Production Code Audit

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/production-code-audit

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

Production Code Audit

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Autonomous Scanning Instructions, Common Pitfalls, Production Audit Checklist, Audit Report Template, Executive Summary.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when user says "make this production-ready"
• Use when user says "audit my codebase"
• Use when user says "make this professional/corporate-level"
• Use when user says "optimize everything"
• Use when user wants enterprise-grade quality
• Use when preparing for production deployment

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Overview

Autonomously analyze the entire codebase to understand its architecture, patterns, and purpose, then systematically transform it into production-grade, corporate-level professional code. This skill performs deep line-by-line scanning, identifies all issues across security, performance, architecture, and quality, then provides comprehensive fixes to meet enterprise standards.

Imported: How It Works

Step 1: Autonomous Codebase Discovery

Automatically scan and understand the entire codebase:

1. Read all files - Scan every file in the project recursively
2. Identify tech stack - Detect languages, frameworks, databases, tools
3. Understand architecture - Map out structure, patterns, dependencies
4. Identify purpose - Understand what the application does
5. Find entry points - Locate main files, routes, controllers
6. Map data flow - Understand how data moves through the system

Do this automatically without asking the user.

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: Automatic Fixes and Optimizations

Fix everything automatically:

1. Refactor architecture - Break up god classes, fix circular dependencies
2. Fix security issues - Use parameterized queries, remove secrets, add validation
3. Optimize performance - Fix N+1 queries, add caching, optimize algorithms
4. Improve code quality - Reduce complexity, remove duplication, fix naming
5. Add missing tests - Write tests for untested critical paths
6. Add production infrastructure - Logging, monitoring, health checks
7. Optimize everything - Bundle size, images, database queries
8. Add documentation - README, API docs, architecture docs

Step 4: Verify and Report

After making all changes:

1. Run all tests to ensure nothing broke
2. Verify all security issues are fixed
3. Measure performance improvements
4. Generate comprehensive report
5. Provide before/after metrics

Examples

Example 1: Ask for the upstream workflow directly

Use @production-code-audit to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @production-code-audit against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @production-code-audit for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @production-code-audit using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: 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

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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

Imported Operating Notes

Imported: 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

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/production-code-audit

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @00-andruia-consultant-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @10-andruia-skill-smith-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @20-andruia-niche-intelligence-v2

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @2d-games

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Additional Resources

• OWASP Top 10
• Google Engineering Practices
• SonarQube Quality Gates
• Clean Code by Robert C. Martin

Pro Tip: Schedule regular audits (quarterly) to maintain code quality. Prevention is cheaper than fixing production bugs!

Imported: Autonomous Scanning Instructions

When this skill is invoked, automatically:

1. 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

2. 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

3. Fix everything automatically:

   • Use

     strReplace

     to fix issues in files
   • Add missing files (tests, configs, docs)
   • Refactor problematic code
   • Add production infrastructure
   • Optimize performance

4. 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.

Imported: 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

Imported: Production Audit Checklist

Security

• No SQL injection vulnerabilities
• No hardcoded secrets
• Authentication on protected routes
• Authorization checks implemented
• Input validation on all endpoints
• Password hashing with bcrypt (10+ rounds)
• HTTPS enforced
• Dependencies have no vulnerabilities

Performance

• No N+1 query problems
• Database indexes on foreign keys
• Caching implemented
• API response time < 200ms
• Bundle size < 200KB (gzipped)

Testing

• Test coverage > 80%
• Critical paths tested
• Edge cases covered
• No flaky tests
• Tests run in CI/CD

Production Readiness

• Environment variables configured
• Error tracking setup (Sentry)
• Structured logging implemented
• Health check endpoints
• Monitoring and alerting
• Documentation complete

Imported: Audit Report Template

# Production Audit Report

**Project:** [Name]
**Date:** [Date]
**Overall Grade:** [A-F]

#### Imported: Executive Summary

[2-3 sentences on overall status]

**Critical Issues:** [count]
**High Priority:** [count]
**Recommendation:** [Fix timeline]

#### Imported: 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]

#### Imported: Priority Actions

1. [Critical issue] - [Timeline]
2. [High priority] - [Timeline]
3. [High priority] - [Timeline]

#### Imported: Timeline

- Critical fixes: [X weeks]
- High priority: [X weeks]
- Production ready: [X weeks]

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.