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tech-debt

Audit codebases to catalog technical debt into a prioritized backlog.

11|Updated Apr 16, 2026
Search Tags:#code quality#technical debt#prioritization#backlog#scoring#analyze#risk
One-click install
npx skills add https://github.com/berkcangumusisik/claude-code-practices --skill tech-debt-berkcangumusisik
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt
Source: https://github.com/berkcangumusisik/claude-code-practices/tree/main/skills/tech-debt
Command: npx skills add https://github.com/berkcangumusisik/claude-code-practices --skill tech-debt-berkcangumusisik

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audits the codebase to identify technical debt and produces a prioritized backlog, helping teams focus on the most impactful improvements and reduce long-term maintenance costs.

Core Features & Use Cases

  • Automatic debt detection: flags TODOs, HACKs, long functions, large files, and outdated dependencies.
  • Scoring and backlog: assigns Impact, Effort, and Risk scores to each item and generates a prioritized backlog.
  • Real-world use: teams sprint on the top-ranked debt items to stabilize a codebase and speed future work.

Quick Start

Run the audit on the repository to generate a backlog report for the current project.

Frequently Asked Questions about tech-debt

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?▼

You can analyze technical debt by auditing the codebase for explicit markers like TODOs and HACKs, plus qualitative signals such as long functions and large files. This generates a prioritized backlog with structured tasks containing impact, effort, and risk scores.

What is the best way to create a prioritized backlog for code quality issues?▼

Generating a prioritized backlog for code quality involves scanning the repository to flag debt markers and outdated dependencies, then assigning impact, effort, and risk scores to produce actionable tasks sorted by priority.

Can I use an automated audit to detect technical debt for software projects of various sizes?▼

Yes, automated technical debt detection applies to software projects of various sizes. The audit scans the codebase to catalog explicit debt markers and qualitative quality signals, ensuring traceability and reporting across different project scales.

How do I score technical debt items by impact, effort, and risk?▼

Scoring technical debt items involves evaluating each flagged issue—such as outdated dependencies or large files—against impact, effort, and risk metrics. This generates a structured backlog report that helps teams focus on the most critical improvements.

What types of technical debt markers and quality signals should I look for during a codebase audit?▼

During a codebase audit, look for explicit debt markers like TODOs and HACKs, alongside qualitative quality signals including long functions, large files, and outdated dependencies to generate a comprehensive prioritized backlog.

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