| 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
repomix --version
Install
npm install -g repomix
brew install repomix
Basic Usage
repomix
repomix --style markdown
repomix --style json
npx repomix --remote owner/repo
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:
npx repomix --remote yamadashy/repomix
npx repomix --remote https://github.com/owner/repo
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):
repomix --remove-comments
Common Use Cases
Code Review Preparation
repomix --include "src/**/*.ts" --remove-comments -o review.md --style markdown
Security Audit
npx repomix --remote vendor/library --style xml -o audit.xml
Documentation Generation
repomix --include "src/**,docs/**,*.md" --style markdown -o context.md
Bug Investigation
repomix --include "src/auth/**,src/api/**" -o debug-context.xml
Implementation Planning
repomix --remove-comments --copy
Command Line Reference
File Selection
repomix --include "src/**/*.ts,*.md"
repomix -i "tests/**,*.test.js"
repomix --no-gitignore
Output Options
repomix --style markdown
repomix -o output.md
repomix --remove-comments
repomix --copy
Configuration
repomix -c custom-config.json
repomix --init
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:
- Always review output before sharing
- Use
.repomixignore for sensitive files
- Enable security checks for unknown codebases
- Avoid packaging
.env files
- Check for hardcoded credentials
Disable security checks if needed:
repomix --no-security-check
Implementation Workflow
When user requests repository packaging:
-
Assess Requirements
- Identify target repository (local/remote)
- Determine output format needed
- Check for sensitive data concerns
-
Configure Filters
- Set include patterns for relevant files
- Add ignore patterns for unnecessary files
- Enable/disable comment removal
-
Execute Packaging
- Run repomix with appropriate options
- Monitor token counts
- Verify security checks
-
Validate Output
- Review generated file
- Confirm no sensitive data
- Check token limits for target LLM
-
Deliver Context
- Provide packaged file to user
- Include token count summary
- Note any warnings or issues
Reference Documentation
For detailed information, see:
- Configuration Reference - Config files, include/exclude patterns, output formats, advanced options
- Usage Patterns - AI analysis workflows, security audit preparation, documentation generation, library evaluation
Additional Resources