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tangzheng202202
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codebase-inspection

Analyze codebases with pygount to produce LOC counts, language breakdowns, and code-vs-comment ratios.

1|Updated Apr 13, 2026
Search Tags:#codebase#analysis#loc#pygount#language-breakdown#repository-metrics
One-click install
npx skills add https://github.com/tangzheng202202/hermes-skills --skill codebase-inspection-tangzheng202202
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/tangzheng202202/hermes-skills/tree/main/01-coding-dev/github/codebase-inspection
Command: npx skills add https://github.com/tangzheng202202/hermes-skills --skill codebase-inspection-tangzheng202202

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes codebases to deliver reliable metrics such as lines of code (LOC), language distribution, and code-vs-comment ratios, enabling quick assessments of repository size and code health.

Core Features & Use Cases

  • LOC & Language Breakdown: Generate a precise breakdown of languages and file counts, plus total code and comment lines.
  • Code-Base Health Metrics: Compute code-vs-comment ratios to help gauge maintainability.
  • Use Case: When asked to size up a repository, quickly produce a summary of languages, LOC, and comments to guide audits or refactors.

Quick Start

Run a targeted analysis on a repository using pygount to obtain LOC, language distribution, and code-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 get a language breakdown for my repository?▼

To count lines of code and get a language breakdown for your repository, you can analyze the codebase to produce precise LOC counts, language distributions, and file counts using pygount.

What is a code-vs-comment ratio and how does it indicate codebase health?▼

A code-vs-comment ratio measures the proportion of comment lines to executable code lines. Computing this ratio helps gauge repository maintainability and baseline code-quality by revealing documentation coverage.

Do I need pygount to analyze repository metrics and language distribution?▼

Yes, you need pygount installed to analyze repository metrics and language distribution. It is a required dependency for generating precise LOC counts and code-vs-comment ratios from your codebase.

Can I use codebase analysis for sizing up a repository before a refactor?▼

Yes, you can use codebase analysis for sizing up a repository before a refactor. It quickly produces a summary of languages, LOC, and comments to guide audits and refactoring decisions.

What's the best way to generate structured outputs for codebase LOC metrics?▼

The best way to generate structured outputs for codebase LOC metrics is applying a targeted analysis to the repository, which validates results and structures the language breakdown and code counts for immediate use.

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