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unclehowell
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codebase-inspection

Analyze code repositories with pygount for LOC, language breakdown, and code-vs-comment ratios.

Updated Sep 1, 2021
Search Tags:#codebase#repository-analysis#loc#pygount#language-breakdown#code-comment-ratio
One-click install
npx skills add https://github.com/unclehowell/unclehowell --skill codebase-inspection-unclehowell
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/unclehowell/unclehowell/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/unclehowell/unclehowell --skill codebase-inspection-unclehowell

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quickly determine codebase size and health by counting lines of code, language distribution, and code-vs-comment ratios across a repository.

Core Features & Use Cases

  • LOC & Language Breakdown: Generates per-language file counts, code lines, and comments to assess tech stack and contributions.
  • Codebase Health Metrics: Enables quick assessment of repository complexity and documentation coverage.
  • Use Case: When evaluating a new project, run this skill to understand language balance and growth potential, or audit an existing repo for maintenance needs.

Quick Start

Point the skill at a repository path to generate a LOC report, language breakdown, and code-vs-comment metrics.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I count lines of code and get a language breakdown for a repository?▼

To count lines of code and get a language breakdown, you can analyze the repository using pygount. This generates per-language file counts, code lines, and comments to assess tech stack distribution and overall codebase health.

What is the best way to check code-vs-comment ratios during a project evaluation?▼

Checking code-vs-comment ratios during a project evaluation involves analyzing the repository to measure documentation coverage. This process outputs per-language metrics, helping you quickly assess repository complexity and maintenance needs.

Can I exclude specific folders when running a codebase health check?▼

Yes, you can exclude specific folders when running a codebase health check. The analysis supports configurable folder exclusions to ensure accurate metrics by ignoring irrelevant directories during your repository audit.

Does pygount support language breakdown analysis for JavaScript and Python repositories?▼

Yes, pygount supports language breakdown analysis for JavaScript and Python repositories. It applies to repository audits across diverse tech stacks, producing accurate LOC counts and code-vs-comment ratios for multiple programming languages.

How do I audit an existing repo for maintenance planning and documentation coverage?▼

To audit an existing repo for maintenance planning, you generate a report of LOC counts, language distribution, and code-vs-comment ratios. This reveals repository complexity and documentation gaps suitable for embedding in dashboards.

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