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1thirteeng3
1thirteeng3COMMUNITY
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codebase-inspection

Analyze codebases to compute lines of code, language breakdown, and code-vs-comment ratios.

Updated Mar 24, 2026
Search Tags:#codebase#code-quality#loc#language-analysis#pygount#repository-metrics
One-click install
npx skills add https://github.com/1thirteeng3/greenmoire --skill codebase-inspection-1thirteeng3
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/1thirteeng3/greenmoire/tree/main/integrations/hermes-agent/skills/github/codebase-inspection
Command: npx skills add https://github.com/1thirteeng3/greenmoire --skill codebase-inspection-1thirteeng3

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This tool analyzes codebases to compute lines of code, language distribution, and code-vs-comment ratios, enabling quick assessments of repo size and composition.

Core Features & Use Cases

  • LOC counting and language breakdown using pygount
  • Code-vs-comment ratio analysis
  • Use cases: quickly determine repo size and language mix for audits or refactoring

Quick Start

Install pygount and run it against your repository to generate a language breakdown and LOC summary.

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 my repository?▼

Yes, you can analyze code-vs-comment ratios to assess code quality. The tool calculates code-vs-comment ratios alongside lines of code to provide code-quality insights across diverse projects and languages.

Do I need to install any dependencies to analyze codebase metrics?▼

Yes, you can exclude specific folders from the repository metrics. The tool supports folder exclusions so you can generate a concise codebase summary while ignoring irrelevant directories.

What is the best way to assess repo size and language composition for an audit?▼

Codebase metrics identify lines of code, language breakdown, and code-vs-comment ratios to evaluate repository size. These metrics enable quick assessments of repo composition and code quality across diverse projects.

Does this code-quality analysis tool work with diverse programming languages?▼

Yes, the code-quality analysis works with diverse projects and languages. It uses pygount to compute a language-by-language summary, supporting varied language mixes within a single repository.

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