Aggregate type safety, lint, tests, and dead-code signals into a 0-10 code health score.
npx skills add https://github.com/singhianand23045/GarryTan --skill health-singhianand23045
Please help me install this Agent Skill. Skill: health Source: https://github.com/singhianand23045/GarryTan/tree/main/health Command: npx skills add https://github.com/singhianand23045/GarryTan --skill health-singhianand23045
Code quality is not a single metric. This Skill collects type safety, lint cleanliness, test coverage, and dead-code signals, and surfaces a weighted 0-10 health score with trends over time.
Run the health skill to generate a live code-quality dashboard for your repository.
High-intent search queries and answers about installing and using this skill.
Code health is quantified by combining type safety, lint cleanliness, test coverage, and dead-code signals into a weighted 0-10 score. You need to run a type checker, linter, test runner, and dead-code detector to generate the metric.
Code health monitoring tracks quality trends over time by aggregating type checks, lint results, tests, and dead-code detection. Trend analysis surfaces trajectories to spot regressions and rate improvements across per-repo and per-branch views.
Yes, you can track code quality across multiple repositories and branches. The Skill provides per-repo and per-branch views to monitor health over time and flag drift in ongoing software projects of any size.
The best way to combine these signals is using a weighted 0-10 health score that aggregates type safety, lint cleanliness, test coverage, and dead-code detection. This creates a single, trackable metric with trend analysis.
Yes, you need to run a type checker, linter, test runner, and dead-code detector before calculating code health. The Skill aggregates the outputs from these four tools to compute the final weighted 0-10 score.
Your code health score may drop when test coverage increases if other weighted signals decline. The score combines type safety, lint cleanliness, tests, and dead-code detection, so regressions in type checking or increased dead-code can offset coverage gains.
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