Overview

Provides a systematic approach to conducting code reviews. Focuses on the review process and quality dimensions, not technology-specific patterns.

Scope

Use this skill to:

Conduct systematic code reviews using a structured process
Evaluate code across multiple dimensions (correctness, safety, maintainability)
Provide constructive feedback with clear, actionable recommendations
Determine approval readiness based on quality standards

NOT for

Technology-specific patterns (see appropriate Buki plugins)
Detailed implementation guidance (see discipline-specific agents)

Review Process Overview

Phase 1: Pre-Review Preparation

Before starting review, gather context

Understand the change:

# Review the diff
git diff <base-branch>...HEAD

# Check scope of changes
git diff --stat <base-branch>...HEAD

Identify relevant context:

# Find similar patterns in codebase
grep -r "similar_pattern" .

Verify business context:
- Is there a related issue/ticket? Review requirements
- What domain is impacted?
- What's the user-facing impact?

Phase 2: Systematic Review

Review across these dimensions

1. Correctness

Does it solve the stated problem?
Does business logic align with domain rules?
Are edge cases handled appropriately?
Do tests verify the expected behavior?

Check correctness by

Reading tests first to understand intended behavior
Tracing code paths through the change
Verifying error scenarios are covered
Cross-referencing with requirements

2. Safety

Does it follow authorization/authentication patterns?
Are there breaking changes to APIs or contracts?
Could this expose sensitive data?
Are data operations safe?
Are there potential race conditions or data integrity issues?

Check safety by

Verifying access control on operations
Running compatibility checks for API changes
Checking for proper input validation
Reviewing transaction boundaries
Validating input sanitization

3. Maintainability

Does it follow existing codebase patterns?
Is the code readable and understandable?
Are complex areas documented?
Does it follow the Boy Scout Rule? (leaves code better than found)
Is naming clear and consistent?

Check maintainability by

Comparing with similar code in codebase
Verifying documentation on complex logic
Checking for magic numbers and hard-coded values
Ensuring consistent naming conventions
Looking for commented-out code (anti-pattern)

4. Testability

Are there tests for new functionality?
Do tests cover edge cases and error scenarios?
Are tests clear and maintainable?
Is test data setup appropriate?

Check testability by

Reviewing test coverage of changed code
Verifying both happy and sad paths are tested
Ensuring tests are deterministic and clear
Checking for proper test isolation

5. Performance

Are there obvious performance issues?
Are database queries efficient?
Are expensive operations properly optimized?
Are resources properly managed?

Check performance by

Identifying N+1 query patterns
Checking for missing indexes on queries
Reviewing resource allocation and cleanup
Verifying appropriate data structures

6. Standards Compliance

Does it follow language-specific best practices?
Does it pass all verification checks?
Are there linting or type errors?
Does it follow agreed coding standards?

Check standards compliance by

Running verification suite
Checking for standard pattern violations
Verifying no bypasses of quality gates

Phase 3: Confidence Scoring

Apply confidence scoring to all findings

Each identified issue must include a confidence score (0-100) indicating how certain you are that it's a genuine problem:

Score	Confidence Level	When to Use
100	Absolutely certain	Objective facts: linter errors, type errors, failing tests, security vulnerabilities
90	Very high confidence	Clear violations of documented standards, obvious correctness bugs
80	High confidence	Pattern violations, missing error handling, maintainability issues
70	Moderately confident	Potential issues that need context, possible edge cases
60	Somewhat confident	Questionable patterns, style concerns with codebase precedent
50	Uncertain	Potential improvements without clear precedent
<50	Low confidence	Speculative concerns, personal preferences

CRITICAL FILTERING RULE: Only report issues with confidence ≥80%. Lower-confidence findings create noise and should be omitted.

Confidence Scoring Guidelines

High Confidence (90-100) - Report these:

Verification failures (linting, tests, types)
Security vulnerabilities (SQL injection, XSS, auth bypass)
Correctness bugs with clear reproduction
Breaking API changes
Violations of documented team standards

Medium-High Confidence (80-89) - Report these:

Missing tests for new functionality
Error handling gaps
Performance issues (N+1 queries, missing indexes)
Maintainability concerns with clear patterns
Boy Scout Rule violations

Medium Confidence (60-79) - DO NOT REPORT:

Style preferences without clear codebase precedent
Speculative performance concerns
Alternative approaches without clear benefit

Low Confidence (<60) - DO NOT REPORT:

Personal opinions
"Could be better" without specific impact
Theoretical edge cases without evidence

False Positive Filtering

CRITICAL: Apply these filters to avoid reporting non-issues:

DO NOT REPORT:

❌ Pre-existing issues not introduced by this change (check git blame)
❌ Issues already handled by linters/formatters
❌ Code with explicit lint-ignore comments (respect developer decisions)
❌ Style preferences without documented standards
❌ Theoretical bugs without evidence or reproduction
❌ "Could use" suggestions without clear benefit
❌ Pedantic nitpicks that don't affect quality

VERIFY BEFORE REPORTING:

