codebase-inspection

Name: codebase-inspection
Availability: InStock
Author: zhouboyu-xreal

Analyze codebases for lines of code, language breakdown, and code-to-comment ratios.

Updated Jun 9, 2026

Search Tags:#code analysis #repository analysis #codebase metrics #language breakdown #lines of code

Ready to run

npx skills add https://github.com/zhouboyu-xreal/Hermes-Memory --skill codebase-inspection-zhouboyu-xreal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/zhouboyu-xreal/Hermes-Memory/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/zhouboyu-xreal/Hermes-Memory --skill codebase-inspection-zhouboyu-xreal

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides insights into codebases, including lines of code, language breakdown, and code-to-comment ratios, enabling users to understand the size and composition of their repositories.

Core Features & Use Cases

LOC and Language Metrics: Offers a summary of lines of code, file counts, and language breakdown.
Codebase Composition: Provides an overview of the codebase's structure and content.
Use Case: When you need to quickly assess the size and complexity of a codebase for planning or optimization.

Quick Start

To get a summary of the codebase at '/path/to/repo', run the command: 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 analyze lines of code and language breakdown in a repository?▼

You can analyze lines of code and language breakdown in a repository by running the codebase-inspection command with your target repository path. It generates metrics including file counts, language distribution, and code-to-comment ratios.

What is the best way to assess codebase size and complexity for project planning?▼

The best way to assess codebase size and complexity for project planning is to extract codebase metrics like total lines of code and language breakdown. This provides a structural overview to understand repository composition.

Do I need pygount to calculate code-to-comment ratios for my codebase?▼

Yes, you need the pygount tool installed to calculate code-to-comment ratios. The codebase analysis relies on pygount as its core dependency to execute and generate the codebase metrics.

Can I get a quick summary of codebase composition for a specific directory path?▼

Yes, you can get a quick summary of codebase composition by executing the command with your specific directory path. It outputs an overview of the repository's structure, content, and language metrics.

What codebase metrics are available for code quality analysis?▼

The codebase metrics available for code quality analysis include lines of code, file counts, language breakdown, and code-to-comment ratios. These metrics help evaluate repository size and composition for optimization.