collab

Orchestrate round-based ideation among multiple LLMs and synthesize a unified plan.

126|22|Updated Jun 22, 2025
One-click install
npx skills add https://github.com/raine/consult-llm --skill collab-raine
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: collab
Source: https://github.com/raine/consult-llm/tree/main/skills/collab
Command: npx skills add https://github.com/raine/consult-llm --skill collab-raine

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinated multi-LLM brainstorming enables teams to surface diverse perspectives and produce a consolidated, actionable plan, reducing bias and paralysis.

Core Features & Use Cases

  • Round-robin collaboration: multiple models contribute and build on each other's ideas across rounds.
  • Synthesis: agent synthesizes best ideas into a concrete plan.
  • Guided experimentation: ideal for architecture decisions, design reviews, and risk assessment.

Quick Start

Load the collab skill, then load consult-llm, and trigger a multi-LLM brainstorming session to generate a plan.

Frequently Asked Questions about collab

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

FAQPage Schema
How do I use multi-LLM collaboration to synthesize an architecture plan?

You can run multi-LLM brainstorming by loading the collab skill alongside consult-llm, then triggering a session where models contribute ideas in rounds before a synthesis agent consolidates them into a unified plan.

What is round-robin brainstorming across multiple AI models?

Round-robin brainstorming is a coordinated collaboration method where multiple LLMs contribute ideas and build on each other's perspectives across sequential rounds to reduce bias and surface diverse viewpoints.

Can I use multi-model AI workflows for risk assessment and design reviews?

Yes, multi-model AI workflows are ideal for guided experimentation in architecture decisions, design reviews, and risk assessment, producing consolidated actionable plans from diverse model perspectives.

How does cross-model synthesis handle divergent perspectives during planning?

Cross-model synthesis uses a dedicated agent to evaluate and consolidate diverse model perspectives into a concrete plan, applying explicit orchestration rules and safeguards to prevent prompt leakage and divergence.

Do I need explicit model orchestration rules for multi-LLM brainstorming sessions?

Yes, multi-LLM brainstorming requires explicit model orchestration rules and session management to coordinate round-based ideation and ensure structured decision output for strategy or architecture tasks.