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ThalesAndrades
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tech-debt-tracker

Detect, score, and track technical debt in codebases using static analysis.

Updated Aug 23, 2026
Search Tags:#project management#code analysis#technical debt#prioritization#risk assessment#trending
One-click install
npx skills add https://github.com/ThalesAndrades/forumfoup2026 --skill tech-debt-tracker-thalesandrades
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-tracker
Source: https://github.com/ThalesAndrades/forumfoup2026/tree/main/.claude/skills/tech-debt-tracker
Command: npx skills add https://github.com/ThalesAndrades/forumfoup2026 --skill tech-debt-tracker-thalesandrades

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

It helps engineering teams systematically identify, assess, and prioritize technical debt to improve software quality.

Core Features & Use Cases

  • Automated Debt Detection: Scan codebases for technical debt signals using AST parsing and regex patterns.
  • Debt Prioritization: Score and rank debt items based on impact, effort, and strategic frameworks.
  • Trend Analysis: Track debt evolution over time with dashboards and forecasts, aiding strategic planning.
  • Use Case: A team wants to identify critical security issues, prioritize refactoring efforts, and monitor progress over development cycles.

Quick Start

Run the scanner on your code repository to generate an inventory, then use the prioritizer to create a backlog, and finally analyze debt trends with the dashboard.

Frequently Asked Questions about tech-debt-tracker

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

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

You can track technical debt by running static analysis scans using AST parsing and regex patterns. The system generates a debt inventory, scores items by impact and effort, and monitors evolution over time through trend dashboards.

What is the best way to prioritize refactoring efforts for technical debt?▼

Prioritizing technical debt involves scoring and ranking items based on impact, effort, and strategic frameworks. This approach creates a structured backlog that helps teams address critical security issues and refactoring needs efficiently.

Can I use AST parsing to identify technical debt signals in Python projects?▼

AST parsing is supported for identifying technical debt signals in codebases. Combined with regex patterns and static analysis, it detects structural issues and code smells to inform technical decision-making and risk assessment.

How does technical debt trend analysis work for development cycles?▼

Technical debt trend analysis tracks debt evolution over time using dashboards and forecasts. It monitors progress across development cycles, aiding strategic planning and helping teams visualize continuous improvement metrics.

Do I need static analysis tools to assess technical debt impact and risk?▼

Static analysis is required to assess technical debt impact and risk. The system uses static analysis, pattern matching, and impact scoring algorithms to evaluate debt severity and inform technical decision-making without runtime execution.

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