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codebase-inspection

Analyze codebase size, language composition, and code-comment ratios.

2|1|Updated May 10, 2026
Search Tags:#code analysis#codebase#metrics#repository#statistics#pygount
One-click install
npx skills add https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture --skill codebase-inspection-zli5460
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/zli5460/hermes-agent-X-Phoenix-Architecture --skill codebase-inspection-zli5460

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

It enables quick and detailed analysis of code repositories, providing metrics such as LOC, language composition, and code-comment ratios.

Core Features & Use Cases

  • Code Metrics Analysis: Generate detailed statistics on code size, language distribution, and file counts.
  • Repository Size Assessment: Quickly assess the size and complexity of a project to inform maintenance or refactoring plans.
  • Use Case: Developers want to determine how many Python, JavaScript, and other files are in their project and review the code/comment ratio to guide documentation efforts.

Quick Start

Use the codebase-inspection skill to analyze a local repository by running pygount with proper folder exclusions.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I analyze codebase size and language composition for a local repository?▼

You can analyze codebase size and language composition by running pygount against your local repository folder. This generates detailed statistics including lines of code, file counts, and language distribution across multiple programming languages.

What metrics does pygount provide for evaluating repository complexity?▼

Pygount provides code metrics including lines of code, language composition, file counts, and code-comment ratios. These metrics help evaluate repository complexity to guide maintenance and refactoring decisions across multiple programming languages.

Can I exclude dependency directories when generating code statistics for my project?▼

Yes, when generating code statistics with pygount, you can apply proper folder exclusions to ignore dependency directories. This ensures accurate metrics analysis by preventing third-party libraries from inflating your actual codebase size.

What is the best way to assess code-comment ratio across different programming languages?▼

The best way to assess code-comment ratio across multiple programming languages is to run a codebase analysis tool like pygount. It automatically detects languages and calculates the ratio to guide your documentation efforts.

Does codebase analysis with pygount work across different folder structures and multi-language projects?▼

Yes, codebase analysis with pygount operates across multiple programming languages and folder structures. It evaluates codebase size and composition regardless of the project's internal directory layout or language mix.

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