codebase-inspection

Name: codebase-inspection
Availability: InStock
Author: Quill-Agent

Analyze GitHub repositories for language composition, LOC counts, and code-to-comment ratios.

3|1|Updated May 19, 2026

Search Tags:#code analysis #GitHub #LOC #pygount #codebase metrics

Ready to run

npx skills add https://github.com/Quill-Agent/Quill-Agent --skill codebase-inspection-quill-agent

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/Quill-Agent/Quill-Agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/Quill-Agent/Quill-Agent --skill codebase-inspection-quill-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Quickly understand the size and composition of your codebase, including language ratios, LOC, and code vs. comment ratios.

Core Features & Use Cases

LOC Analysis: Provides a total count of lines of code (LOC).
Language Breakdown: Details the languages used and the file count for each language.
Codebase Composition: Inspects and provides ratios between code and comment lines.

Quick Start

Inspect your repository using codebase-inspection and specify the repository path: codebase-inspection /path/to/repo.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema

How do I get a breakdown of lines of code by language in a GitHub repository?▼

Static codebase analysis provides a lines of code breakdown by language for GitHub repositories, counting total LOC, detailing language composition, and listing file counts for each language used.

How do I calculate the code-to-comment ratio for my Python project?▼

You calculate the code-to-comment ratio for a Python project by applying static code analysis with pygount, which inspects the codebase to provide the exact ratio between code lines and comment lines.

Do I need to install pygount before analyzing codebase metrics?▼

Yes, you need to install pygount before analyzing codebase metrics. The static code analysis requires pygount to be installed in your environment to successfully gather LOC counts and language composition data.

What is the best way to quickly inspect codebase size and composition?▼

The best way to quickly inspect codebase size and composition is to run a static code analysis tool that instantly provides total LOC, language ratios, and code-to-comment ratios for your target repository.

Can I analyze codebase metrics for a local clone of a GitHub repository?▼

Yes, you can analyze codebase metrics for a local clone by specifying the local repository path during static code analysis, which allows the tool to scan the directory and calculate LOC and language composition metrics.