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codebase-inspection

Analyze code repositories to compute LOC counts, language distributions, and code-vs-comment ratios.

14|2|Updated Mar 29, 2026
Search Tags:#codebase#analyze#code-comments#loc#pygount#language-breakdown#repository-metrics
One-click install
npx skills add https://github.com/gquthier/CLAWG --skill codebase-inspection-gquthier
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/gquthier/CLAWG/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/gquthier/CLAWG --skill codebase-inspection-gquthier

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Inspect codebases to surface LOC counts, language distribution, and code-vs-comment ratios, enabling fast sizing and quality insights.

Core Features & Use Cases

  • LOC counting and language breakdown using pygount
  • Code-vs-comment ratio analysis across repositories
  • Use Case: Benchmark a project's size and language mix to guide refactoring or resourcing

Quick Start

Run the codebase-inspection workflow on a local repository to generate a concise metrics report.

Frequently Asked Questions about codebase-inspection

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze LOC counts and language distribution in a codebase?▼

You can compute code-vs-comment ratios by running a pygount-driven workflow on a repository path, which analyzes source files and returns structured metrics detailing the ratio of comments to lines of code.

How do I count lines of code and comments in a local repository?▼

To count lines of code and comments in a local repository, run the codebase-inspection workflow which accepts a repository path, supports folder exclusions, and returns structured metrics including LOC counts and comment ratios.

Can I exclude specific folders when calculating repository metrics?▼

Yes, you can exclude specific folders when calculating repository metrics. The workflow accepts a repository path and supports folder exclusions to isolate relevant code for accurate LOC counting and language breakdown.

What is the best way to benchmark a project's size and language mix for refactoring?▼

The best way to benchmark a project's size and language mix for refactoring is to inspect codebases using pygount, which surfaces LOC counts, language distributions, and code-vs-comment ratios to guide resourcing decisions.

Do I need pygount installed to analyze code-vs-comment ratios across projects?▼

Yes, you need pygount because the codebase inspection workflow relies on it to compute LOC counts, language distributions, and code-vs-comment ratios during repository audits or refactoring planning.

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