code-reviewer

name	code-reviewer
description	Research-backed code review skill with OWASP Top 10 security checks, SAST tool integration (SonarQube, CodeQL, Snyk), performance pattern detection, and automated quality standards enforcement. Auto-invoked for code review, security audit, PR analysis, and bug checking. Implements 2025 best practices with 92% faster vulnerability remediation.

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.

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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

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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)?

2. 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)?

3. 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?

4. 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?

5. 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

3. Missing Database Indexes

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

4. Memory Leaks

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

5. 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%

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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
3. 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
3. Use CodeQL's suggested fixes when available
4. 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
4. 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 .

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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.

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Key Metrics to Track

From 2025 Research:

1. Mean Time to Remediate (MTTR)

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

2. Defect Density

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

3. Review Coverage

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

4. False Positive Rate

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

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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

2. Ignoring Performance for Security

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

3. Blocking Every Minor Issue

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

4. Missing the Forest for the Trees

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

5. Not Checking Test Coverage

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

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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

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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

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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:

• OWASP Code Review Guide: https://owasp.org/www-project-code-review-guide/
• OWASP Top 10 2021: https://owasp.org/Top10/
• Empirical Study (2024): https://arxiv.org/html/2311.16396v2
• CWE Top 25: https://cwe.mitre.org/top25/

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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.