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codebase-inspection

Analyze codebases with pygount for LOC counts, language breakdowns, and code-to-comment ratios.

Updated Jun 4, 2026
Search Tags:#codebase#analysis#LOC#language breakdown#code-to-comment ratio
One-click install
npx skills add https://github.com/kngender5/hermes --skill codebase-inspection-kngender5
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/kngender5/hermes/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/kngender5/hermes --skill codebase-inspection-kngender5

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill simplifies the process of inspecting codebases by providing metrics like lines of code, language breakdown, and code-to-comment ratios.

Core Features & Use Cases

  • LOC (Lines of Code) Count: Obtain an overview of the repository's size in lines of code.
  • Language Breakdown: Understand the distribution of programming languages within the repository.
  • Code-to-Comment Ratios: Gain insights into the density of code versus documentation within the repository.
  • Use Case: When you need to quickly understand the size and composition of a codebase.

Quick Start

Run 'codebase-inspection' on your codebase to get a detailed analysis of its codebase structure.

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 language breakdown and LOC count for a codebase?▼

To get a language breakdown and LOC count for a codebase, you can analyze repositories to extract lines of code metrics and distribution across programming languages. This provides a detailed overview of repository size and composition.

What is the best way to calculate code-to-comment ratios in a repository?▼

Calculating code-to-comment ratios in a repository involves analyzing source files to measure documentation density against executable lines. This extracts insights into the balance between code and comments for quality assessments.

Does codebase analysis require pygount to extract code metrics?▼

Yes, codebase analysis requires pygount to extract code metrics like LOC counts and language distributions. The library performs the underlying source code parsing needed to evaluate repository composition accurately.

Can I use this for a repository audit to understand codebase composition?▼

Yes, you can use this for a repository audit to understand codebase composition. It evaluates repository structure by providing detailed metrics on language breakdowns and lines of code for comprehensive codebase analysis.

What metrics are included in a codebase inspection?▼

A codebase inspection includes lines of code (LOC) counts, language breakdowns showing the distribution of programming languages, and code-to-comment ratios. These metrics simplify inspecting codebases for size and composition.

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