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codebase-audit-pre-push

Deep audit before GitHub push: removes junk files, dead code, security holes, and optimization issues. Checks every file line-by-line for production readiness.

Documentation

Pre-Push Codebase Audit

As a senior engineer, you're doing the final review before pushing this code to GitHub. Check everything carefully and fix problems as you find them.

When to Use This Skill

  • User requests "audit the codebase" or "review before push"
  • Before making the first push to GitHub
  • Before making a repository public
  • Pre-production deployment review
  • User asks to "clean up the code" or "optimize everything"

Your Job

Review the entire codebase file by file. Read the code carefully. Fix issues right away. Don't just note problems—make the necessary changes.

Audit Process

1. Clean Up Junk Files

Start by looking for files that shouldn't be on GitHub:

Delete these immediately:

  • OS files: .DS_Store, Thumbs.db, desktop.ini
  • Logs: *.log, npm-debug.log*, yarn-error.log*
  • Temp files: *.tmp, *.temp, *.cache, *.swp
  • Build output: dist/, build/, .next/, out/, .cache/
  • Dependencies: node_modules/, vendor/, __pycache__/, *.pyc
  • IDE files: .idea/, .vscode/ (ask user first), *.iml, .project
  • Backup files: *.bak, *_old.*, *_backup.*, *_copy.*
  • Test artifacts: coverage/, .nyc_output/, test-results/
  • Personal junk: TODO.txt, NOTES.txt, scratch.*, test123.*

Critical - Check for secrets:

  • .env files (should never be committed)
  • Files containing: password, api_key, token, secret, private_key
  • *.pem, *.key, *.cert, credentials.json, serviceAccountKey.json

If you find secrets in the code, mark it as a CRITICAL BLOCKER.

2. Fix .gitignore

Check if the .gitignore file exists and is thorough. If it’s missing or not complete, update it to include all junk file patterns above. Ensure that .env.example exists with keys but no values.

3. Audit Every Source File

Look through each code file and check:

Dead Code (remove immediately):

  • Commented-out code blocks
  • Unused imports/requires
  • Unused variables (declared but never used)
  • Unused functions (defined but never called)
  • Unreachable code (after return, inside if (false))
  • Duplicate logic (same code in multiple places—combine)

Code Quality (fix issues as you go):

  • Vague names: data, info, temp, thing → rename to be descriptive
  • Magic numbers: if (status === 3) → extract to named constant
  • Debug statements: remove console.log, print(), debugger
  • TODO/FIXME comments: either resolve them or delete them
  • TypeScript any: add proper types or explain why any is used
  • Use === instead of == in JavaScript
  • Functions longer than 50 lines: consider splitting
  • Nested code greater than 3 levels: refactor with early returns

Logic Issues (critical):

  • Missing null/undefined checks
  • Array operations on potentially empty arrays
  • Async functions that are not awaited
  • Promises without .catch() or try/catch
  • Possibilities for infinite loops
  • Missing default in switch statements

4. Security Check (Zero Tolerance)

Secrets: Search for hardcoded passwords, API keys, and tokens. They must be in environment variables.

Injection vulnerabilities:

  • SQL: No string concatenation in queries—use parameterized queries only
  • Command injection: No exec() with user-provided input
  • Path traversal: No file paths from user input without validation
  • XSS: No innerHTML or dangerouslySetInnerHTML with user data

Auth/Authorization:

  • Passwords hashed with bcrypt/argon2 (never MD5 or plain text)
  • Protected routes check for authentication
  • Authorization checks on the server side, not just in the UI
  • No IDOR: verify users own the resources they are accessing

Data exposure:

  • API responses do not leak unnecessary information
  • Error messages do not expose stack traces or database details
  • Pagination is present on list endpoints

Dependencies:

  • Run npm audit or an equivalent tool
  • Flag critically outdated or vulnerable packages

5. Scalability Check

Database:

  • N+1 queries: loops with database calls inside → use JOINs or batch queries
  • Missing indexes on WHERE/ORDER BY columns
  • Unbounded queries: add LIMIT or pagination
  • Avoid SELECT *: specify columns

API Design:

  • Heavy operations (like email, reports, file processing) → move to a background queue
  • Rate limiting on public endpoints
  • Caching for data that is read frequently
  • Timeouts on external calls

Code:

  • No global mutable state
  • Clean up event listeners (to avoid memory leaks)
  • Stream large files instead of loading them into memory

6. Architecture Check

Organization:

  • Clear folder structure
  • Files are in logical locations
  • No "misc" or "stuff" folders

Separation of concerns:

  • UI layer: only responsible for rendering
  • Business logic: pure functions
  • Data layer: isolated

Use Cases

  • User requests "audit the codebase" or "review before push"
  • Before making the first push to GitHub
  • Before making a repository public
  • Pre-production deployment review
  • User asks to "clean up the code" or "optimize everything"