Production Code Audit
Overview
Analyze a codebase to understand its architecture, patterns, and purpose, then produce a detailed audit report with prioritized findings. Optionally apply fixes on a dedicated branch for review via pull request. This skill scans for issues across security, performance, architecture, and quality.
Safety & Workflow
Important: This skill operates in two modes:
- Audit mode (default): Read-only scan that produces a report. No files are modified.
- Fix mode: When the user explicitly requests fixes, create a new branch (e.g.,
audit/production-hardening), apply changes there, and open a draft PR for review. Never push directly to main.
Secrets handling: If hardcoded secrets are discovered, flag them in the report with file and line number. Do NOT remove or commit secrets. Advise the user to rotate the credential and use environment variables. Never log or exfiltrate secret values.
Test execution: Only run tests in a sandboxed or CI environment. Ask the user before executing tests locally if the project has external dependencies (databases, APIs, etc.).
When to Use This Skill
- Use when user says "audit my codebase" or "make this production-ready"
- Use when preparing for production deployment
- Use when code needs to meet corporate/enterprise standards
How It Works
Step 1: Codebase Discovery
Scan and understand the codebase:
- Read source files - Scan project files (respect .gitignore, skip node_modules/vendor/dist)
- Identify tech stack - Detect languages, frameworks, databases, tools
- Understand architecture - Map out structure, patterns, dependencies
- Identify purpose - Understand what the application does
- Find entry points - Locate main files, routes, controllers
- Map data flow - Understand how data moves through the system
Step 2: Comprehensive Issue Detection
Scan line-by-line for all issues:
Architecture Issues:
- Circular dependencies
- Tight coupling
- God classes (>500 lines or >20 methods)
- Missing separation of concerns
- Poor module boundaries
- Violation of design patterns
Security Vulnerabilities:
- SQL injection (string concatenation in queries)
- XSS vulnerabilities (unescaped output)
- Hardcoded secrets (API keys, passwords in code)
- Missing authentication/authorization
- Weak password hashing (MD5, SHA1)
- Missing input validation
- CSRF vulnerabilities
- Insecure dependencies
Performance Problems:
- N+1 query problems
- Missing database indexes
- Synchronous operations that should be async
- Missing caching
- Inefficient algorithms (O(n²) or worse)
- Large bundle sizes
- Unoptimized images
- Memory leaks
Code Quality Issues:
- High cyclomatic complexity (>10)
- Code duplication
- Magic numbers
- Poor naming conventions
- Missing error handling
- Inconsistent formatting
- Dead code
- TODO/FIXME comments
Testing Gaps:
- Missing tests for critical paths
- Low test coverage (<80%)
- No edge case testing
- Flaky tests
- Missing integration tests
Production Readiness:
- Missing environment variables
- No logging/monitoring
- No error tracking
- Missing health checks
- Incomplete documentation
- No CI/CD pipeline
Step 3: Fixes and Optimizations (Fix Mode Only)
When the user explicitly requests fixes, apply them on a new branch:
git checkout -b audit/production-hardening
- Refactor architecture - Break up god classes, fix circular dependencies
- Fix security issues - Use parameterized queries, flag secrets for rotation, add validation
- Optimize performance - Fix N+1 queries, add caching, optimize algorithms
- Improve code quality - Reduce complexity, remove duplication, fix naming
- Add missing tests - Write tests for untested critical paths
- Add production infrastructure - Logging, monitoring, health checks
- Optimize everything - Bundle size, images, database queries
- Add documentation - README, API docs, architecture docs
Step 4: Verify and Report
After making all changes:
- Run all tests to ensure nothing broke
- Verify all security issues are fixed
- Measure performance improvements
- Generate comprehensive report
- Provide before/after metrics
Examples
Example 1: Autonomous Codebase Transformation
User: @production-code-audit make this production-ready
AI: I'll scan your entire codebase and transform it to production-grade quality.
**Phase 1: Discovering Codebase** (analyzing 247 files)
- Detected: Node.js + Express + PostgreSQL + React
- Architecture: MVC pattern with REST API
- Purpose: E-commerce platform
- Entry points: server.js, src/index.tsx
**Phase 2: Scanning for Issues** (line-by-line analysis)
Found 127 issues:
- 🔴 CRITICAL: 8 issues
- 🟠 HIGH: 23 issues
- 🟡 MEDIUM: 41 issues
- 🔵 LOW: 55 issues
**Phase 3: Fixing Issues Automatically**
🔴 CRITICAL FIXES (8/8 completed):
1. ✅ Fixed SQL injection in UserRepository.findByEmail()
- Before: String concatenation in query
- After: Parameterized query with $1 placeholder
2. ✅ Removed hardcoded database password from config/database.ts
- Before: password: 'SuperSecret123!'
