Which output formats are supported?

Repomix supports multiple output formats including XML, Markdown, JSON, and plain text, allowing you to choose the format that your specific LLM handles most effectively.

Can I use Repomix on remote repositories?

Yes, Repomix can process remote GitHub repositories directly using the --remote flag, making it easy to analyze third-party libraries without cloning them.

Does Repomix handle sensitive data?

Yes, Repomix includes built-in security checks using Secretlint to detect and warn about sensitive information like API keys, passwords, and private credentials before you share the code with an AI.

Repomix is a tool that packs entire codebases into a single file formatted specifically for AI assistants like Claude, ChatGPT, and Gemini to ensure they have the full context of your project.

How does Repomix help with LLM token limits?

It provides automated token counting for individual files and the total repository, helping you filter out unnecessary files to stay within the context window of models like Claude 3.5 Sonnet.

Repomix Repository Packager

Name: Repomix Repository Packager
Author: Microck

byMicrock

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개발자 도구

Packages entire codebases into single, token-optimized files for seamless AI analysis and LLM context management.

Repomix is a powerful utility designed to bridge the gap between complex codebases and large language models (LLMs) by compressing entire repositories into single, AI-friendly files. It supports multiple output formats like XML and Markdown while intelligently respecting .gitignore rules, stripping unnecessary comments, and performing security checks to prevent sensitive data leaks. Whether you are performing a deep-dive security audit, providing context for complex bug fixes, or onboarding an AI assistant to a new library, Repomix ensures your codebase is structured for maximum comprehension and minimal token waste.

주요 기능

01Direct processing of remote repositories without requiring local cloning

02Intelligent file filtering using .gitignore and custom include/exclude patterns

03Automated token counting to optimize LLM context window usage

04Multi-format output support including XML, Markdown, and JSON

05Built-in security scanning via Secretlint to detect leaked credentials

0681 GitHub stars

사용 사례

01Creating comprehensive context snapshots for LLM-based code reviews and debugging

02Generating AI-ready documentation and implementation plans for legacy codebases

03Packaging third-party libraries for deep security and architectural analysis

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills repomix

For use in Claude.ai and ChatGPT

Download Skill