Why is token counting important in Repomix?

LLMs have limited context windows (e.g., 200k for Claude). Repomix counts tokens so you can ensure your packaged codebase fits within the limits of your target model.

What is Repomix used for?

Repomix packs an entire repository into a single, structured file that is easy for AI models to understand, making it ideal for codebase analysis, debugging, and providing context to LLMs.

Can I use Repomix on remote repositories?

Absolutely. You can use the --remote flag to package any public GitHub repository without needing to clone it to your local machine first.

Does Repomix protect my sensitive data?

Yes, it includes built-in security checks using Secretlint to detect and warn you about API keys, passwords, or credentials before you package your code for AI analysis.

Which output formats does Repomix support?

It supports XML, Markdown, JSON, and plain text, allowing you to choose the format best suited for your specific AI assistant or developer workflow.

Repomix Repository Packager

Name: Repomix Repository Packager
Author: nordeim

bynordeim

Developer Tools

Packages entire codebases into optimized, AI-friendly files to provide rich context for LLMs like Claude, ChatGPT, and Gemini.

About

Repomix is a specialized tool designed to bridge the gap between complex codebases and AI context windows. It intelligently packs entire repositories—including local or remote sources—into single, structured files such as XML, Markdown, or JSON while respecting .gitignore rules and security constraints. By optimizing file structures, stripping unnecessary comments, and providing accurate token counts, it allows developers to feed large-scale code context into LLMs for tasks like architectural analysis, security auditing, and comprehensive bug investigation without the need for manual copy-pasting.

Key Features

Remote repository support to process GitHub repos without local cloning.
0 GitHub stars
Multi-format output including XML, Markdown, and JSON optimized for LLM consumption.
Intelligent token counting to manage LLM context window limits.
Built-in security scanning with Secretlint to prevent sensitive data leakage.
Customizable file filtering and comment removal to reduce noise and token usage.

Use Cases

Generating comprehensive context for AI-driven code reviews and architectural planning.
Creating repository snapshots for documentation and codebase investigation.
Packaging third-party libraries for security audits and vulnerability assessments.

About

Key Features

Remote repository support to process GitHub repos without local cloning.
0 GitHub stars
Multi-format output including XML, Markdown, and JSON optimized for LLM consumption.
Intelligent token counting to manage LLM context window limits.
Built-in security scanning with Secretlint to prevent sensitive data leakage.
Customizable file filtering and comment removal to reduce noise and token usage.

Use Cases

Generating comprehensive context for AI-driven code reviews and architectural planning.
Creating repository snapshots for documentation and codebase investigation.
Packaging third-party libraries for security audits and vulnerability assessments.