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codebase-inspection

Analyze codebases with pygount for lines of code, language breakdown, and code-to-comment ratios.

1|Updated Apr 29, 2026
Search Tags:#code analysis#pygount#codebase metrics#language breakdown#lines of code
One-click install
npx skills add https://github.com/bailynlove/STARK-TOWER --skill codebase-inspection-bailynlove
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/bailynlove/STARK-TOWER/tree/main/opencrew/skills/github/codebase-inspection
Command: npx skills add https://github.com/bailynlove/STARK-TOWER --skill codebase-inspection-bailynlove

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount, and includes scripts (resource) components.

What problem does it solve?

This Skill provides insights into codebases, including lines of code, language composition, and code-to-comment ratios.

Core Features & Use Cases

  • LOC Counting: Accurately count lines of code for any given repository.
  • Language Breakdown: Determine the programming languages used within a repository.
  • Codebase Metrics: Analyze codebase size, composition, and health.
  • Use Case: When you need to understand the scope and complexity of a codebase, or when preparing for a code audit.

Quick Start

Run the codebase-inspection skill on your repository to analyze its codebase statistics.

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 analyze codebase metrics for a repository?▼

To count lines of code and analyze codebase metrics, you can use pygount to accurately measure lines of code, language breakdown, and code-to-comment ratios for any given repository.

What is included in a codebase language breakdown analysis?▼

A codebase language breakdown analysis includes determining the exact programming languages used within a repository, alongside metrics for codebase size, composition, and overall code-to-comment ratios.

How do I calculate the code-to-comment ratio for a code audit?▼

To calculate the code-to-comment ratio for a code audit, analyze the codebase using pygount, which provides specific metrics on the ratio of code lines to comment lines across the repository.

Does pygount support code analysis for evaluating repository scope and complexity?▼

Yes, pygount supports code analysis for evaluating repository scope and complexity by providing detailed metrics on lines of code and language composition applicable for codebase assessments and repository audits.

Can I use codebase metrics to prepare for a repository audit?▼

Yes, you can use codebase metrics to prepare for a repository audit by analyzing the codebase's size, language composition, and code-to-comment ratios to understand its overall scope and health.

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