Can I filter for specific file types like TypeScript or Python?

Yes, you can specify include patterns like '**/*.ts' to ensure only relevant source files are packed into the analysis file.

How does it handle very large repositories?

It uses a --compress flag powered by Tree-sitter to reduce the token size by approximately 70%. You can also use include/exclude patterns to focus on specific directories.

Do I need to install Repomix before using this skill?

No, the skill uses npx to execute the latest version of Repomix directly, meaning no permanent installation is required on your system.

Does Repomix Explorer work with private repositories?

Yes, it can analyze local directories and remote repositories that you have access to through your local shell environment and authenticated Git credentials.

What is the benefit of the XML output format?

XML is the recommended format for AI analysis because it provides clear, structured boundaries between files, making it easier for Claude to distinguish between different modules.

Repomix Explorer

Name: Repomix Explorer
Author: yamadashy

byyamadashy

•

21,373

Herramientas para Desarrolladores

Packs entire codebases into AI-optimized files to enable deep, context-aware repository analysis and pattern discovery.

Acerca de

Repomix Explorer empowers Claude to analyze complete local or remote repositories by condensing them into a single, structured XML or Markdown file. This skill automates the packing process using the Repomix CLI, handles token compression for large codebases, and utilizes advanced search techniques to extract insights about project architecture, file structures, and code patterns. It is an essential tool for developers needing to provide high-context codebase information to LLMs without manually copying and pasting multiple files.

Características Principales

Supports remote repository analysis from GitHub, GitLab, and Bitbucket URLs
Uses Tree-sitter compression to reduce token usage by up to 70% in large projects
Generates structured XML output for accurate AI parsing and file boundary detection
Automatically calculates file metrics, character counts, and estimated token usage
Provides advanced pattern search (grep) to find specific functions, classes, or configurations
21,373 GitHub stars

Casos de Uso

Rapidly onboarding to a new codebase by generating a structural overview and file tree
Preparing large-scale code context for LLM tasks like refactoring or feature implementation
Performing architectural audits to identify patterns, dependencies, and entry points

Acerca de

Características Principales

Supports remote repository analysis from GitHub, GitLab, and Bitbucket URLs
Uses Tree-sitter compression to reduce token usage by up to 70% in large projects
Generates structured XML output for accurate AI parsing and file boundary detection
Automatically calculates file metrics, character counts, and estimated token usage
Provides advanced pattern search (grep) to find specific functions, classes, or configurations
21,373 GitHub stars

Casos de Uso

Rapidly onboarding to a new codebase by generating a structural overview and file tree
Preparing large-scale code context for LLM tasks like refactoring or feature implementation
Performing architectural audits to identify patterns, dependencies, and entry points