codehealth

Analyze codebases to score file health from 1-10 using 32 indicators.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/dangrahn/agent-skills --skill codehealth
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: codehealth
Source: https://github.com/dangrahn/agent-skills/tree/main/skills/codehealth
Command: npx skills add https://github.com/dangrahn/agent-skills --skill codehealth

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Score source files on a 1-10 code health scale by detecting code health indicators (code smells). Use to assess before/after refactoring, gate quality, and prioritize improvements.

Core Features & Use Cases

  • Detects 32 indicators across module-level, function-level, implementation-level, design-level, and security categories to compute a 1-10 health score.
  • Produces actionable insights and concrete refactor targets for high-risk areas in large codebases.
  • Serves as a quality gate for measuring health improvements across a project or repository.

Quick Start

Score a target file to obtain its 1-10 health score and prioritized refactor targets.

Frequently Asked Questions about codehealth

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

FAQPage Schema
How do I quantify code health to identify refactoring targets?

Code health is quantified using a 1-10 scale based on 32 code smell indicators across module, function, implementation, design, and security. This analysis returns prioritized refactor targets and actionable guidance for high-risk areas.

What is the best way to measure code quality improvements after refactoring?

Measure code quality improvements by running a before/after workflow to calculate a health score delta. This compares per-file or per-module results to validate that refactoring efforts positively impacted the codebase.

Can I use static analysis to gate code quality before merging changes?

Yes, static analysis can serve as a quality gate by measuring health improvements across a project. You can enforce pre-refactor baselines and post-refactor score deltas to prevent regressions from merging into your repository.

Does technical debt analysis work across multiple programming languages?

Technical debt analysis works across languages by evaluating per-file or per-module results. The 32 indicators detect code smells at module, function, implementation, design, and security levels regardless of the specific programming language.

What code smells are detected when calculating a 1-10 code health score?

The code health score detects 32 code smells categorized into module-level, function-level, implementation-level, design-level, and security indicators to provide a comprehensive assessment of source file health.