✅ Run git diff to confirm issue is in changed lines
✅ Check if automated tools already catch this
✅ Verify against documented project standards (CLAUDE.md, CONTRIBUTING.md, etc.)
✅ Confirm the issue actually impacts correctness, safety, or maintainability

Example of False Positive vs. Genuine Issue:

❌ False Positive: "This function could use TypeScript generics for better type safety" (confidence: 60%, style preference, no documented standard)

✅ Genuine Issue: "Function processPayment at services/payment.ts:42 performs database operation without transaction protection, risking data inconsistency if an error occurs mid-operation." (confidence: 90%, documented pattern violation, clear impact)

Phase 4: Feedback & Decision

Provide structured feedback

Summary: High-level assessment
Strengths: What's done well (positive reinforcement)
Issues: Organized by severity with confidence scores:
- Critical (confidence ≥90): Blocks approval (security, correctness, breaking changes)
- Important (confidence ≥80): Should be addressed (maintainability, best practices)
Actionable next steps: Specific changes with file:line references
Decision: Approve, Request Changes, or Needs Discussion

Note: Suggestions/nice-to-haves are intentionally omitted. Focus only on high-confidence, actionable feedback.

Approval Criteria

✅ Approve When

🔄 Request Changes When

Critical issues: Security holes, correctness bugs, breaking changes
Important issues: Pattern violations, missing tests, unclear code
Verification failures not addressed
Business logic doesn't match requirements
Insufficient error handling

💬 Needs Discussion When

Architectural concerns
Unclear requirements
Trade-off decisions needed
Pattern deviation requires justification
Performance implications uncertain

Common Review Pitfalls

Reviewers often miss

Authorization bypasses: Operations without proper access control
Breaking changes: Not checking compatibility
Error handling gaps: Only reviewing happy paths
Test quality: Tests exist but don't actually test edge cases
Domain logic errors: Not understanding business rules
Commented-out code: Leaving dead code instead of removing
Magic numbers: Unexplained constants without names
Over-clever code: Complex when simple would work
Boy Scout Rule violations: Making code worse, not better

Red Flags (Never Approve)

These always require changes

❌ Commented-out code → Remove it (git preserves history)
❌ Secrets or credentials in code → Use secure configuration
❌ Breaking changes without compatibility verification
❌ Tests commented out or skipped → Fix code, not tests
❌ Verification failures ignored → Must all pass
❌ No tests for new functionality → Tests are required
❌ Hard-coded business logic → Should be configurable
❌ Error handling missing → Must handle edge cases
❌ Obvious security vulnerabilities → Must fix immediately

Integration with Development Workflow

Code review fits in Phase 2: Implementation

Implementation → Verification Suite → Code Review → Approval → Merge
                 (automated checks)   (this skill)    (human)

Review happens AFTER verification

Developer runs verification suite
ALL automated checks must pass
Code review skill applied for quality assessment
Issues identified and fixed
Re-verify after fixes
Human reviews and approves for merge

Review is NOT a substitute for verification. Both are required.

Output Format

Structure review feedback as

Review Summary

Brief overall assessment of the change and its quality.

Strengths

✅ What's done well (positive reinforcement)
✅ Good patterns followed
✅ Particularly nice implementations

Issues

Note: Only issues with confidence ≥80% are reported. All findings include confidence scores.

🔴 Critical (Block Approval)

[Issue Title] - file/path.ts:42 - Confidence: 95%

Problem: Clear description of the issue
Impact: Why this is critical (security, correctness, breaking change)
Fix: Specific actionable steps

🟡 Important (Should Address)

[Issue Title] - file/path.ts:89 - Confidence: 85%

Problem: Description of maintainability/quality issue
Impact: How this affects code quality
Suggestion: Recommended improvement

Verification Status

All automated checks passed
API compatibility verified (if applicable)
Tests cover edge cases
Documentation updated

Decision

[APPROVE / REQUEST CHANGES / NEEDS DISCUSSION]

Next Actions

Specific actionable steps with file:line references
Verification commands to re-run
Patterns to consult

Constructive Feedback Principles

When providing feedback

Be specific: Point to exact lines, not vague areas
Explain why: Don't just say "this is wrong," explain the impact
Provide direction: Suggest approaches or patterns
Balance critique with praise: Note what's done well
Prioritize issues: Critical vs. important vs. suggestions
Be respectful: Code is not the person
Assume competence: Ask questions, don't accuse
Teach, don't just correct: Help developers grow

Example of constructive feedback

✅ Good: "In services/payment_service:45, processing payments without transaction protection could lead to data inconsistency if an error occurs mid-operation . Wrap the operation in a transaction to ensure atomicity. Consider the ACID principles from database design."

❌ Bad: "Use transactions here."

Quality Philosophy

Code review ensures

Correctness: Solves the actual problem
Safety: Protects data and follows security patterns
Maintainability: Future developers can understand and modify
Consistency: Follows established patterns
Quality: Meets standards

Remember

Reviews are about code quality, not personal critique
Goal is to improve code AND developer skills
Balance thoroughness with pragmatism
Perfection is not the standard; "good enough" that meets quality bar is
Boy Scout Rule: Leave code better than you found it

📖 code-reviewer