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tech-debt-tracker

Scan Python codebases to detect, prioritize, and track technical debt.

Updated Mar 28, 2026
Search Tags:#code quality#technical debt#prioritization#debt management#code scanning
One-click install
npx skills add https://github.com/saschadudkin-sketch/rezidence4 --skill tech-debt-tracker-saschadudkin-sketch
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-tracker
Source: https://github.com/saschadudkin-sketch/rezidence4/tree/main/.agents/skills/tech-debt-tracker
Command: npx skills add https://github.com/saschadudkin-sketch/rezidence4 --skill tech-debt-tracker-saschadudkin-sketch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, 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 identifying, prioritizing, and tracking it across codebases.

Core Features & Use Cases

  • Automated Debt Detection: Scan codebases to automatically detect 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 accumulated technical debt. Use this Skill to scan the codebase, prioritize the debt, and track its resolution over time.

Quick Start

Use the tech-debt-tracker skill to scan your codebase for technical debt and generate a prioritized backlog.

Frequently Asked Questions about tech-debt-tracker

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

FAQPage Schema
How do I identify and prioritize technical debt across a large codebase?▼

Technical debt identification and prioritization involves scanning your codebase to automatically detect debt, then applying proven frameworks to rank items based on business impact. This generates a prioritized backlog for your engineering team.

What is technical debt tracking and how does trend analysis help manage code quality?▼

Technical debt tracking monitors accumulated code quality issues over time. Trend analysis helps manage code quality by tracking debt evolution, providing executive-friendly dashboards that visualize progress for engineering teams.

Do I need Python to scan my codebase for technical debt?▼

Yes, you need Python to scan your codebase for technical debt. The automated debt detection and code scanning features rely on a Python environment to execute the necessary analysis scripts.

What's the best way to track technical debt resolution over time?▼

The best way to track technical debt resolution over time is by continuously scanning your codebase and using trend analysis. This monitors debt evolution and provides executive-friendly dashboards to visualize code quality improvements.

Can I generate a prioritized backlog from automated code scanning results?▼

Yes, you can generate a prioritized backlog from automated code scanning results. The scanning detects various types of technical debt, and intelligent prioritization frameworks rank them based on business impact.

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