codebase-inspection

Name: codebase-inspection
Availability: InStock
Author: linfordwu

Quantify codebase LOC, language distribution, and code-vs-comment ratios with pygount for CI pipelines.

1|1|Updated Apr 25, 2026

Search Tags:#codebase #code-analysis #loc #pygount #language-breakdown #repo-metrics

Ready to run

npx skills add https://github.com/linfordWu/owls --skill codebase-inspection-linfordwu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/linfordWu/owls/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/linfordWu/owls --skill codebase-inspection-linfordwu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Inspect and quantify codebases by counting LOC, breaking down languages, and measuring code-vs-comment ratios to inform project health.

Core Features & Use Cases

LOC counting and language breakdown for repositories
File counts and code-vs-comment analysis
Use cases: evaluating project size, tracking code quality, budgeting refactoring

Quick Start

Scan a repository to produce a language breakdown and LOC metrics with pygount.

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 scan a repository using pygount. This process produces LOC metrics and identifies language distribution to inform project health checks.

What is a code-vs-comment ratio and how is it used for project health checks?▼

A code-vs-comment ratio measures the proportion of comments relative to executable code in a codebase. It serves as a health-check metric to track code quality and inform refactoring budgets across repositories.

Can I integrate LOC analysis into a CI pipeline to track code quality?▼

Yes, you can integrate LOC analysis into local workflows or CI pipelines. Automating repository metrics like file counts and code-vs-comment ratios helps continuously track project size and code quality.

How do I analyze codebases of varying sizes for code-vs-comment ratios?▼

Analyzing codebases of varying sizes involves applying metrics tools like pygount to quantify LOC and code-vs-comment ratios. This produces standardized language reports and health-check metrics regardless of repository scale.

Do I need pygount to compute language distribution and file counts?▼

Yes, pygount is required to compute language distribution and file counts. It provides the underlying analysis needed to quantify codebase characteristics and generate accurate language breakdown reports.

What's the best way to evaluate project size for budgeting refactoring?▼

Evaluating project size for refactoring budgets requires quantifying codebase characteristics like LOC and file counts. Generating a language breakdown helps assess the overall scope and health of the codebase.