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codebase-inspection

Analyze codebases to quantify lines of code, language distribution, and code-vs-comment ratios.

2|Updated Mar 26, 2026
Search Tags:#codebase#metrics#code-quality#loc#language-analysis#pygount#repo-insight
One-click install
npx skills add https://github.com/CUexter/hermes-agent --skill codebase-inspection-cuexter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/CUexter/hermes-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/CUexter/hermes-agent --skill codebase-inspection-cuexter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams understand codebases at a glance by providing LOC counts, language distribution, and code-vs-comment ratios to prioritize refactoring and auditing tasks.

Core Features & Use Cases

  • LOC breakdown by language, file counts, and totals
  • Language mix visualization for project health
  • Quick assessment of code quality via code/comment ratios
  • Use Case: When you need a fast repo health check before a refactor or migration.

Quick Start

Analyze a repository at /path/to/repo to return LOC totals, language breakdown, and code-vs-comment ratios.

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 analyze language distribution in a repository?▼

You can analyze codebases to quantify lines of code, language distribution, and code-vs-comment ratios using pygount. This provides a fast repo health check to identify language trends and prioritize refactoring tasks.

What is a code-vs-comment ratio used for in codebase analysis?▼

A code-vs-comment ratio helps assess code quality and project health by showing how thoroughly a codebase is documented. It indicates whether documentation is keeping pace with development across single repositories or monorepos.

Can I use pygount to analyze a monorepo for LOC breakdown by language?▼

Yes, pygount analyzes monorepos to provide LOC breakdowns by language, file counts, and totals. It outputs structured results that can be consumed by dashboards or reports for evaluating repo size.

Do I need to install pygount before analyzing repo metrics?▼

Yes, pygount is required as a prerequisite to analyze codebases and generate metrics. Once installed, you can analyze a repository path to return LOC totals, language breakdown, and code-vs-comment ratios.

What is the best way to get structured code metrics for a dashboard before a migration?▼

Analyzing your codebase with pygount outputs structured results containing LOC totals and language distribution that can be consumed by dashboards. This offers a quick assessment of repo health before a refactor or migration.

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