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samuelmukoti
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codebase-inspection

Analyze codebases to compute LOC, language distribution, and code-vs-comment ratios.

Updated Apr 21, 2026
Search Tags:#codebase#code-quality#static-analysis#loc#language-analysis#pygount#repo-metrics
One-click install
npx skills add https://github.com/samuelmukoti/myai-agent --skill codebase-inspection-samuelmukoti
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/samuelmukoti/myai-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/samuelmukoti/myai-agent --skill codebase-inspection-samuelmukoti

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze codebases to count LOC, present language breakdown, and compute code-vs-comment ratios using pygount for quick repo-health insights.

Core Features & Use Cases

  • LOC counting with language distribution per repository
  • Code-vs-comment ratio analysis and file-level breakdown
  • Use Case: compare two repos to identify language mix and complexity

Quick Start

Run a repository analysis on the target path to output LOC, language distribution, and code-vs-comment metrics.

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 my repository?▼

Codebase inspection analyzes your repository to compute lines of code, language distribution, and file counts. It outputs per-language metrics and a code-vs-comment breakdown using pygount.

Can I analyze a large monorepo to estimate code size and language mix?▼

Yes, codebase inspection supports large monorepos for size estimation and language breakdown. It computes per-language metrics and file counts to help assess repository health and complexity.

What is the code-vs-comment ratio and how is it calculated?▼

The code-vs-comment ratio measures documentation density relative to executable code. Codebase inspection calculates this metric using pygount, providing a file-level breakdown suitable for reporting and audits.

Do I need pygount installed to analyze codebase metrics?▼

Yes, pygount is required to perform codebase inspection. This dependency enables the Skill to count lines of code, identify language distribution, and compute code-vs-comment ratios.

What is the best way to compare two repositories for language complexity and health?▼

Codebase inspection allows you to compare two repositories by running analysis on each target path. You can identify the language mix, lines of code, and code-vs-comment ratios for comparison.

What are the limitations of using LOC counting for repository health assessment?▼

Lines of code counting provides quantitative size and language distribution metrics but does not evaluate runtime logic or structural quality. Codebase inspection focuses on file counts and code-vs-comment ratios.

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