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repomix skill

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This skill packages entire codebases into AI-friendly representations for efficient analysis, context-aware documentation, and secure, token-aware LLM

This is most likely a fork of the repomix skill from mamba-mental
npx playbooks add skill microck/ordinary-claude-skills --skill repomix

Review the files below or copy the command above to add this skill to your agents.

Files (2)
SKILL.md
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---
name: repomix
description: Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
---

# Repomix Skill

Repomix packs entire repositories into single, AI-friendly files. Perfect for feeding codebases to LLMs like Claude, ChatGPT, and Gemini.

## When to Use

Use when:
- Packaging codebases for AI analysis
- Creating repository snapshots for LLM context
- Analyzing third-party libraries
- Preparing for security audits
- Generating documentation context
- Investigating bugs across large codebases
- Creating AI-friendly code representations

## Quick Start

### Check Installation
```bash
repomix --version
```

### Install
```bash
# npm
npm install -g repomix

# Homebrew (macOS/Linux)
brew install repomix
```

### Basic Usage
```bash
# Package current directory (generates repomix-output.xml)
repomix

# Specify output format
repomix --style markdown
repomix --style json

# Package remote repository
npx repomix --remote owner/repo

# Custom output with filters
repomix --include "src/**/*.ts" --remove-comments -o output.md
```

## Core Capabilities

### Repository Packaging
- AI-optimized formatting with clear separators
- Multiple output formats: XML, Markdown, JSON, Plain text
- Git-aware processing (respects .gitignore)
- Token counting for LLM context management
- Security checks for sensitive information

### Remote Repository Support
Process remote repositories without cloning:
```bash
# Shorthand
npx repomix --remote yamadashy/repomix

# Full URL
npx repomix --remote https://github.com/owner/repo

# Specific commit
npx repomix --remote https://github.com/owner/repo/commit/hash
```

### Comment Removal
Strip comments from supported languages (HTML, CSS, JavaScript, TypeScript, Vue, Svelte, Python, PHP, Ruby, C, C#, Java, Go, Rust, Swift, Kotlin, Dart, Shell, YAML):
```bash
repomix --remove-comments
```

## Common Use Cases

### Code Review Preparation
```bash
# Package feature branch for AI review
repomix --include "src/**/*.ts" --remove-comments -o review.md --style markdown
```

### Security Audit
```bash
# Package third-party library
npx repomix --remote vendor/library --style xml -o audit.xml
```

### Documentation Generation
```bash
# Package with docs and code
repomix --include "src/**,docs/**,*.md" --style markdown -o context.md
```

### Bug Investigation
```bash
# Package specific modules
repomix --include "src/auth/**,src/api/**" -o debug-context.xml
```

### Implementation Planning
```bash
# Full codebase context
repomix --remove-comments --copy
```

## Command Line Reference

### File Selection
```bash
# Include specific patterns
repomix --include "src/**/*.ts,*.md"

# Ignore additional patterns
repomix -i "tests/**,*.test.js"

# Disable .gitignore rules
repomix --no-gitignore
```

### Output Options
```bash
# Output format
repomix --style markdown  # or xml, json, plain

# Output file path
repomix -o output.md

# Remove comments
repomix --remove-comments

# Copy to clipboard
repomix --copy
```

### Configuration
```bash
# Use custom config file
repomix -c custom-config.json

# Initialize new config
repomix --init  # creates repomix.config.json
```

## Token Management

Repomix automatically counts tokens for individual files, total repository, and per-format output.

Typical LLM context limits:
- Claude Sonnet 4.5: ~200K tokens
- GPT-4: ~128K tokens
- GPT-3.5: ~16K tokens

## Security Considerations

Repomix uses Secretlint to detect sensitive data (API keys, passwords, credentials, private keys, AWS secrets).

Best practices:
1. Always review output before sharing
2. Use `.repomixignore` for sensitive files
3. Enable security checks for unknown codebases
4. Avoid packaging `.env` files
5. Check for hardcoded credentials

Disable security checks if needed:
```bash
repomix --no-security-check
```

## Implementation Workflow

When user requests repository packaging:

1. **Assess Requirements**
   - Identify target repository (local/remote)
   - Determine output format needed
   - Check for sensitive data concerns

2. **Configure Filters**
   - Set include patterns for relevant files
   - Add ignore patterns for unnecessary files
   - Enable/disable comment removal

3. **Execute Packaging**
   - Run repomix with appropriate options
   - Monitor token counts
   - Verify security checks

4. **Validate Output**
   - Review generated file
   - Confirm no sensitive data
   - Check token limits for target LLM

5. **Deliver Context**
   - Provide packaged file to user
   - Include token count summary
   - Note any warnings or issues

## Reference Documentation

For detailed information, see:
- [Configuration Reference](./references/configuration.md) - Config files, include/exclude patterns, output formats, advanced options
- [Usage Patterns](./references/usage-patterns.md) - AI analysis workflows, security audit preparation, documentation generation, library evaluation

## Additional Resources

- GitHub: https://github.com/yamadashy/repomix
- Documentation: https://repomix.com/guide/
- MCP Server: Available for AI assistant integration

Overview

This skill packages entire code repositories into single, AI-friendly files using Repomix. It preserves file structure and context while offering filters, comment removal, token counting, and multiple output formats. Use it to create compact, LLM-ready snapshots for analysis, audits, or documentation workflows.

How this skill works

Repomix scans a local or remote repository, applies include/exclude patterns and .gitignore rules, and serializes selected files into one output file (XML, Markdown, JSON, or plain text). It can strip comments, detect sensitive data with Secretlint, and compute token counts per file and for the whole package to help fit LLM context limits. Custom headers, summaries, and configuration files let you tailor the produced artifact for downstream AI tasks.

When to use it

  • Prepare a repository snapshot to feed into an LLM for code review or architectural analysis
  • Package third-party libraries or dependencies for security audits without cloning everything manually
  • Create a consolidated context file for documentation generation or automated summarization
  • Bundle targeted modules when investigating bugs across multiple files or services
  • Trim and optimize repository content to fit specific LLM token limits before analysis

Best practices

  • Define precise include patterns to limit output to relevant source files and docs
  • Use .repomixignore or --no-gitignore cautiously to exclude sensitive or irrelevant files
  • Enable security checks and review output for hardcoded secrets before sharing
  • Monitor token counts and choose output format that balances readability and token efficiency
  • Remove comments when you need compact, code-only context but keep them for documentation tasks

Example use cases

  • Generate a Markdown snapshot of src/ and docs/ to feed into an LLM for feature planning
  • Produce an XML package of a vendor library via npx repomix --remote owner/repo for a security audit
  • Create a compact plain-text export with comments removed to fit within a 128K-token LLM context
  • Package authentication and API modules only to investigate a cross-service bug
  • Assemble a repo snapshot with token counts and a header summary for handoff to a contractor

FAQ

Can I run Repomix on a remote GitHub repo without cloning?

Yes. Repomix supports remote repository packaging via npx or the --remote flag and can target specific commits or URLs.

How does Repomix help with LLM token limits?

Repomix counts tokens per file and for the entire output, offers comment removal, and supports selective includes to keep the package within an LLM's context window.