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benreceveur
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tech-debt-tracker

Scan codebases for technical debt indicators and generate prioritized backlog items.

Updated Aug 23, 2026
Search Tags:#code quality#automation#development#refactoring#metrics#technical debt#prioritization
One-click install
npx skills add https://github.com/benreceveur/claude-workflow-engine --skill tech-debt-tracker
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-tracker
Source: https://github.com/benreceveur/claude-workflow-engine/tree/main/skills/tech-debt-tracker
Command: npx skills add https://github.com/benreceveur/claude-workflow-engine --skill tech-debt-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, git, and includes scripts (resource) and examples (resource) components.

What problem does it solve?

This Skill systematically identifies, quantifies, and prioritizes technical debt within a codebase, transforming abstract "code smells" into actionable, business-impact-driven tasks. It helps teams focus refactoring efforts on the highest-value areas, leading to faster delivery and improved code health.

Core Features & Use Cases

  • Automated Debt Scanning: Analyzes code for complexity, duplication, outdated patterns, and missing tests, providing a comprehensive view of technical debt.
  • Quantitative Metrics: Calculates objective metrics like SQALE index (remediation time), cyclomatic complexity, and code churn to measure debt objectively.
  • Impact-Based Prioritization: Prioritizes debt items by business impact and estimated effort, creating a clear, actionable roadmap for debt paydown.
  • Use Case: Get a prioritized list of technical debt items in your project, ranked by their impact on critical modules and estimated effort to fix, allowing your team to focus on the most valuable refactoring work in the next sprint.

Quick Start

Scan the project directory for technical debt indicators and generate a summary report.

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 in my codebase?▼

Technical debt tracking automatically scans your code for complexity, duplication, outdated patterns, and missing tests, then ranks issues by business impact and effort. This produces a prioritized backlog so teams focus refactoring on the highest-value areas first.

What metrics does automated debt scanning measure?▼

Automated scanning calculates cyclomatic complexity, code churn, test coverage gaps, and SQALE index (remediation time) to quantify debt objectively. These metrics reveal which modules contribute most to overall code health issues.

Can I use technical debt tracking across multiple programming languages?▼

Yes, debt tracking applies across languages and project scopes. It configures thresholds per language and project type, generating consistent metrics and actionable insights regardless of your tech stack.

How do I integrate debt insights into sprint planning?▼

The Skill exports prioritized debt items as backlog entries with estimated effort and business impact ratings. These integrate directly into sprint planning tools, enabling data-driven refactoring scheduling.

What are the prerequisites for running technical debt analysis?▼

You need Python 3 and Git installed. The Skill scans local repositories and requires access to your project's git history to calculate churn and trend metrics.

When should I run debt tracking—before or after code changes?▼

Run debt scanning regularly throughout development to track trends and catch emerging issues early. Baseline scans before major refactoring efforts establish metrics for measuring improvement.

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