techdebt

Name: techdebt
Availability: InStock
Author: franklee16

Detect duplicated logic, dead code, and code smells with file paths and line numbers.

203|27|Updated Apr 19, 2026

Search Tags:#code quality #linting #refactoring #technical debt #duplication #dead code #tests

Ready to run

npx skills add https://github.com/franklee16/academic-research-skills --skill techdebt-franklee16

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: techdebt
Source: https://github.com/franklee16/academic-research-skills/tree/main/project-management/techdebt
Command: npx skills add https://github.com/franklee16/academic-research-skills --skill techdebt-franklee16

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you reduce technical debt by locating duplicated code, dead code, outdated patterns, and common code smells so your codebase stays maintainable and easier to extend.

Core Features & Use Cases

Targeted Technical Debt Scanning: Identifies duplication, dead code, outdated patterns, and code smells across your repository with file paths and line numbers.
Actionable Fix Workflow: Prioritizes findings by severity, guides you through atomic refactors, and emphasizes verification steps after changes.
Developer-Focused Maintenance: Supports end-of-session cleanup by running linting and tests to ensure fixes do not introduce new issues.

Quick Start

Ask the assistant to scan your repository for technical debt, report issues by category with severity, then fix the high-severity items safely and verify with ruff and pytest.

Frequently Asked Questions about techdebt

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

FAQPage Schema

How do I find and fix technical debt in my codebase?▼

To find technical debt, scan your repository to identify duplicated logic, dead code, outdated patterns, and code smells. Generate a categorized report with file paths and line numbers, then prioritize and apply fixes safely while verifying changes with ruff and pytest.

What are common code smells and how do I locate them across my project?▼

Common code smells include duplicated logic and dead code. You can locate them across your project by scanning the codebase to produce a categorized issue report, which highlights affected file paths and line numbers for targeted refactoring.

Can I use ruff and pytest to validate refactoring during code cleanup?▼

Yes, you can use ruff and pytest to validate refactoring during code cleanup. After applying fixes for technical debt, run linting and tests to ensure the changes do not introduce new issues into the codebase.

What is the best way to prioritize refactoring tasks for long-lived projects?▼

The best way to prioritize refactoring tasks is evaluating identified technical debt by impact and ease. Generate a categorized report of code smells and duplicated logic, then address high-severity issues first to maintain project stability.

Does this approach detect outdated patterns and dead code during end-of-session maintenance?▼

Yes, this approach detects outdated patterns and dead code during end-of-session maintenance. It scans the codebase for technical debt, applies fixes safely, and runs ruff and pytest to verify code hygiene before completing the session.