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repomix skill

/skills/repomix

This skill packages entire codebases into AI-friendly files, optimizing token usage and providing multi-format outputs for efficient LLM analysis.

npx playbooks add skill mamba-mental/agent-skill-manager --skill repomix

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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 context and structure while offering filters, comment removal, token counting, and multiple output formats to prepare repositories for LLM analysis. Use it to create compact, audit-ready snapshots or to feed code context into conversational models.

How this skill works

The skill scans a local or remote repository, applies include/exclude patterns, and optionally strips comments or sensitive data. It generates outputs in XML, Markdown, JSON, or plain text, counts tokens per file and overall for LLM budget planning, and flags potential secrets using security checks. Outputs can include custom headers and summaries and respect .gitignore or a .repomixignore file.

When to use it

  • Prepare a repository snapshot for an LLM-based code review or assistant.
  • Create a compact context file for security audits or compliance reviews.
  • Package third-party libraries or unfamiliar code before analysis.
  • Generate documentation-ready context combining code and docs for downstream tooling.
  • Bundle targeted modules for focused bug investigations or design reviews

Best practices

  • Define strict include/exclude patterns to keep outputs focused and under token limits.
  • Enable security checks and inspect results before sharing outputs externally.
  • Use token counts to select the appropriate LLM and output format for your context size.
  • Strip comments when you need concise logic-only snapshots; keep comments when documentation context is required.
  • Maintain a .repomixignore for secrets and non-essential files to avoid accidental exposure

Example use cases

  • Package a feature branch (src/**) into a Markdown file for an LLM-powered code review.
  • Generate an XML snapshot of a vendor library for a security audit with Secretlint warnings.
  • Create a combined docs+code Markdown file to feed a documentation generator or assistant.
  • Extract only auth and API modules for focused bug triage and provide token counts for LLM selection.
  • Produce a JSON output of a remote repo at a specific commit for reproducible forensic analysis

FAQ

Can Repomix process remote repositories without cloning?

Yes. It can fetch and package remote repositories by shorthand, full URL, or specific commit reference without a local clone.

How does token counting work and why does it matter?

Repomix reports token counts per file and total for chosen formats so you can choose an LLM that fits the context window and avoid truncation during analysis.

Can I remove comments and sensitive data automatically?

You can enable comment removal and secret detection; however, always manually review outputs because automated checks are not foolproof.