ck:repomix

Pack repositories into XML, Markdown, JSON, or plain text for AI ingestion.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-repomix-dattran26
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ck:repomix
Source: https://github.com/DatTran26/KienTruThiHanh/tree/main/.agents/skills/repomix
Command: npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-repomix-dattran26

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Repomix reduces friction when feeding large codebases to AI systems by packaging repositories into AI-friendly formats that preserve structure and key metadata.

Core Features & Use Cases

  • AI-optimized packaging: outputs XML, Markdown, JSON, or plain text suitable for ingestion by LLMs and copilots.
  • Local and remote repository support: package code from your filesystem or remote sources without manual cloning.
  • Context-aware snapshots: generate compact representations that respect token limits for AI analysis, audits, and documentation.

Quick Start

Package the current directory with Repomix to generate an AI-friendly repository snapshot.

Frequently Asked Questions about ck:repomix

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

FAQPage Schema
How do I package a codebase into AI-friendly formats for LLM ingestion?

Packaging a codebase into AI-friendly formats involves consolidating repository files into XML, Markdown, JSON, or plain text. This process creates compact snapshots that preserve structure and metadata for efficient AI analysis and code review.

Can I package remote repositories without manually cloning them first?

Yes, you can package remote repositories directly without manual cloning. The tool fetches code from remote sources and packages it into AI-friendly files, streamlining the workflow for AI context generation and security auditing.

Does repository packaging support include and exclude patterns for file filtering?

Yes, repository packaging supports include and exclude patterns to filter files. This ensures only relevant code is packaged into the AI-friendly snapshot, optimizing token counts and preventing unnecessary data from reaching the LLM.

What is the best way to prepare a large codebase for AI security auditing?

Preparing a large codebase for AI security auditing requires generating context-aware snapshots that respect token limits. Packaging repositories into structured XML or Markdown outputs ensures AI assistants can efficiently ingest and analyze the codebase.

Do I need the Repomix CLI installed to pack repositories into AI snapshots?

Yes, the Repomix CLI is required to pack repositories into AI snapshots. This command-line dependency handles the repository packaging process, enabling local and remote codebase extraction for AI assistant ingestion.

Why does packaging a repository for AI context require token counting?

Packaging a repository for AI context requires token counting to ensure the generated snapshots respect LLM token limits. This prevents oversized inputs and optimizes the compact representation of code for efficient AI analysis and documentation.