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Chang-Shih-Yung
Chang-Shih-YungCOMMUNITY
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health

Aggregate type checker, linter, and test results into a 0-10 composite score.

Updated Apr 1, 2026
Search Tags:#code quality#testing#static analysis#linting#dashboard#type checking#health check
One-click install
npx skills add https://github.com/Chang-Shih-Yung/nexus-finance --skill health-chang-shih-yung
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: health
Source: https://github.com/Chang-Shih-Yung/nexus-finance/tree/main/.claude/skills/gstack/health
Command: npx skills add https://github.com/Chang-Shih-Yung/nexus-finance --skill health-chang-shih-yung

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the need to manually run type checkers, linters, test runners, and dead code detectors separately, then manually aggregate the results into a meaningful quality score. It provides a single command to get a 0-10 composite health score and track whether code quality is improving or slipping over time.

Core Features & Use Cases

  • Composite Quality Scoring: Aggregates results from type checkers, linters, test runners, dead code detectors, and shell linters into a weighted 0-10 score.
  • Trend Tracking: Monitors health scores over time to show if the codebase is improving or degrading.
  • Use Case: Imagine you're about to ship a feature and want to know if your code quality has dropped. Run this skill to get an instant dashboard showing exactly which tools failed and how the score compares to last week.

Quick Start

Use the health skill to run all available code quality checks and display the composite dashboard for the current project.

Frequently Asked Questions about health

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

FAQPage Schema
How do I get a single code quality score from multiple linters and test runners?▼

A composite code quality score aggregates results from type checkers, linters, test runners, and dead code detectors into a weighted 0-10 metric, providing an instant dashboard showing exactly which tools failed.

What is the best way to track codebase health trends over time?▼

Tracking codebase health trends requires monitoring a composite quality score over time to show if the codebase is improving or degrading, which helps validate code quality before shipping a new feature.

How does automated static analysis detect which quality tools to run?▼

Automated static analysis detects which quality tools to run by reading project-local configuration files such as tsconfig.json, biome.json, package.json, and pyproject.toml to invoke appropriate checkers without manual specification.

Do I need to manually configure each linter and type checker for a health check?▼

No, you do not need to manually configure each linter for a health check. The process automatically detects and invokes appropriate quality tools by reading existing project-local configuration files.

Can I use a code quality dashboard for pre-ship validation?▼

Yes, you can use a code quality dashboard for pre-ship validation. It automates code quality assessment by aggregating results from type checkers and linters, showing if your code quality has dropped before shipping.

Why run dead code detectors and shell linters together with type checking?▼

Running dead code detectors and shell linters together with type checking ensures comprehensive continuous quality monitoring. Aggregating these results into a composite score provides a complete view of software development workflow health.

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