Code Auditing Skill

SkillProductivity

Task-focused project skill.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Code Auditing Skill skill

What this skill tells your AI

The instructions your AI receives, as published by lidr-academy/lidr-specboot in ai-specs/skills/code-auditing/SKILL.md and read by ahel’s review.

Comprehensive methodology for systematic code quality audits.

When to Use

  • Comprehensive code quality audits
  • Security vulnerability assessments
  • Technical debt identification
  • Pre-release code reviews
  • Best practices verification
  • Library and dependency audits

Audit Phases

Phase 0: Pre-Analysis Setup

  1. Check for project configuration files (package.json, tsconfig.json, etc.)
  2. Identify tech stack and main libraries
  3. Check for linting/formatting configs
  4. Run existing linting/testing commands as baseline
  5. Load documentation for identified core libraries

Phase 1: Discovery

  1. Find all code files by type
  2. Create tracking list for each file
  3. Group files by module/feature for contextual analysis

Phase 2: File-by-File Analysis

For each file, analyze for:

  • Dead code (unused functions, variables, imports)
  • Code smells and anti-patterns
  • Custom implementations that could use established libraries
  • Security vulnerabilities
  • Performance issues
  • Outdated patterns or deprecated APIs
  • Missing error handling
  • Overly complex functions
  • Duplicate code

Phase 3: Best Practices Verification

For every library and framework:

  1. Retrieve official documentation
  2. Compare implementation against official patterns
  3. Identify deviations from recommendations
  4. Note outdated usage patterns
  5. Flag discouraged anti-patterns

Phase 4: Pattern Detection

Look for recurring issues:

  • Common anti-patterns across files
  • Duplicated logic that could be abstracted
  • Inconsistent coding styles
  • Missing error handling patterns

Phase 5: Library Recommendations

For custom implementations:

  1. Check if current libraries provide the functionality
  2. Search for mature ecosystem packages
  3. Verify library health (commits, issues, activity)
  4. Check compatibility with project setup

Phase 6: Comprehensive Report

Generate detailed report with:

  • Executive summary
  • Critical issues requiring immediate attention
  • File-by-file findings
  • Prioritized action plan
  • Effort estimates
  • Library recommendations

Issue Priority Levels

  • Critical - Security vulnerabilities, broken functionality
  • High Priority - Performance bottlenecks, unmaintainable code
  • Medium Priority - Code quality, best practices deviations
  • Low Priority - Style, minor improvements
  • Quick Wins - Less than 30 minutes to fix

Analysis Categories

Security

  • Hardcoded secrets
  • SQL injection risks
  • XSS vulnerabilities
  • Missing input validation
  • Exposed sensitive data

Performance

  • Inefficient algorithms
  • Blocking operations
  • Memory leaks
  • Missing caching opportunities
  • N+1 query patterns

TypeScript/Type Safety

  • Missing type annotations
  • Use of any type
  • Custom types duplicating official types
  • Missing @types packages

Async/Promise Issues

  • Missing await keywords
  • Unhandled promise rejections
  • Callback hell

Dead Code

  • Unused imports and exports
  • Unused functions, classes, and methods
  • Unused variables and types
  • Unreachable code blocks
  • Unused files (not imported anywhere)
  • Unused dependencies

Tools:

  • JavaScript/TypeScript: npx knip --reporter json
  • Python: deadcode . --dry

Important: Always verify tool findings before reporting. Check for:

  • Dynamic imports (import(variable))
  • Framework patterns (React components, decorators)
  • Re-exports for public API
  • Entry points (CLI scripts, serverless handlers)

Resources

See the reference documents for complete methodologies:

  • references/audit-methodology.md - Full 6-phase audit process with detailed checklists
  • references/dead-code-methodology.md - Dead code detection tools, verification, and cleanup workflows

Quick Reference

Before Starting

  • Read project configuration files
  • Identify tech stack and libraries
  • Run existing linters as baseline
  • Create file tracking list

During Audit

  • Mark files as in-progress
  • Analyze each category systematically
  • Note specific line numbers
  • Document before/after examples
  • Mark files as completed

After Audit

  • Categorize all findings by priority
  • Generate comprehensive report
  • Save report to project root
  • Provide brief console summary

Signals

GitHub stars
84
Forks
78
Last commit
Jul 2026

ahel review

  • K1binfo
    installs-packages (in references/dead-code-methodology.md)

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Item type
skill
Key
code-auditing
Source
github.com/lidr-academy/lidr-specboot