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repomix-analysis

Pack repositories into XML files for large-context AI analysis.

52|4|Updated Jan 18, 2026
Search Tags:#code analysis#ai#gemini#repomix#large context#codebase packing
One-click install
npx skills add https://github.com/vicnaum/vics-agent-skills --skill repomix-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: repomix-analysis
Source: https://github.com/vicnaum/vics-agent-skills/tree/main/skills/repomix-analysis
Command: npx skills add https://github.com/vicnaum/vics-agent-skills --skill repomix-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines complex code analysis by intelligently packing large codebases into manageable formats suitable for advanced AI models, overcoming token limitations.

Core Features & Use Cases

  • Codebase Packing: Uses Repomix to create AI-friendly representations (e.g., XML) of entire repositories or specific sub-sections.
  • Contextual Analysis: Enables AI models with vast context windows (like Gemini) to perform deep, cross-file analysis.
  • Iterative Refinement: Guides the packing process based on token counts and user-defined scope, ensuring efficient use of AI context.

Quick Start

Use the repomix-analysis skill to pack the entire current repository into an XML file for analysis by a large-context AI model.

Frequently Asked Questions about repomix-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze a large codebase that exceeds AI token limits?▼

Repomix packs large codebases into AI-friendly XML formats to overcome token limits for analysis. It enables models with vast context windows to perform deep, cross-file analysis by creating manageable representations of entire repositories or specific sub-sections.

What is the best way to prepare repository files for Gemini Pro code analysis?▼

Repomix creates AI-friendly XML representations of entire repositories, enabling models like Gemini Pro with vast context windows to perform deep, cross-file analysis. It guides the packing process based on token counts to ensure efficient use of AI context.

Can I analyze specific sub-sections of a repository instead of the entire codebase?▼

Yes, you can analyze specific sub-sections by using iterative scope reduction and semantic splitting. This approach guides the packing process based on your defined scope and token counts, ensuring targeted and efficient AI analysis.

How does codebase packing handle token count constraints for AI models?▼

Codebase packing handles token constraints through iterative refinement based on token counts. It intelligently packs large codebases into manageable formats, ensuring efficient use of AI context windows during cross-file analysis.

Does repomix-analysis require any external dependencies to run?▼

No, repomix-analysis does not require any external dependencies to run. It operates independently using its internal scripts and references to pack repositories into AI-friendly formats for large-context models.

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