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/code-auditing

Systematic methodology for comprehensive codebase analysis — security review, technical debt identification, dead code detection, code quality checks, and best-practices verification against official library documentation.

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somepulp-agents
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Install
$ npx -y skills add jeffrigby/somepulp-agents --skill code-auditing --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/code-auditing

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Systematic methodology for comprehensive codebase analysis — security review, technical debt identification, dead code detection, code quality checks, and best-practices verification against official library documentation.

SKILL.md

code-auditing.SKILL.md
name: code-auditing
description: Systematic methodology for comprehensive codebase analysis — security review, technical debt identification, dead code detection, code quality checks, and best-practices verification against official library documentation.
when_to_use: When the user asks to "audit code", "find technical debt", "perform a security review", "identify dead code", "analyze code quality", "check best practices", or "run a code audit".
allowed-tools: Read, Grep, Glob, Bash, WebSearch, WebFetch

Code Auditing Skill

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 .`

**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:

  • `${CLAUDE_SKILL_DIR}/references/audit-methodology.md` - Full 6-phase audit process with detailed checklists
  • `${CLAUDE_SKILL_DIR}/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
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