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projectedanx
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𝕏@ALifeInArtifyAIGitHub

codebase-inspection

Analyzes software repositories with pygount to calculate code metrics and language distribution.

1|Updated May 12, 2026
Search Tags:#code analysis#codebase#metrics#repository#loc#pygount
One-click install
npx skills add https://github.com/projectedanx/hermes-agent --skill codebase-inspection-projectedanx
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/projectedanx/hermes-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/projectedanx/hermes-agent --skill codebase-inspection-projectedanx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount.

What problem does it solve?

This Skill eliminates the guesswork involved in understanding a project's scale by providing precise metrics on lines of code, language distribution, and documentation density.

Core Features & Use Cases

  • Language Breakdown: Quickly identify the primary programming languages used in a repository.
  • Code vs. Comment Analysis: Measure the ratio of executable code to documentation to assess project maintainability.
  • Use Case: When onboarding to a new repository, use this Skill to generate a summary report that highlights the project size and the complexity of its language composition.

Quick Start

Use the codebase-inspection skill to analyze the current directory and provide a summary of the lines of code 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 analyze lines of code and language distribution in a software repository?▼

To analyze lines of code in a software repository, this Skill scans directories to calculate total lines, language distribution, and code-to-comment ratios using the pygount utility. It generates a summary report highlighting project scale and language composition.

What is a code-to-comment ratio and how does it assess project maintainability?▼

A code-to-comment ratio measures the proportion of executable code to documentation within a repository. This Skill calculates the ratio to help assess project maintainability by indicating documentation density across the codebase.

Do I need pygount installed to calculate lines of code in a directory?▼

Yes, you need the pygount package installed in your environment to calculate lines of code accurately. This Skill relies on the pygount dependency to perform source code metrics extraction and language distribution analysis.

Can I exclude build artifacts and dependency folders when scanning a codebase?▼

Yes, you can exclude build artifacts and dependency folders when scanning a codebase. The analysis supports directory-level scanning with configurable exclusion patterns to ensure metrics reflect only relevant source code.

What's the best way to get a language breakdown when onboarding to a new repository?▼

The best way to get a language breakdown when onboarding to a new repository is to run a directory scan that identifies primary programming languages. This generates a summary report highlighting project size and language composition complexity.

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