How long does a typical code audit take?

Audit depth is configurable: Quick audits take 15-30 minutes, Standard audits take 30-60 minutes, and Deep audits can take over an hour for exhaustive analysis.

Does it provide specific file references for found issues?

Yes, every finding in the generated report includes specific file and line references along with impact descriptions and suggested actions.

Can I focus the audit on specific areas like security only?

Yes, the skill can be configured to focus exclusively on security, performance, testing, or high-level architectural reviews based on your needs.

How does it help with project management?

The skill generates a prioritized action plan that categorizes fixes into quick wins, medium-term improvements, and long-term strategic initiatives.

What programming languages does Code Auditor support?

The Code Auditor is language-agnostic; it uses pattern matching, structural analysis, and standard CLI tools to analyze any codebase Claude can access.

Code Auditor

Name: Code Auditor
Author: prof-ramos

byprof-ramos

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Security & Testing

Performs exhaustive codebase analysis to identify security vulnerabilities, technical debt, and architectural improvements.

About

The Code Auditor skill provides a comprehensive evaluation of your repository across six critical dimensions: architecture, code quality, security, performance, testing, and maintainability. By utilizing a multi-layered approach—combining pattern matching, deep file analysis, and static analysis tools—it synthesizes complex codebase data into an actionable report. This skill is ideal for teams looking to assess the health of a legacy project, prepare for a production release, or establish a baseline for technical debt reduction with prioritized recommendations and effort estimates.

Key Features

Technical debt assessment focused on complexity hotspots and code duplication
Performance optimization targeting database queries and memory usage patterns
Comprehensive security scanning for OWASP vulnerabilities and secrets management
Architectural review of module boundaries and dependency management
1 GitHub stars
Detailed test coverage assessment and identification of missing scenarios

Use Cases

Performing a thorough security and quality audit before a major production release
Conducting a performance and architectural review to resolve scaling bottlenecks
Evaluating a legacy codebase to identify and prioritize technical debt reduction

About

Key Features

Technical debt assessment focused on complexity hotspots and code duplication
Performance optimization targeting database queries and memory usage patterns
Comprehensive security scanning for OWASP vulnerabilities and secrets management
Architectural review of module boundaries and dependency management
1 GitHub stars
Detailed test coverage assessment and identification of missing scenarios

Use Cases

Performing a thorough security and quality audit before a major production release
Conducting a performance and architectural review to resolve scaling bottlenecks
Evaluating a legacy codebase to identify and prioritize technical debt reduction