agoMITView on GitHub

Use when completing tasks, implementing major features, or before merging. Validates work meets requirements through systematic review process.

187 other projects use a version of this, 132 of them edited.

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Projects with it also use chinese-code-review, chinese-commit-conventions and 9 more.

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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

Show its rules and text

We split this skill into the rules it gives an agent

13 rules. 5 are common, 7 are distinctive, and 1 is very specific to this project.

  • 5

    Common

    Most of the 173 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    After each task in subagent-driven development

    line 24
  2. Common:

    After completing a major feature

    line 25
  3. Common:

    Before merge to main

    line 26
  4. Common:

    When stuck (fresh perspective)

    line 30
  5. Common:

    Before refactoring (baseline check)

    line 31
  6. Distinctive:

    After complex logic implementation

    line 32
  7. Distinctive:

    When touching critical code (auth, payments, data)

    line 33
  8. Distinctive:

    Before dispatching a reviewer, check yourself:

    line 44
  9. Very specific:

    Use delegate_task to dispatch a focused reviewer:

    line 80
  10. Distinctive:

    Do edge cases work?

    line 150
  11. Distinctive:

    Do they cover edge cases?

    line 161
  12. Distinctive:

    Do they test behavior, not implementation?

    line 162
  13. Distinctive:

    Do all tests pass?

    line 163

“Common” is measured: kept by at least 6 in 10 of the 173 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Requesting Code Review

Overview

Dispatch a reviewer subagent to catch issues before they cascade. Review early, review often.

Core principle: Fresh perspective finds issues you'll miss.

When to Request Review

Mandatory:

  • After each task in subagent-driven development
  • After completing a major feature
  • Before merge to main
  • After bug fixes

Optional but valuable:

  • When stuck (fresh perspective)
  • Before refactoring (baseline check)
  • After complex logic implementation
  • When touching critical code (auth, payments, data)

Never skip because:

  • "It's simple" — simple bugs compound
  • "I'm in a hurry" — reviews save time
  • "I tested it" — you have blind spots

Review Process

Step 1: Self-Review First

Before dispatching a reviewer, check yourself:

  • Code follows project conventions
  • All tests pass
  • No debug print statements left
  • No hardcoded secrets or credentials
  • Error handling in place
  • Commit messages are clear
# Run full test suite
pytest tests/ -q

# Check for debug code
search_files("print(", path="src/", file_glob="*.py")
search_files("console.log", path="src/", file_glob="*.js")

# Check for TODOs
search_files("TODO|FIXME|HACK", path="src/")

Step 2: Gather Context

# Changed files
git diff --name-only HEAD~1

# Diff summary
git diff --stat HEAD~1

# Recent commits
git log --oneline -5

Step 3: Dispatch Reviewer Subagent

Use delegate_task to dispatch a focused reviewer:

delegate_task(
    goal="Review implementation for correctness and quality",
    context="""
    WHAT WAS IMPLEMENTED:
    [Brief description of the feature/fix]

    ORIGINAL REQUIREMENTS:
    [From plan, issue, or user request]

    FILES CHANGED:
    - src/models/user.py (added User class)
    - src/auth/login.py (added login endpoint)
    - tests/test_auth.py (added 8 tests)

    REVIEW CHECKLIST:
    - [ ] Correctness: Does it do what it should?
    - [ ] Edge cases: Are they handled?
    - [ ] Error handling: Is it adequate?
    - [ ] Code quality: Clear names, good structure?
    - [ ] Test coverage: Are tests meaningful?
    - [ ] Security: Any vulnerabilities?
    - [ ] Performance: Any obvious issues?

    OUTPUT FORMAT:
    - Summary: [brief assessment]
    - Critical Issues: [must fix — blocks merge]
    - Important Issues: [should fix before merge]
    - Minor Issues: [nice to have]
    - Strengths: [what was done well]
    - Verdict: APPROVE / REQUEST_CHANGES
    """,
    toolsets=['file']
)

Step 4: Act on Feedback

Critical Issues (block merge):

  • Security vulnerabilities
  • Broken functionality
  • Data loss risk
  • Test failures
  • Action: Fix immediately before proceeding

Important Issues (should fix):

  • Missing edge case handling
  • Poor error messages
  • Unclear code
  • Missing tests
  • Action: Fix before merge if possible

Minor Issues (nice to have):

  • Style preferences
  • Refactoring suggestions
  • Documentation improvements
  • Action: Note for later or quick fix

If reviewer is wrong:

  • Push back with technical reasoning
  • Show code/tests that prove it works
  • Request clarification

Review Dimensions

Correctness

  • Does it implement the requirements?
  • Are there logic errors?
  • Do edge cases work?
  • Are there race conditions?

Code Quality

  • Is code readable?
  • Are names clear and descriptive?
  • Is it too complex? (Functions >20 lines = smell)
  • Is there duplication?

Testing

  • Are there meaningful tests?
  • Do they cover edge cases?
  • Do they test behavior, not implementation?
  • Do all tests pass?

Security

  • Any injection vulnerabilities?
  • Proper input validation?
  • Secrets handled correctly?
  • Access control in place?

Performance

  • Any N+1 queries?
  • Unnecessary computation in loops?
  • Memory leaks?
  • Missing caching opportunities?

Review Output Format

Standard format for reviewer subagent output:

## Review Summary

**Assessment:** [Brief overall assessment]
**Verdict:** APPROVE / REQUEST_CHANGES

---

## Critical Issues (Fix Required)

1. **[Issue title]**
   - Location: `file.py:45`
   - Problem: [Description]
   - Suggestion: [How to fix]

## Important Issues (Should Fix)

1. **[Issue title]**
   - Location: `file.py:67`
   - Problem: [Description]
   - Suggestion: [How to fix]

## Minor Issues (Optional)

1. **[Issue title]**
   - Suggestion: [Improvement idea]

## Strengths

- [What was done well]

Integration with Other Skills

With subagent-driven-development

Review after EACH task — this is the two-stage review:

  1. Spec compliance review (does it match the plan?)
  2. Code quality review (is it well-built?)
  3. Fix issues from either review
  4. Proceed to next task only when both approve

With test-driven-development

Review verifies:

  • Tests were written first (RED-GREEN-REFACTOR followed?)
  • Tests are meaningful (not just asserting True)?
  • Edge cases covered?
  • All tests pass?

With writing-plans

Review validates:

  • Implementation matches the plan?
  • All tasks completed?
  • Quality standards met?

Red Flags

Never:

  • Skip review because "it's simple"
  • Ignore Critical issues
  • Proceed with unfixed Important issues
  • Argue with valid technical feedback without evidence

Quality Gates

Must pass before merge:

  • No critical issues
  • All tests pass
  • Review verdict: APPROVE
  • Requirements met

Should pass before merge:

  • No important issues
  • Documentation updated
  • Performance acceptable

Remember

Review early
Review often
Be specific
Fix critical issues first
Quality over speed

A good review catches what you missed.

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