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Found 40 Skills
This skill should be used when analyzing technical debt in a codebase, documenting code quality issues, creating technical debt registers, or assessing code maintainability. Use this for identifying code smells, architectural issues, dependency problems, missing documentation, security vulnerabilities, and creating comprehensive technical debt documentation.
AI-powered systematic codebase analysis. Combines mechanical structure extraction with Claude's semantic understanding to produce documentation that captures not just WHAT code does, but WHY it exists and HOW it fits into the system. Includes pattern recognition, red flag detection, flow tracing, and quality assessment. Use for codebase analysis, documentation generation, architecture understanding, or code review.
Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.
Systematically analyze codebase structure, complexity, dependencies, and architectural patterns to understand project organization