yoetz

Coordinate multi-model LLM tasks for code review and bundling workflows.

6|Updated Feb 3, 2026
One-click install
npx skills add https://github.com/avivsinai/yoetz --skill yoetz
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: yoetz
Source: https://github.com/avivsinai/yoetz/tree/main/.claude/skills/yoetz
Command: npx skills add https://github.com/avivsinai/yoetz --skill yoetz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Fast, CLI-first orchestration of multiple LLMs for code review, bundling, and multimodal workflows, helping teams coordinate opinions and actions without leaving the terminal.

Core Features & Use Cases

  • Multi-Model Council: gather opinions from multiple models to reach consensus on code changes.
  • Bundle & Context Management: package files for LLM context, track sessions, and streamline reviews.
  • Ask, Review, Generate, Browser: perform single-model inquiries, code reviews, asset generation, and web fallback from the CLI.
  • Browser fallback: provide a web UI path when API access is limited or unavailable.

Quick Start

Install the yoetz CLI and begin by bundling files with yoetz bundle and asking questions with yoetz ask to see multi-model coordination in action.

Frequently Asked Questions about yoetz

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

FAQPage Schema
How do I run multi-model LLM code reviews from the CLI?

Multi-model LLM code reviews are run from the CLI by coordinating a council of models to analyze bundled code files, gathering consensus opinions and outputting structured JSON results directly in the terminal.

What is LLM bundling for code context management?

LLM bundling for code context management is the process of packaging files into a consolidated context for language models, streamlining reviews and tracking sessions without leaving the terminal environment.

Can I use a web browser for LLM tasks when API access is limited?

Yes, you can use a web browser fallback for LLM tasks when API access is limited or unavailable, providing an alternative web UI path for exploration and multimodal workflows.

How do I get consensus from multiple AI models on code changes?

You get consensus from multiple AI models on code changes by issuing a council command that gathers opinions across different models, applying explicit voting to reach a coordinated agreement.

Do I need specific dependencies to orchestrate multimodal LLM workflows?

No specific dependencies are required to orchestrate multimodal LLM workflows, as the CLI relies on environment configuration and optional resource directories to coordinate tasks like asking and generating.

What is the best way to package code files for LLM context?

The best way to package code files for LLM context is using a bundler command that consolidates files for language model processing, tracking sessions and streamlining subsequent code reviews.