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codebase-inspection

Analyze codebases with pygount for lines of code, language composition, and code-vs-comment ratios.

228k|44.7k|Updated Jul 22, 2025
Search Tags:#code analysis#LOC#pygount#codebase metrics#repository stats#language breakdown
One-click install
npx skills add https://github.com/NousResearch/hermes-agent --skill codebase-inspection-nousresearch
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/NousResearch/hermes-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/NousResearch/hermes-agent --skill codebase-inspection-nousresearch

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the analysis of codebases to provide key metrics like lines of code, language composition, and code-vs-comment ratios, saving developers time on manual code audits.

Core Features & Use Cases

  • Lines of Code (LOC) Counting: Accurately count lines of code across various programming languages.
  • Language Breakdown: Identify the proportion of different programming languages within a repository.
  • Code vs. Comment Ratio: Understand the balance between executable code and comments/documentation.
  • Use Case: Before integrating a new library or assessing project scope, use this Skill to get a quick, objective overview of its size and structure.

Quick Start

Use the codebase-inspection skill to get a summary of lines of code and language breakdown for the current directory.

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 get a language breakdown for a repository?▼

You can analyze codebase metrics by running this Skill to automatically inspect your repository and calculate lines of code, language composition, and code-vs-comment ratios using pygount.

What does code-vs-comment ratio analysis tell me about code quality?▼

Code-vs-comment ratio analysis reveals the balance between executable code and documentation within a repository, providing an objective overview of project structure and aiding in code quality evaluation.

Do I need to install pygount to analyze codebase metrics?▼

Yes, you need pygount installed, as this Skill requires it for deterministic code metric generation, including language breakdown and lines of code counting across various programming languages.

How can I assess project scope before integrating a new library?▼

Assess project scope before integrating a new library by inspecting the target codebase to retrieve key metrics like lines of code and language composition, giving you a quick, objective overview of its size and structure.

What is the best way to automate code audits for repository stats?▼

The best way to automate code audits for repository stats is using this Skill to automate codebase analysis, replacing manual code audits with pygount-driven metrics for lines of code and language composition.

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