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HuskyDanny
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codebase-inspection

Analyze codebases for lines of code, language composition, and code-vs-comment ratios.

Updated Apr 15, 2026
Search Tags:#code analysis#repository analysis#language breakdown#codebase stats#LOC counting
One-click install
npx skills add https://github.com/HuskyDanny/hermes-agent-config --skill codebase-inspection-huskydanny
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/HuskyDanny/hermes-agent-config/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/HuskyDanny/hermes-agent-config --skill codebase-inspection-huskydanny

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the process of inspecting codebases, providing valuable metrics like lines of code, language composition, and code-vs-comment ratios.

Core Features & Use Cases

  • LOC Counting: Get a total count of lines of code in a repository.
  • Language Breakdown: Analyze the distribution of programming languages in a codebase.
  • Codebase Stats: Obtain insights into the size and composition of a repository.
  • Use Case: When you need to quickly assess the complexity and language diversity of a repository.

Quick Start

Run the codebase-inspection skill on your repository to get a summary of LOC and language breakdown.

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 repository?▼

To count lines of code and get a language breakdown, you can analyze the repository to calculate total LOC and language distribution. This provides metrics on code composition and code-vs-comment ratios.

Do I need pygount to analyze codebase stats?▼

Yes, you need pygount installed to analyze codebase stats. The Skill requires this dependency to process repository files and calculate lines of code and language composition metrics.

What is the best way to assess code complexity and language diversity in a codebase?▼

The best way to assess code complexity and language diversity is by inspecting codebase metrics. Analyzing lines of code and language distribution provides insights into repository size and composition quickly.

Can I measure code-vs-comment ratios across a whole repository?▼

Yes, you can measure code-vs-comment ratios across a whole repository. The analysis evaluates source files to calculate the proportion of comment lines relative to executable lines of code.

What kind of codebase stats can I obtain from a repository analysis?▼

From a repository analysis, you can obtain codebase stats including total lines of code, programming language distribution, and the ratio of code to comments to assess repository composition.

Are there limitations when using a script-based approach for LOC counting?▼

Using a script-based approach for LOC counting depends on the pygount library's parsing capabilities, meaning recognition of languages and file types is limited to what the dependency supports.

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