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john-data-chen
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codebase-inspection

Analyze codebases for LOC, language distribution, and code-vs-comment ratios.

2|Updated Apr 25, 2026
Search Tags:#codebase#repository#language#code-analysis#loc#pygount
One-click install
npx skills add https://github.com/john-data-chen/hermes-agent-backup --skill codebase-inspection-john-data-chen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/john-data-chen/hermes-agent-backup/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/john-data-chen/hermes-agent-backup --skill codebase-inspection-john-data-chen

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze codebases to quantify lines of code, language distribution, and the balance between code and comments to inform audits and refactors.

Core Features & Use Cases

  • LOC and language breakdowns per repository
  • Code-vs-comment ratio calculations
  • Use Case: assess project size and language makeup for onboarding or refactoring decisions

Quick Start

Run pygount on your target repository to generate a language and LOC summary.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I analyze lines of code and language distribution in a local repository?▼

To analyze lines of code in a local repository, run a code analysis tool to generate a structured summary of language distribution, file counts, and code volume. This provides a clear breakdown of the project's language makeup.

What is a code-vs-comment ratio and when do I need it for a codebase?▼

A code-vs-comment ratio measures the proportion of comments relative to executable lines in a codebase. You need this metric during code reviews or audits to assess documentation quality and inform refactoring decisions.

Does pygount work for analyzing codebases hosted on GitHub?▼

Yes, pygount works for analyzing codebases hosted on GitHub or stored locally. It analyzes the repository files to output language breakdowns, LOC counts, and code-vs-comment ratios applicable to any codebase directory.

Can I use code analysis to assess project size for onboarding?▼

Yes, you can use code analysis to assess project size and language makeup for onboarding. Analyzing lines of code and language distribution helps new developers understand the scale and structure of the codebase quickly.

Do I need to install dependencies before analyzing a codebase?▼

Yes, you need to install pygount as a prerequisite before analyzing a codebase. Once installed, you can run it on your target repository to generate the language and lines of code summary output.

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