tooyoung:codebase-stats

Name: tooyoung:codebase-stats
Availability: InStock
Author: shiqkuangsan

Count lines of code and analyze codebase structure across project types.

17|4|Updated Jan 25, 2026

Search Tags:#developer tools #code analysis #codebase #monorepo #loc #lines of code

Ready to run

npx skills add https://github.com/shiqkuangsan/oh-my-daily-skills --skill tooyoung-codebase-stats

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tooyoung:codebase-stats
Source: https://github.com/shiqkuangsan/oh-my-daily-skills/tree/main/skills/codebase-stats
Command: npx skills add https://github.com/shiqkuangsan/oh-my-daily-skills --skill tooyoung-codebase-stats

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps developers understand the size and composition of their codebase by counting lines of code (LOC) and identifying different modules within a project.

Core Features & Use Cases

Automated LOC Counting: Calculates LOC for various file types without external tools.
Monorepo Support: Detects and analyzes modules in complex monorepo structures (JS/TS, Rust, Java, Go, Python).
Use Case: Quickly assess the size of your project, identify the largest modules, and understand the distribution of code across different languages.

Quick Start

Run codebase-stats on the current project to see a breakdown of lines of code by file type and module.

Frequently Asked Questions about tooyoung:codebase-stats

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

FAQPage Schema

How do I count lines of code in a monorepo without installing external tools?▼

You can count lines of code in a monorepo without external tools by using built-in Bash scripting and Glob file discovery to identify modules and calculate LOC across JavaScript, TypeScript, Rust, Java, Go, and Python files.

Does codebase structure analysis work with multi-module projects?▼

Codebase structure analysis works with multi-module projects by detecting and analyzing different modules across complex monorepos and monoliths, identifying file types and calculating lines of code for various supported languages.

What is the best way to analyze codebase size across different programming languages?▼

The best way to analyze codebase size across different languages is to run an automated LOC counter that identifies file types and modules, providing a breakdown of lines of code for JavaScript, TypeScript, Rust, Java, Go, and Python.

How do I identify the largest modules in a complex project structure?▼

To identify the largest modules in a complex project structure, run codebase-stats to detect modules within monorepos and calculate the distribution of lines of code across different file types and languages.

Can I analyze a Rust and Go codebase composition using Bash scripting?▼

Yes, you can analyze Rust and Go codebase composition using Bash scripting and Glob to discover files and count lines of code without relying on external LOC counters, identifying modules and file types automatically.

When do I need to analyze codebase size and structure?▼

You need to analyze codebase size and structure when you want to quickly assess project scale, identify the largest modules, and understand the distribution of code across different languages within monorepos or multi-module projects.