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SethyPagna
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codebase-inspection

Count lines of code and classify repository composition by language using pygount.

Updated May 14, 2026
Search Tags:#codebase analysis#loc#pygount#language breakdown#repository metrics#code ratios
One-click install
npx skills add https://github.com/SethyPagna/Secretary-Jarvis --skill codebase-inspection-sethypagna
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/SethyPagna/Secretary-Jarvis/tree/main/src/capabilities/skills/github/codebase-inspection
Command: npx skills add https://github.com/SethyPagna/Secretary-Jarvis --skill codebase-inspection-sethypagna

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the guesswork from understanding a repository by turning raw source files into clear size, language, and comment-to-code metrics.

Core Features & Use Cases

  • Repository Summary: Measures lines of code, file counts, and language distribution across a project.
  • Composition Analysis: Helps compare code, comments, empty files, and binary content to understand what a codebase is made of.
  • Use Case: A developer can quickly assess a new repository before refactoring, estimating effort, or deciding which languages dominate the project.

Quick Start

Use the codebase-inspection skill to analyze the repository and report its language breakdown, file counts, and code-versus-comment ratios.

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 analyze language breakdown in a repository?▼

Repository metrics for sizing and language mix are generated by counting lines of code and classifying repository composition. This provides clear size, language, and comment-to-code ratio metrics across the project.

How do I measure code-versus-comment ratios in a codebase?▼

Code-versus-comment ratios are measured by comparing lines of code, comments, empty files, and binary content. This composition analysis reveals exactly what the codebase is made of for refactoring estimates.

Do I need pygount to analyze repository composition and file counts?▼

Yes, pygount is required to produce accurate summary and ratio metrics for the analysis. The Skill depends on it to count lines of code and classify repository composition across software projects.

What is excluded when calculating code ratios for language distribution?▼

Dependency and build folders are excluded when calculating code ratios for language distribution. This ensures the repository metrics reflect actual source files rather than generated or external content.

What's the best way to assess a new repository before estimating effort?▼

The best way to assess a new repository is generating a repository summary with lines of code, file counts, and language distribution. This removes guesswork by showing which languages dominate.

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