model-chat

Orchestrate a multi-agent debate and synthesize consensus, disagreements, and action steps.

1|Updated Apr 10, 2026

Search Tags:#claude #multi-agent #orchestration #synthesis #debate #decision-making

Ready to run

npx skills add https://github.com/ezjonline/ezj-automations --skill model-chat-ezjonline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: model-chat
Source: https://github.com/ezjonline/ezj-automations/tree/main/skills/model-chat
Command: npx skills add https://github.com/ezjonline/ezj-automations --skill model-chat-ezjonline

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, python-dotenv.

What problem does it solve?

This Skill helps you evaluate complex questions by turning a single prompt into a structured debate among multiple AI perspectives, reducing blind spots and surfacing stronger decisions.

Core Features & Use Cases

Parallel Multi-Agent Debate: Spawns several specialized agents that respond in round-robin fashion with full shared context.
Structured Synthesis: Merges agreement, disagreement, surprising insights, and a final recommendation into a clear output.
Interactive Steering: Lets you inject guidance between rounds when the discussion needs redirection.
Use Case: Ask it to compare product strategies, troubleshoot a design choice, or pressure-test a plan before you commit to it.

Quick Start

Ask the model-chat skill to run a multi-agent debate on your chosen topic and return the final synthesis.

Frequently Asked Questions about model-chat

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

FAQPage Schema

How do I run a multi-agent debate to evaluate a product strategy?▼

To run a multi-agent debate, prompt the system with your topic to spawn specialized agents that respond in round-robin fashion with full shared context, culminating in a structured synthesis of consensus, disagreements, and action steps. This process reduces blind spots and surfaces stronger decisions.

What is multi-agent orchestration for decision-making?▼

Multi-agent orchestration for decision-making is a process that spawns several specialized AI agents to analyze a topic in parallel. It manages a round-robin conversation, preserves transcripts, and merges agreements and disagreements into a structured final recommendation.

How do I pressure-test a plan using parallel AI perspectives?▼

You can pressure-test a plan by initiating a structured debate among multiple AI agents, applying interactive steering to inject guidance between rounds. The agents evaluate tradeoffs in parallel and produce a synthesized recommendation of action steps.

Do I need Anthropic and python-dotenv to orchestrate AI debates?▼

Yes, you need the Anthropic and python-dotenv dependencies to orchestrate AI debates. Anthropic provides the underlying model capabilities for the agents, while python-dotenv manages environment configuration required to execute the parallel agent orchestration.

Can I inject guidance into an AI debate between rounds?▼

Yes, you can inject guidance into an AI debate between rounds through interactive steering. This feature lets you redirect the discussion when the parallel perspectives need adjustment before the final synthesis of consensus and action steps is generated.

What is the best way to synthesize disagreements from multiple AI agents?▼

The best way to synthesize disagreements from multiple AI agents is using a structured multi-agent debate. It preserves shared context transcripts during round-robin execution and merges surprising insights, disagreements, and consensus into a clear final recommendation.