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Simon-Copilot-Studio
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codebase-inspection

Identify codebase size and language distribution using pygount.

Updated Mar 7, 2026
Search Tags:#codebase#code-analysis#loc#pygount#language-breakdown#repository-metrics
One-click install
npx skills add https://github.com/Simon-Copilot-Studio/ai-content-hub --skill codebase-inspection-simon-copilot-studio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/Simon-Copilot-Studio/ai-content-hub/tree/main/github/codebase-inspection
Command: npx skills add https://github.com/Simon-Copilot-Studio/ai-content-hub --skill codebase-inspection-simon-copilot-studio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Codebases often require quick, repeatable metrics like lines of code, language distribution, and repository size. This Skill provides a fast, automated way to measure these attributes using pygount, reducing manual counting and guesswork.

Core Features & Use Cases

  • LOC counting and language breakdown for a repository
  • Code-vs-comment ratio insights and file counts
  • Use cases: evaluating a project's size before a refactor, comparing multiple repos for language mix, auditing a codebase for maintainability

Quick Start

Run pygount on the target repository to generate a full language breakdown and LOC 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 repository?▼

You can count lines of code and get a language breakdown by running pygount on the target repository, which generates a full report of LOC counts and language composition across the project.

What is the best way to measure codebase size before starting a refactor?▼

The best way to measure codebase size before a refactor is to run automated repository metrics using pygount, providing fast, repeatable file counts and language distribution data without manual counting.

Does pygount support code-vs-comment ratio analysis for multiple projects?▼

Yes, pygount supports code-vs-comment ratio analysis, allowing you to compare language mix and repository metrics across multiple projects of varying sizes to audit maintainability.

Can I exclude specific folders when analyzing repository metrics to ensure accurate counts?▼

Yes, you can and should exclude specific folders when analyzing repository metrics with pygount, as proper folder exclusions are required to provide accurate, fast metrics for your codebase.

What do I need to install to analyze codebase language distribution automatically?▼

You need to have pygount installed to analyze codebase language distribution, as this dependency is required to automatically identify language composition and generate the LOC report.

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