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tech-debt-analyzer

Analyze codebases to identify and categorize technical debt.

4|1|Updated Jan 26, 2026
Search Tags:#code quality#refactoring#maintainability#analysis#technical debt#code audit
One-click install
npx skills add https://github.com/wyattowalsh/agents --skill tech-debt-analyzer-wyattowalsh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-analyzer
Source: https://github.com/wyattowalsh/agents/tree/main/skills/tech-debt-analyzer
Command: npx skills add https://github.com/wyattowalsh/agents --skill tech-debt-analyzer-wyattowalsh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, and includes scripts (resource) and references (resource) and templates (resource) components.

What problem does it solve?

This Skill systematically identifies and quantifies technical debt within a codebase, providing a clear roadmap for remediation and improving long-term maintainability.

Core Features & Use Cases

  • Comprehensive Debt Inventory: Detects complexity issues, dead code, dependency staleness, and pattern inconsistencies.
  • Prioritization & Planning: Ranks debt items by risk and effort, generating actionable roadmaps.
  • Use Case: A development team wants to allocate their next sprint effectively. They use this Skill to identify the most critical technical debt items that pose the highest risk and require the least effort to fix, ensuring maximum impact.

Quick Start

Run a full codebase debt inventory by executing the tech-debt-analyzer skill with the scan command.

Frequently Asked Questions about tech-debt-analyzer

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

FAQPage Schema
How do I identify and categorize technical debt in a codebase?▼

You identify technical debt by scanning the codebase to detect complexity issues, dead code, dependency staleness, and pattern inconsistencies. This analysis tool automates the inventory process using Python scripts to systematically categorize debt items.

What is the best way to prioritize technical debt for a sprint roadmap?▼

Prioritizing technical debt involves ranking identified items by their associated risk and the effort required for remediation. This tool generates an actionable roadmap to help teams prioritize fixes that deliver maximum impact during development cycles.

How do I track technical debt over time to maintain code maintainability?▼

You can track technical debt over time using the tracking mode to monitor debt metrics across successive scans. This approach helps teams visualize remediation progress and ensure long-term code maintainability as the project evolves.

Do I need Python and uv installed to run a code audit for technical debt?▼

Yes, you need Python and the uv dependency manager installed to run this code audit. The technical debt analysis is executed through Python scripts that rely on uv to manage the required execution environment.

Can I generate a deep analysis report for pattern inconsistencies in my code?▼

Yes, you can generate a deep analysis report for pattern inconsistencies by running the deep analysis mode. This mode examines the codebase beyond a surface scan to provide detailed reporting on structural inconsistencies and debt items.

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