Tech Debt Tracker

Analyze codebases for technical debt using AST parsing and regex patterns.

Updated Feb 16, 2026

Search Tags:#code quality #automation #code analysis #refactoring #technical debt #developer productivity

Ready to run

npx skills add https://github.com/Nuwanda04/Ballen-Fisk --skill tech-debt-tracker-nuwanda04

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Tech Debt Tracker
Source: https://github.com/Nuwanda04/Ballen-Fisk/tree/main/.cursor/skills/tech-debt-tracker
Command: npx skills add https://github.com/Nuwanda04/Ballen-Fisk --skill tech-debt-tracker-nuwanda04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires json, ast, re, os, sys, collections, datetime, pathlib, typing, dataclasses, statistics, argparse, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Technical debt slows down development, increases bugs, and makes maintenance costly. This skill helps identify, prioritize, and track technical debt to improve code quality and team velocity.

Core Features & Use Cases

Automated Debt Detection: Scans codebases to find issues like large functions, complexity, duplication, and security risks.
Intelligent Prioritization: Ranks debt items based on business impact and effort using frameworks like Cost of Delay.
Trend Analysis: Tracks debt over time to visualize progress and forecast future health.
Use Case: A development team can use this skill to automatically scan their codebase weekly, identify the top 5 most critical debt items, and plan their remediation in the next sprint planning session.

Quick Start

Scan the current directory for technical debt and display the findings.

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 technical debt in a codebase automatically?▼

To identify technical debt automatically, the Skill scans your codebase using Python AST parsing and regex pattern matching. It detects code complexity, large function sizes, duplication, security vulnerabilities, and documentation gaps to provide actionable remediation insights.

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

The best way to prioritize technical debt for refactoring is by ranking items based on business impact and remediation effort. The Skill applies frameworks like Cost of Delay to help teams identify critical debt items for their next sprint planning session.

Can I track technical debt trends over time using Python scripts?▼

Yes, you can track technical debt trends over time using the Skill's Python scripts. It records analysis metrics chronologically, allowing you to visualize remediation progress and forecast the future health of your codebase.

Does automated code analysis work for finding security vulnerabilities and duplication?▼

Automated code analysis works effectively for finding security vulnerabilities and code duplication. The Skill leverages AST parsing to evaluate structural complexity and regex matching to detect patterns associated with duplicated code and security risks.

How do I scan my current directory for technical debt?▼

To scan your current directory for technical debt, you run the Skill's Python scripts with standard library modules like os, pathlib, and argparse. It analyzes the directory structure and outputs a prioritized list of code quality issues.