tech-debt-analyzer

Analyze codebases for technical debt using Python static analysis scripts.

88|22|Updated Dec 17, 2025

Search Tags:#code quality #refactoring #maintainability #dependency analysis #technical debt #code smells

Ready to run

npx skills add https://github.com/travisjneuman/.claude --skill tech-debt-analyzer-travisjneuman

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tech-debt-analyzer
Source: https://github.com/travisjneuman/.claude/tree/main/skills/tech-debt-analyzer
Command: npx skills add https://github.com/travisjneuman/.claude --skill tech-debt-analyzer-travisjneuman

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, and includes scripts (resource) and assets (resource) and references (resource) components.

What problem does it solve?

This Skill helps you systematically identify, analyze, and document technical debt within your codebase, improving code quality and maintainability.

Core Features & Use Cases

Code Smells Detection: Identifies issues like large files, complex functions, and debt markers (TODO, FIXME).
Dependency Analysis: Checks for outdated or vulnerable packages.
Severity Assessment: Helps categorize debt by severity (Critical, High, Medium, Low).
Use Case: You suspect your project has accumulated technical debt. Use this Skill to get a comprehensive report on code smells, dependency issues, and suggestions for documentation and prevention strategies.

Quick Start

Use the tech-debt-analyzer skill to analyze the codebase in the 'src' directory.

Frequently Asked Questions about tech-debt-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I scan a codebase for code smells and technical debt?▼

To detect technical debt, the analyzer runs Python static code analysis scripts to scan your codebase for code smells like large files, complex functions, and debt markers such as TODO and FIXME comments.

What is the best way to assess dependency health for technical debt?▼

Assessing dependency health involves checking installed packages for outdated or vulnerable versions. This analyzer automates dependency checks to identify risky packages affecting codebase maintainability.

How are technical debt issues categorized for refactoring planning?▼

Technical debt issues are categorized by severity levels—Critical, High, Medium, and Low—helping you prioritize refactoring efforts and improve code quality based on risk assessment.

Do I need Python to analyze code quality and maintainability?▼

Yes, you need Python installed, as this analyzer requires Python scripts to execute static code analysis, perform dependency checks, and generate technical debt reports.

Can I generate a technical debt report for a specific source directory?▼

Yes, you can target a specific source directory like 'src' for code quality assessment. The analyzer processes the specified directory and outputs a comprehensive technical debt report.

What are the limitations of static code analysis for technical debt detection?▼

Static code analysis limitations include detecting only structural issues like complex functions and debt markers without evaluating runtime behavior or broader architectural design flaws.