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tech-debt-analyzer

Detects code smells, dependency issues, and technical debt in JavaScript and TypeScript codebases.

2|1|Updated Jun 12, 2025
Search Tags:#code quality#typescript#static analysis#refactoring#dependency analysis#technical debt#code smells
One-click install
npx skills add https://github.com/agent-trust-protocol/atp-core --skill tech-debt-analyzer-agent-trust-protocol
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tech-debt-analyzer
Source: https://github.com/agent-trust-protocol/atp-core/tree/main/.claude/skills/tech-debt-analyzer
Command: npx skills add https://github.com/agent-trust-protocol/atp-core --skill tech-debt-analyzer-agent-trust-protocol

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve? Technical debt accumulates silently in codebases, slowing development and increasing risk. This Skill automates the detection of code smells, dependency problems, and quality issues, then helps you document, categorize, and prioritize them in a structured debt register. ## Core Features & Use Cases - Automated Code Smell Detection: Scans JavaScript/TypeScript source files for large files, complex functions, TODO/FIXME markers, console statements, weak typing, long parameter lists, deep nesting, and magic numbers. - Dependency Health Analysis: Examines package.json for deprecated packages, duplicate functionality, and unsafe version constraints. - Debt Documentation Templates: Provides a technical debt register template and ADR template to standardize how findings are recorded and tracked. - Use Case: Before sprint planning, run the analysis scripts on your codebase, review the generated markdown report, and populate a debt register so the team can prioritize the top five items for the next sprint. ## Quick Start Analyze the src directory of my project for technical debt and create a prioritized debt register from the findings.

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 code smells in a TypeScript codebase?▼

Run the detect_code_smells.py script against your source directory to scan for large files, complex functions, deep nesting, magic numbers, and weak typing. It outputs a markdown or JSON report grouped by severity for easy triage.

How to find deprecated npm packages in package.json?▼

Run analyze_dependencies.py with your package.json path. It flags known deprecated packages like request, tslint, and node-sass, detects duplicate functionality such as multiple HTTP clients, and warns about unsafe version constraints.

What is a technical debt register and how do I create one?▼

A technical debt register is a living document tracking known debt items with severity, impact, effort estimates, and resolution status. Copy the DEBT_REGISTER_TEMPLATE.md from the assets folder and add each finding as a structured entry.

Does the code smell detector work on test files?▼

No, the detector automatically skips test files, build artifacts, and node_modules. It only analyzes .ts, .tsx, .js, and .jsx source files, excluding paths containing .test., .spec., __tests__, dist, or build.

What are the limitations of automated technical debt detection?▼

Automated scripts catch measurable issues like complexity and file size but miss architectural problems, missing abstractions, and business-logic flaws. Combine script output with manual code review of critical areas for comprehensive coverage.

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