codebase-inspection

Analyze software repositories with pygount to calculate lines of code and language distribution.

9|Updated Jul 1, 2026
One-click install
npx skills add https://github.com/Cyapstaye/Adame_ver.open --skill codebase-inspection-cyapstaye
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/Cyapstaye/Adame_ver.open/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/Cyapstaye/Adame_ver.open --skill codebase-inspection-cyapstaye

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount.

What problem does it solve?

This skill solves the difficulty of manually auditing large repositories to understand their size, language distribution, and code-to-comment ratios.

Core Features & Use Cases

  • Language Breakdown: Automatically identifies and counts files by programming language.
  • Metric Reporting: Calculates lines of code (LOC) and comment density to assess project complexity.
  • Use Case: Use this when you need to quickly audit a new repository to determine its primary technologies and overall scale before starting a code review or refactoring task.

Quick Start

Run the codebase inspection skill on the current directory to generate a summary report of all language statistics and line counts.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I calculate lines of code and language distribution for a local repository?

You can calculate lines of code and language distribution by running a codebase analysis tool that traverses the file system to count lines of code, identify programming languages, and measure documentation ratios automatically.

What is the best way to audit a new codebase before starting a refactoring task?

The best way to audit a new codebase for refactoring is to generate a summary report of language statistics and line counts, allowing you to determine primary technologies and overall scale quickly.

Does codebase analysis with pygount filter out dependency directories and build artifacts?

Yes, codebase analysis with pygount supports large-scale auditing by filtering out dependency directories and build artifacts, ensuring the reported metrics accurately reflect your actual source code.

Can I measure code-to-comment ratios and documentation density across a software project?

Yes, you can measure code-to-comment ratios and documentation density across a software project by calculating comment density metrics to assess overall project complexity and documentation coverage.

Do I need to install pygount locally to perform repository metrics analysis?

Yes, you need to install the pygount package in your local environment to perform file-system traversal and analysis, as the repository metrics calculation relies entirely on this utility.