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ck:repomix

Pack local and remote Git repositories into AI-friendly XML, Markdown, JSON, or plain files.

Updated Apr 2, 2026
Search Tags:#repomix#security-audit#batch-processing#token-management#repository-packaging#llm-context
One-click install
npx skills add https://github.com/hidonguyen/trade-ops --skill ck-repomix-hidonguyen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ck:repomix
Source: https://github.com/hidonguyen/trade-ops/tree/main/.opencode/skills/repomix
Command: npx skills add https://github.com/hidonguyen/trade-ops --skill ck-repomix-hidonguyen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, pytest-cov, pytest-mock, repomix, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines packaging codebases into single, AI-friendly files so large language models can analyze, audit, or document repositories without manual file selection, formatting errors, or exceeding token limits.

Core Features & Use Cases

  • AI-optimized Packaging: Consolidates repositories into XML, Markdown, JSON, or plain text with clear separators and metadata for LLM consumption.
  • Remote & Batch Processing: Supports processing local paths, GitHub remote URLs via npx, and batch jobs with the provided Python script.
  • Token Management & Security: Produces token count summaries, token-count trees, comment removal, .repomixignore support, and secret scanning to reduce accidental data exposure.
  • Use Case: Create a token-aware snapshot of a project for security audits, cross-repo comparisons, code review context for an LLM, or documentation generation.

Quick Start

Use the ck:repomix skill to package this repository into a Markdown snapshot ready for LLM analysis.

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 Git repository into a single file for LLM context preparation?▼

You can package repositories for LLM context preparation by consolidating local paths or remote GitHub URLs into XML, Markdown, JSON, or plain text files. This creates AI-friendly snapshots with clear separators and metadata for language model consumption.

Can I process remote GitHub repositories in batch for security audits?▼

Yes, you can process remote GitHub repositories in batch for security audits using the provided Python script or npx. This enables packaging multiple codebases into AI-friendly files while applying secret scanning to reduce accidental data exposure.

Does repomix support token counting and comment removal for repository packaging?▼

Yes, repomix supports token management during repository packaging by producing token count summaries and token-count trees. It also includes comment removal features to help optimize the final file size for LLM consumption.

What is the best way to prepare code review context for an LLM without exceeding token limits?▼

The best way to prepare code review context for an LLM without exceeding token limits is consolidating repositories into AI-friendly files with token count summaries. Applying gitignore-aware filtering and .repomixignore support ensures only necessary files are packaged.

How do I configure include and ignore patterns when packaging repositories for AI analysis?▼

You can configure include and ignore patterns when packaging repositories for AI analysis via the repomix CLI or npx. It supports gitignore-aware filtering and .repomixignore files to precisely control which codebase files are consolidated into the final snapshot.

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