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tech-debt-tracker

Scan codebases with Python to identify, prioritize, and track technical debt.

Updated Apr 2, 2026
Search Tags:#code quality#technical debt#prioritization#codebase management#tracking
One-click install
npx skills add https://github.com/4lerman/text_evaluator --skill tech-debt-tracker-4lerman
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-tracker
Source: https://github.com/4lerman/text_evaluator/tree/main/.agents/skills/engineering-advanced-skills/tech-debt-tracker
Command: npx skills add https://github.com/4lerman/text_evaluator --skill tech-debt-tracker-4lerman

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ast, regex, json, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps engineering teams manage technical debt by automating detection, prioritization, and tracking across codebases.

Core Features & Use Cases

  • Automated Debt Detection: Scan codebases to identify various types of technical debt.
  • Intelligent Prioritization: Use proven frameworks to prioritize debt based on business impact.
  • Trend Analysis: Track debt evolution over time with executive-friendly dashboards.
  • Use Case: Imagine you have a large codebase with known technical debt. Use this Skill to automatically scan the codebase, prioritize the debt based on impact, and track its resolution over time.

Quick Start

Run the Tech Debt Tracker to scan your codebase and generate a prioritized backlog: run tech-debt-tracker

Frequently Asked Questions about tech-debt-tracker

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

FAQPage Schema
How do I automatically detect and track technical debt in my codebase?▼

Automated debt detection scans your codebase using Python scripts to identify technical debt, which is then prioritized based on business impact and tracked over time using trend analysis.

What is the best way to prioritize technical debt for engineering teams?▼

The best way to prioritize technical debt is by applying proven frameworks that evaluate business impact, allowing teams to systematically rank and address codebase issues based on their actual severity.

Can I use Python ast and regex to scan code quality issues?▼

Yes, you can use Python ast, regex, and json libraries to scan codebases, analyze structural patterns, and organize the resulting technical debt data for code quality assessment.

How do I generate executive-friendly dashboards for technical debt trend analysis?▼

You can generate executive-friendly dashboards for technical debt by tracking debt evolution over time, organizing the scanned data into json formats, and reporting trend analysis to visualize progress.

Does this approach to codebase management work for large engineering teams?▼

Yes, this approach to codebase management is explicitly designed for engineering teams handling codebases with technical debt, providing automated scanning and prioritization to handle large-scale tracking workflows.

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