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ashiqcodeleaf
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codebase-inspection

Inspect codebases to calculate lines of code, language composition, file counts, and code-comment ratios.

Updated Jun 22, 2026
Search Tags:#code analysis#repository analysis#pygount#codebase metrics#lines of code
One-click install
npx skills add https://github.com/ashiqcodeleaf/long-Run-Agents --skill codebase-inspection-ashiqcodeleaf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/ashiqcodeleaf/long-Run-Agents/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/ashiqcodeleaf/long-Run-Agents --skill codebase-inspection-ashiqcodeleaf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount, and includes scripts (resource) components.

What problem does it solve?

Quickly get insights into your codebase's lines of code, language composition, and other key metrics, helping you understand its size and complexity at a glance.

Core Features & Use Cases

  • LOC Count: Know how many lines of code your project contains.
  • Language Breakdown: See which programming languages are being used in your codebase.
  • File Counts: Get an overview of the number of files and their distribution.
  • Code-Comment Ratio: Understand the ratio between code and comment lines.
  • Use Case: If you're working on a large project and want to know its size in terms of lines of code or the most prevalent language, this skill provides a fast and simple way to do so.

Quick Start

Inspect the codebase located at /path/to/repo with codebase-inspection.

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 composition for my project?▼

Codebase metrics analysis provides insights into lines of code, language composition, and code-comment ratios. It uses source analysis libraries to scan your repository, helping you understand project size and complexity at a glance.

How do I count lines of code in a large codebase automatically?▼

To count lines of code in a large codebase, execute an analysis script targeting your repository directory. The tool scans all project files, calculating total LOC, file counts, and the distribution of code versus comments.

Does pygount work for analyzing codebases of any size and type?▼

Yes, pygount can handle various project types and sizes for codebase assessments. It scans your repository to provide metrics like lines of code and language composition, making it suitable for both small and large software engineering workflows.

What is the best way to get a code-comment ratio for a repository?▼

The best way to get a code-comment ratio is to run a repository analysis tool that parses source files automatically. This approach evaluates your codebase to calculate the exact ratio between executable code lines and comment lines.

Can I see a language breakdown of my codebase files?▼

Yes, you can see a language breakdown of your codebase files by inspecting the repository. The analysis identifies all programming languages used in your project and reports their composition alongside file counts and LOC metrics.

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