Agent skill · data analytics · yamadashy
repomix
Pack and analyze codebases into AI-friendly single files using Repomix. Use when the user wants to explore repositories, analyze code structure, find patterns, check token counts, or prepare codebase context for AI analysis. Supports both local directories and remote GitHub repositories.
Why this skill is useful
Adds specific commands and options for analyzing codebases that the AI wouldn't reliably generate on its own.
What it needs
Requires npx installed locally. About 3k tokens when loaded. Last updated 2026-08-06. 27,686 stars on the source repository.
What this skill does
Repomix — Codebase Packer & Analyzer Pack entire codebases into a single, AI-friendly file for analysis. Repomix intelligently collects repository files, respects .gitignore, runs security checks, and generates structured output optimized for LLM consumption. When to Use "Analyze this repo" / "Explore this codebase" "What's the structure of facebook/react?" "Find all authentication-related code" "How many tokens is this project?" "Pack this repo for AI analysis" "Show me the main components of vercel/next.js" Quick Reference Pack a Remote Repository Always output to a temporary directory (/tmp on Unix, %TEMP% on Windows) for remote repositories to avoid polluting the user's working directory. Pack a Local Directory Key Options Option Description -------- ------------- --style <format> Output format: xml (default, recommended), markdown, plain, json --compress Tree-sitter compression (~70% token reduction) — use for large repos --include <patterns> Include only matching patterns (e.g., "src//.ts,/.md") --ignore <patterns> Additional ignore patterns --output <path> Custom output path (default: repomix-output.xml) --remote-branch <name> Specific branch, tag, or commit (for remote repos) Workflow Step 1: Pack the Repository Choose the appropriate command based on the target: Step 2: Check Command Output The command displays: Files processed: Number of files included Total characters: Size of content Total tokens: Estimated AI tokens Output file location: Where the file was saved Note the output file location for subsequent analysis. Step 3: Analyze the Output Structure overview: 1. Search for the file tree section (near the beginning of the output) 2. Check the metrics summary for overall statistics Search for patterns (use the output file path from Step 2): Read specific sections using offset/limit for large outputs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills yamadashy/clawhub