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Repomix

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yamadashy
repomix

Pack and analyze codebases into AI-friendly single files using Repomix. Use when the user wants to explore repositories, analyze code structure, find patterns, check token counts, or prepare codebase context for AI analysis. Supports both local directories and remote GitHub repositories.

Overview

Publisheryamadashy
Repositoryrepomix
Skill namerepomix
Stars
28.8K
Forks
1.6K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by yamadashy on GitHub. Read the source before you install it.

Installation

Install the Repomix AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yamadashy/repomix/tree/main/.agents/clawhub
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yamadashy/repomix.git /tmp/repomix
mkdir -p .claude/skills
cp -r /tmp/repomix/.agents/clawhub .claude/skills/repomix
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Repomix in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Repomix on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Repomix is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Repomix — Codebase Packer & Analyzer

Pack entire codebases into a single, AI-friendly file for analysis. Repomix intelligently collects repository files, respects .gitignore, runs security checks, and generates structured output optimized for LLM consumption.

When to Use

  • "Analyze this repo" / "Explore this codebase"
  • "What's the structure of facebook/react?"
  • "Find all authentication-related code"
  • "How many tokens is this project?"
  • "Pack this repo for AI analysis"
  • "Show me the main components of vercel/next.js"

Quick Reference

Pack a Remote Repository

bash
npx repomix@latest --remote <owner/repo> --output /tmp/<repo-name>-analysis.xml

Always output to a temporary directory (/tmp on Unix, %TEMP% on Windows) for remote repositories to avoid polluting the user's working directory.

Pack a Local Directory

bash
npx repomix@latest [directory] --output /tmp/<name>-analysis.xml

Key Options

OptionDescription
--style <format>Output format: xml (default, recommended), markdown, plain, json
--compressTree-sitter compression (~70% token reduction) — use for large repos
--include <patterns>Include only matching patterns (e.g., "src/**/*.ts,**/*.md")
--ignore <patterns>Additional ignore patterns
--output <path>Custom output path (default: repomix-output.xml)
--remote-branch <name>Specific branch, tag, or commit (for remote repos)

Workflow

Step 1: Pack the Repository

Choose the appropriate command based on the target:

bash
# Remote repository (always output to /tmp)
npx repomix@latest --remote yamadashy/repomix --output /tmp/repomix-analysis.xml

# Large remote repo with compression
npx repomix@latest --remote facebook/react --compress --output /tmp/react-analysis.xml

# Local directory
npx repomix@latest ./src --output /tmp/src-analysis.xml

# Specific file types only
npx repomix@latest --include "**/*.{ts,tsx,js,jsx}" --output /tmp/filtered-analysis.xml

Step 2: Check Command Output

The command displays:

  • Files processed: Number of files included
  • Total characters: Size of content
  • Total tokens: Estimated AI tokens
  • Output file location: Where the file was saved

Note the output file location for subsequent analysis.

Step 3: Analyze the Output

Structure overview:

  1. Search for the file tree section (near the beginning of the output)
  2. Check the metrics summary for overall statistics

Search for patterns (use the output file path from Step 2):

bash
# Find exports and main entry points
grep -iE "export.*function|export.*class" <output-file>

# Search with context
grep -iE -A 5 -B 5 "authentication|auth" <output-file>

# Find API endpoints
grep -iE "router|route|endpoint|api" <output-file>

# Find database models
grep -iE "model|schema|database|query" <output-file>

Read specific sections using offset/limit for large outputs.

Step 4: Report Findings

  • Metrics: Files, tokens, size from command output
  • Structure: Directory layout from file tree analysis
  • Key findings: Based on pattern search results
  • Next steps: Suggestions for deeper exploration

Best Practices

  1. Use --compress for large repos (>100k lines) to reduce token usage by ~70%
  2. Use pattern search first before reading entire output files
  3. Use a temporary directory for output (/tmp on Unix, %TEMP% on Windows) to keep the user's workspace clean
  4. Use --include to focus on specific parts of a codebase
  5. XML is the default and recommended format — it has clear file boundaries for structured analysis

Output Formats

FormatBest For
XML (default)Structured analysis, clear file boundaries
MarkdownHuman-readable documentation
PlainSimple grep-friendly output
JSONProgrammatic/machine analysis

Error Handling

  • Command fails: Check error message, verify repository URL/path, check permissions
  • Output too large: Use --compress, narrow scope with --include
  • Network issues (remote): Verify connection, suggest local clone as alternative
  • Pattern not found: Try alternative patterns, check file tree to verify files exist

Security

Repomix automatically excludes potentially sensitive files (API keys, credentials, .env files) through built-in security checks. Trust its security defaults unless the user explicitly requests otherwise.

Frequently asked questions

What does the Repomix AI skill do?

Pack and analyze codebases into AI-friendly single files using Repomix. Use when the user wants to explore repositories, analyze code structure, find patterns, check token counts, or prepare codebase context for AI analysis. Supports both local directories and remote GitHub repositories.

Why use Repomix on TypingMind?

Because you install it once and use it with any model. Repomix is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Repomix in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yamadashy/repomix/tree/main/.agents/clawhub. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Repomix?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Repomix?

As many as you like. As long as a model supports skills, you can use Repomix with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Repomix AI skill free?

Yes. It is published on GitHub by yamadashy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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