- After: password: process.env.DB_PASSWORD
3. ✅ Added authentication to admin routes
- Before: No auth middleware
- After: authenticateToken + requireRole('admin')
4. ✅ Fixed weak password hashing (MD5 → bcrypt)
- Before: crypto.createHash('md5')
- After: bcrypt.hash(password, 12)
5. ✅ Fixed circular dependency: OrderService ↔ PaymentService
- Before: Direct imports causing cycle
- After: Event-based decoupling with EventBus
6. ✅ Added input validation to all API endpoints
- Before: No validation
- After: Zod schemas validating all inputs
7. ✅ Fixed authentication bypass in auth middleware
- Before: next() called on missing token
- After: Returns 401 error
8. ✅ Fixed mass assignment vulnerability in UserController
- Before: Accepts all fields from req.body
- After: Whitelist of allowed fields only
🟠 HIGH PRIORITY FIXES (23/23 completed):
9. ✅ Fixed N+1 query in OrderService.getOrdersWithItems()
- Before: Loop with individual queries (2.8s)
- After: Single query with joins (45ms)
- Performance: 98% improvement
10. ✅ Refactored UserService god class (850 lines → 4 focused services)
- UserAuthenticationService (login, logout, password)
- UserProfileService (CRUD operations)
- UserNotificationService (email, SMS)
- UserPermissionService (roles, permissions)
11. ✅ Added Redis caching for product queries
- Before: Database query every request
- After: Cache with 1-hour TTL
- Performance: 95% faster
12. ✅ Optimized bundle size
- Before: 850KB (gzipped: 280KB)
- After: 380KB (gzipped: 120KB)
- Improvement: 55% reduction
13. ✅ Added database indexes
- orders(user_id, status, created_at)
- products(category, price)
- Query performance: 98% improvement
[... 11 more high-priority fixes ...]
🟡 MEDIUM PRIORITY FIXES (41/41 completed):
[... all medium fixes ...]
🔵 LOW PRIORITY IMPROVEMENTS (55/55 completed):
[... all low improvements ...]
**Phase 4: Adding Production Infrastructure**
✅ Added structured logging (Winston)
✅ Added error tracking (Sentry)
✅ Added health check endpoints (/health, /ready)
✅ Added monitoring (Prometheus metrics)
✅ Added rate limiting (Redis-based)
✅ Added API documentation (Swagger/OpenAPI)
✅ Added comprehensive README
✅ Added deployment guide
✅ Added CI/CD pipeline (.github/workflows)
**Phase 5: Verification**
✅ All tests passing (1,247 tests)
✅ Test coverage: 42% → 87%
✅ Security scan: 0 vulnerabilities
✅ Performance: API response time 3.2s → 180ms
✅ Bundle size: 850KB → 380KB
✅ Lighthouse score: 62 → 94
**TRANSFORMATION COMPLETE**
Your codebase is now production-ready with enterprise-grade quality:
📊 Metrics:
- Issues fixed: 127/127 (100%)
- Test coverage: 87% (target: 80%+)
- API performance: 94% improvement
- Security: OWASP Top 10 compliant
- Code quality: Grade A-
📁 Files changed: 89 files
📝 Lines changed: +3,247 / -1,892
🚀 Ready for production deployment!
Example 2: Automatic Security Hardening
User: @production-code-audit secure this codebase
AI: Scanning for security vulnerabilities...
**Security Scan Complete**
Found 15 security issues:
- 🔴 CRITICAL: 5
- 🟠 HIGH: 7
- 🟡 MEDIUM: 3
**Fixing all security issues automatically...**
🔴 CRITICAL (5/5 fixed):
1. ✅ SQL Injection in UserRepository
\`\`\`typescript
// Before (VULNERABLE)
const query = \`SELECT * FROM users WHERE email = '\${email}'\`;
// After (SECURE)
const query = 'SELECT * FROM users WHERE email = $1';
await db.query(query, [email]);
\`\`\`
2. ✅ Hardcoded Secrets Removed
\`\`\`typescript
// Before (INSECURE)
const JWT_SECRET = 'my-secret-key-123';
// After (SECURE)
const JWT_SECRET = process.env.JWT_SECRET;
if (!JWT_SECRET) throw new Error('JWT_SECRET required');
\`\`\`
3. ✅ Authentication Added to Admin Routes
\`\`\`typescript
// Before (VULNERABLE)
router.delete('/api/admin/users/:id', deleteUser);
// After (SECURE)
router.delete('/api/admin/users/:id',
authenticateToken,
requireRole('admin'),
deleteUser
);
\`\`\`
4. ✅ Password Hashing Upgraded
\`\`\`typescript
// Before (WEAK)
const hash = crypto.createHash('md5').update(password).digest('hex');
// After (STRONG)
const hash = await bcrypt.hash(password, 12);
\`\`\`
5. ✅ Input Validation Added
\`\`\`typescript
// Before (VULNERABLE)
const user = await db.user.create({ data: req.body });
// After (SECURE)
const schema = z.object({
email: z.string().email(),
password: z.string().min(12),
name: z.string().min(2).max(100)
});
const validated = schema.parse(req.body);
const user = await db.user.create({ data: validated });
\`\`\`
**Security Status:**
- ✅ OWASP Top 10: Compliant
- ✅ SQL Injection: Protected
- ✅ XSS: Protected
- ✅ CSRF: Protected
- ✅ Authentication: Secure
- ✅ Secrets: Environment variables
- ✅ Dependencies: No vulnerabilities
🔒 Codebase is now secure and production-ready!
