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repomix

Package entire code repositories into single AI-friendly files.

1|Updated Feb 17, 2026
Search Tags:#code analysis#LLM#AI context#repomix#code packaging#repository snapshot
One-click install
npx skills add https://github.com/chef0111/physthink --skill repomix-chef0111
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: repomix
Source: https://github.com/chef0111/physthink/tree/main/.agents/skills/repomix
Command: npx skills add https://github.com/chef0111/physthink --skill repomix-chef0111

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of packaging entire code repositories into single, AI-friendly files, making it easier to analyze, review, or provide context to Large Language Models (LLMs).

Core Features & Use Cases

  • Repository Packaging: Converts entire codebases into a single file, respecting .gitignore rules.
  • Multiple Output Formats: Supports XML, Markdown, JSON, and plain text outputs.
  • AI Optimization: Includes token counting and optional comment removal for LLM consumption.
  • Use Case: You need to provide a large codebase to an AI for a security audit. Use Repomix to package the entire repository into a single Markdown file, filtering out unnecessary files and removing comments to optimize for the AI's context window.

Quick Start

Use repomix to package the current directory into a markdown file.

Frequently Asked Questions about repomix

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

FAQPage Schema
How do I package an entire code repository into a single file for AI context?▼

Packaging a code repository for AI context involves consolidating the codebase into a single file using a code packaging tool. This process respects .gitignore rules and supports formats like XML, Markdown, JSON, and plain text for LLM consumption.

Can I remove comments and count tokens when preparing a codebase for LLM analysis?▼

Yes, you can remove comments and count tokens when preparing a codebase for LLM analysis. This AI optimization reduces file size and helps manage the context window by stripping unnecessary data from the repository snapshot.

Does repomix support packaging remote repositories or only local directories?▼

Repomix supports packaging both local directories and remote repositories. This allows you to directly fetch and consolidate a remote codebase into a single AI-friendly file without needing a local clone.

What is the best way to filter specific file types when creating a repository snapshot?▼

The best way to filter file types when creating a repository snapshot is using built-in filtering options. This allows you to include or exclude specific directories and file types, ensuring only relevant code is packaged for AI review.

How do I format code into XML or Markdown for a security audit by an AI?▼

To format code into XML or Markdown for an AI security audit, package the repository using a code consolidation tool. This converts the codebase into a structured single file, making it easier for the LLM to analyze the entire codebase.

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