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Code Auditor

Community
mhattingpete
code-auditor

Performs comprehensive codebase analysis covering architecture, code quality, security, performance, testing, and maintainability. Use when user wants to audit code quality, identify technical debt, find security issues, assess test coverage, or get a codebase health check.

Overview

Publishermhattingpete
Repositoryclaude-skills-marketplace
Skill namecode-auditor
Stars
675
Forks
96
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by mhattingpete on GitHub. Read the source before you install it.

Installation

Install the Code Auditor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/mhattingpete/claude-skills-marketplace.git /tmp/claude-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/claude-skills-marketplace/productivity-skills-plugin/skills/code-auditor .claude/skills/code-auditor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Auditor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Auditor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Auditor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Auditor

Comprehensive codebase analysis covering architecture, code quality, security, performance, testing, and maintainability.

When to Use

  • "audit the code"
  • "analyze code quality"
  • "check for issues"
  • "review the codebase"
  • "find technical debt"
  • "security audit"
  • "performance review"

What It Analyzes

1. Architecture & Design

  • Overall structure and organization
  • Design patterns in use
  • Module boundaries and separation of concerns
  • Dependency management
  • Architectural decisions and trade-offs

2. Code Quality

  • Complexity hotspots (cyclomatic complexity)
  • Code duplication (DRY violations)
  • Naming conventions and consistency
  • Documentation coverage
  • Code smells and anti-patterns

3. Security

  • Common vulnerabilities (OWASP Top 10)
  • Input validation and sanitization
  • Authentication and authorization
  • Secrets management
  • Dependency vulnerabilities

4. Performance

  • Algorithmic complexity issues
  • Database query optimization
  • Memory usage patterns
  • Caching opportunities
  • Resource leaks

5. Testing

  • Test coverage assessment
  • Test quality and effectiveness
  • Missing test scenarios
  • Testing patterns and practices
  • Integration vs unit test balance

6. Maintainability

  • Technical debt assessment
  • Coupling and cohesion
  • Ease of future changes
  • Onboarding friendliness
  • Documentation quality

Approach

  1. Explore using Explore agent (thorough mode)
  2. Identify patterns with Grep and Glob
  3. Read critical files for detailed analysis
  4. Run static analysis tools if available
  5. Synthesize findings into actionable report

Thoroughness Levels

  • Quick (15-30 min): High-level, critical issues only
  • Standard (30-60 min): Comprehensive across all dimensions
  • Deep (60+ min): Exhaustive with detailed examples

Output Format

markdown
# Code Audit Report

## Executive Summary
- Overall health score
- Critical issues count
- Top 3 priorities

## Findings by Category

### Architecture & Design
#### 🔴 High Priority
- [Finding with file:line reference]
  - Impact: [description]
  - Recommendation: [action]

#### 🟡 Medium Priority
...

### [Other categories]

## Prioritized Action Plan
1. Quick wins (< 1 day)
2. Medium-term improvements (1-5 days)
3. Long-term initiatives (> 5 days)

## Metrics
- Files analyzed: X
- Lines of code: Y
- Test coverage: Z%
- Complexity hotspots: N

Tools Used

  • Task (Explore agent): Thorough codebase exploration
  • Grep: Pattern matching for issues
  • Glob: Find files by type/pattern
  • Read: Detailed file analysis
  • Bash: Run linters, coverage tools

Success Criteria

  • Comprehensive coverage of all six dimensions
  • Specific file:line references for all findings
  • Severity/priority ratings (Critical/High/Medium/Low)
  • Actionable recommendations (not just observations)
  • Estimated effort for fixes
  • Both quick wins and long-term improvements

Integration

  • feature-planning: Plan technical debt reduction
  • test-fixing: Address test gaps identified
  • project-bootstrapper: Set up quality tooling

Configuration

Can focus on specific areas:

  • Security-only audit
  • Performance-only audit
  • Testing-only assessment
  • Quick architecture review

Frequently asked questions

What does the Code Auditor AI skill do?

Performs comprehensive codebase analysis covering architecture, code quality, security, performance, testing, and maintainability. Use when user wants to audit code quality, identify technical debt, find security issues, assess test coverage, or get a codebase health check.

Why use Code Auditor on TypingMind?

Because you install it once and use it with any model. Code Auditor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Auditor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mhattingpete/claude-skills-marketplace/tree/main/productivity-skills-plugin/skills/code-auditor. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Code Auditor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Auditor?

As many as you like. As long as a model supports skills, you can use Code Auditor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Auditor AI skill free?

Yes. It is published on GitHub by mhattingpete under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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