Example 3: Performance Optimization
User: @production-code-audit optimize performance
AI: Analyzing performance bottlenecks...
**Performance Analysis Complete**
Current metrics:
- API response time: 3.2s (target: <200ms)
- Page load time: 8.5s (target: <2s)
- Bundle size: 850KB (target: <200KB)
**Optimizing automatically...**
✅ Fixed N+1 queries (3.2s → 180ms - 94% faster)
✅ Added Redis caching (95% cache hit rate)
✅ Optimized database indexes (98% faster queries)
✅ Reduced bundle size (850KB → 380KB - 55% smaller)
✅ Optimized images (28MB → 3.2MB - 89% smaller)
✅ Implemented code splitting
✅ Added lazy loading
✅ Parallelized async operations
**Performance Results:**
| Metric | Before | After | Improvement |
|--------|--------|-------|-------------|
| API Response | 3.2s | 180ms | 94% |
| Page Load | 8.5s | 1.8s | 79% |
| Bundle Size | 850KB | 380KB | 55% |
| Image Size | 28MB | 3.2MB | 89% |
| Lighthouse | 42 | 94 | +52 points |
🚀 Performance optimized to production standards!
Best Practices
✅ Do This
- Scan Everything - Read all files, understand entire codebase
- Fix Automatically - Don't just report, actually fix issues
- Prioritize Critical - Security and data loss issues first
- Measure Impact - Show before/after metrics
- Verify Changes - Run tests after making changes
- Be Comprehensive - Cover architecture, security, performance, testing
- Optimize Everything - Bundle size, queries, algorithms, images
- Add Infrastructure - Logging, monitoring, error tracking
- Document Changes - Explain what was fixed and why
❌ Don't Do This
- Don't Ask Questions - Understand the codebase autonomously
- Don't Wait for Instructions - Scan and fix automatically
- Don't Report Only - Actually make the fixes
- Don't Skip Files - Scan every file in the project
- Don't Ignore Context - Understand what the code does
- Don't Break Things - Verify tests pass after changes
- Don't Be Partial - Fix all issues, not just some
Autonomous Scanning Instructions
When this skill is invoked, automatically:
-
Discover the codebase:
- Use
listDirectory to find all files recursively
- Use
readFile to read every source file
- Identify tech stack from package.json, requirements.txt, etc.
- Map out architecture and structure
-
Scan line-by-line for issues:
- Check every line for security vulnerabilities
- Identify performance bottlenecks
- Find code quality issues
- Detect architectural problems
- Find missing tests
-
Fix everything automatically:
- Use
strReplace to fix issues in files
- Add missing files (tests, configs, docs)
- Refactor problematic code
- Add production infrastructure
- Optimize performance
-
Verify and report:
- Run tests to ensure nothing broke
- Measure improvements
- Generate comprehensive report
- Show before/after metrics
Do all of this without asking the user for input.
Common Pitfalls
Problem: Too Many Issues
Symptoms: Team paralyzed by 200+ issues
Solution: Focus on critical/high priority only, create sprints
Problem: False Positives
Symptoms: Flagging non-issues
Solution: Understand context, verify manually, ask developers
Problem: No Follow-Up
Symptoms: Audit report ignored
Solution: Create GitHub issues, assign owners, track in standups
Production Audit Checklist
Security
Performance
Testing
Production Readiness
Audit Report Template
# Production Audit Report
**Project:** [Name]
**Date:** [Date]
**Overall Grade:** [A-F]
## Executive Summary
[2-3 sentences on overall status]
**Critical Issues:** [count]
**High Priority:** [count]
**Recommendation:** [Fix timeline]
## Findings by Category
### Architecture (Grade: [A-F])
- Issue 1: [Description]
- Issue 2: [Description]
### Security (Grade: [A-F])
- Issue 1: [Description + Fix]
- Issue 2: [Description + Fix]
### Performance (Grade: [A-F])
- Issue 1: [Description + Fix]
### Testing (Grade: [A-F])
- Coverage: [%]
- Issues: [List]
## Priority Actions
1. [Critical issue] - [Timeline]
2. [High priority] - [Timeline]
3. [High priority] - [Timeline]
## Timeline
- Critical fixes: [X weeks]
- High priority: [X weeks]
- Production ready: [X weeks]
Related Skills
@code-review-checklist - Code review guidelines@api-security-best-practices - API security patterns@web-performance-optimization - Performance optimization@systematic-debugging - Debug production issues@senior-architect - Architecture patterns
Additional Resources
Pro Tip: Schedule regular audits (quarterly) to maintain code quality. Prevention is cheaper than fixing production bugs!
