codebase-inspection

Name: codebase-inspection
Availability: InStock
Author: hermesagents

Analyze Git repositories with pygount to report LOC, language breakdown, and code-vs-comment metrics.

Updated Aug 27, 2026

Search Tags:#code-analysis #loc #pygount #language-breakdown #repository-metrics #code-vs-comment

Ready to run

npx skills add https://github.com/Hermesagents/hermes-agents --skill codebase-inspection-hermesagents

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/Hermesagents/hermes-agents/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/Hermesagents/hermes-agents --skill codebase-inspection-hermesagents

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps developers quantify and understand a codebase by providing lines of code, language distribution, and code-vs-comment ratios.

Core Features & Use Cases

LOC counting and language breakdown using pygount
Code-vs-comment ratio insights across projects
Use Case: evaluate new repositories, compare multiple repos, or monitor codebase health over time

Quick Start

Point the skill at your repository path to receive a concise LOC, language distribution, and code-vs-comment report.

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 Git repository?▼

To count lines of code and get a language breakdown, point the skill at your Git repository path to receive a concise report using pygount for per-language counts and comment ratios.

Can I exclude specific folders when analyzing codebase metrics?▼

Yes, you can exclude specific folders when analyzing codebase metrics. The skill supports optional folder exclusions to tailor performance and avoid scanning irrelevant directories.

What is the best way to compare code-vs-comment ratios across multiple projects?▼

The best way to compare code-vs-comment ratios is running this analysis on checked-out projects. It quantifies comment ratios across projects to evaluate repository health and compare multiple repos.

Does pygount support language diversity analysis for monorepos?▼

Yes, pygount supports language diversity analysis for monorepos. The skill relies on pygount to compute per-language counts and assess size and language diversity within monorepos or checked-out projects.

When should I use a code analyzer for repository metrics?▼

You should use a code analyzer for repository metrics when you need to evaluate new repositories, compare multiple repos, or monitor codebase health and code quality over time.

What are the limitations of using pygount for LOC counting?▼

Pygount focuses on computing per-language LOC and comment ratios. It does not perform deep semantic code quality analysis, serving primarily to quantify size, language diversity, and code-vs-comment metrics.