Can it help prevent future technical debt?

Yes, it includes a prevention strategy section that suggests quality gates, CI/CD pipeline checks, and debt budget tracking for the team.

When is the best time to run this skill?

It is most effective when development velocity drops, during legacy code evaluations, or when planning a major structural refactor.

How does this skill calculate technical debt ROI?

The skill evaluates development velocity impact in hours per month against estimated remediation effort to provide a percentage-based ROI and estimated payback period.

What debt categories are covered by the analysis?

It analyzes five main categories: Code Debt, Architecture Debt, Testing Debt, Documentation Debt, and Infrastructure Debt.

Which code metrics does the analyzer track?

It provides a dashboard covering cyclomatic complexity, code duplication percentages, and unit test coverage compared against target benchmarks.

Technical Debt Analyzer

Name: Technical Debt Analyzer
Author: Uniswap

byUniswap

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分析与监控

Identifies, quantifies, and prioritizes technical debt within codebases using ROI-based remediation plans.

关于

The Technical Debt Analyzer is a specialized Claude Code skill designed to evaluate the long-term health of software projects by identifying architectural flaws, code duplication, and testing gaps. It calculates the real-world impact of debt on development velocity and provides a prioritized roadmap for cleanup, complete with ROI estimates and effort levels. This tool is essential for engineering leads and developers managing legacy systems who need data-driven insights to justify refactoring tasks and improve code maintainability.

主要功能

Automated debt metrics dashboards featuring cyclomatic complexity and duplication data
13 GitHub stars
Comprehensive debt categorization across code, architecture, and testing layers
Impact assessment modeling for development velocity and maintenance risk
Prioritized remediation roadmaps with effort estimates and ROI calculations
Prevention strategy recommendations including quality gates and debt budgeting

使用场景

Assessing the maintenance burden and quality of a legacy codebase before a major migration
Identifying specific code modules that are slowing down sprint velocity and team productivity
Creating a data-driven business case for refactoring by calculating payback periods

关于

主要功能

Automated debt metrics dashboards featuring cyclomatic complexity and duplication data
13 GitHub stars
Comprehensive debt categorization across code, architecture, and testing layers
Impact assessment modeling for development velocity and maintenance risk
Prioritized remediation roadmaps with effort estimates and ROI calculations
Prevention strategy recommendations including quality gates and debt budgeting

使用场景

Assessing the maintenance burden and quality of a legacy codebase before a major migration
Identifying specific code modules that are slowing down sprint velocity and team productivity
Creating a data-driven business case for refactoring by calculating payback periods