tech-debt-analyzer

Name: tech-debt-analyzer
Availability: InStock
Author: Nirbhay

Analyze JavaScript/TypeScript codebases for technical debt indicators.

19|5|Updated Nov 23, 2025

Search Tags:#code quality #refactoring #maintainability #dependency analysis #technical debt #code smells

Ready to run

npx skills add https://github.com/Nir-Bhay/markups --skill tech-debt-analyzer-nir-bhay

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tech-debt-analyzer
Source: https://github.com/Nir-Bhay/markups/tree/main/.agents/skills/tech-debt-analyzer
Command: npx skills add https://github.com/Nir-Bhay/markups --skill tech-debt-analyzer-nir-bhay

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill systematically identifies, analyzes, and documents technical debt in JavaScript/TypeScript codebases, helping to improve code quality and maintainability.

Core Features & Use Cases

Automated Analysis: Detects code smells, complex functions, and dependency issues.
Debt Categorization: Organizes findings into clear categories like Code Quality, Architecture, and Security.
Documentation: Provides templates for technical debt registers and Architecture Decision Records (ADRs).
Use Case: A development team can use this Skill to regularly scan their codebase, identify areas with high technical debt, and create a prioritized backlog of refactoring tasks.

Quick Start

Run the tech-debt-analyzer skill to analyze the 'src' directory and output a markdown report.

Frequently Asked Questions about tech-debt-analyzer

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

FAQPage Schema

How do I detect technical debt and code smells in a JavaScript codebase?▼

You can detect technical debt by running automated analysis scripts that scan JavaScript and TypeScript codebases to identify code smells, complex functions, and dependency issues, then categorize the findings into clear quality, architecture, and security buckets.

What is the best way to document and categorize technical debt for refactoring?▼

The best way to document technical debt is to use provided templates for technical debt registers and Architecture Decision Records, which organize detected code smells and dependency issues into categorized, prioritized refactoring backlogs.

Does the technical debt analyzer require any specific runtime environment?▼

Yes, the technical debt analyzer requires Python 3 with standard libraries for script execution to run the automated detection scripts that analyze JavaScript and TypeScript codebases for maintainability issues.

Can I analyze TypeScript codebases for maintainability and dependency issues?▼

Yes, you can analyze TypeScript codebases for maintainability and dependency issues. The analyzer systematically scans both JavaScript and TypeScript code to detect complex functions and dependency problems affecting code quality.

How do I generate a technical debt report from my source code?▼

To generate a technical debt report, run the analyzer against your source directory to output a markdown report. It uses automated detection scripts to find code smells and categorize them into a structured format for your refactoring backlog.