What problem does it solve?
Large code repositories are overwhelming for AI models due to context window limitations and unstructured data. This Skill solves that by intelligently packaging entire codebases into concise, AI-friendly formats, making them digestible for analysis, review, and understanding.
Core Features & Use Cases
- AI-Optimized Packaging: Converts complex repositories into single XML, Markdown, JSON, or plain text files, preserving structure and context for LLM consumption.
- Customizable Filtering: Use include/exclude patterns,
.gitignore rules, and comment removal to tailor the output to specific AI analysis needs.
- Security & Token Management: Integrates Secretlint for sensitive data detection and provides token counts to manage LLM context limits effectively.
- Use Case: Before asking an AI to refactor a module, use Repomix to package only the relevant source files, stripping comments and ensuring it fits within the AI's context window, leading to more accurate and efficient code suggestions.
Quick Start
Package the current repository into a markdown file, removing all comments, and save it as 'codebase-snapshot.md'.