prism-debate

Name: prism-debate
Availability: InStock
Author: JayKim

Orchestrate multi-agent debates with fixed worldviews to synthesize evidence-based verdicts.

Updated Jan 17, 2026

Search Tags:#multi-agent #debate #decision-support #adversarial-analysis #position-tracking #round-based

Ready to run

npx skills add https://github.com/JayKim88/claude-ai-engineering --skill prism-debate

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: prism-debate
Source: https://github.com/JayKim88/claude-ai-engineering/tree/main/plugins/prism-debate/skills/prism-debate
Command: npx skills add https://github.com/JayKim88/claude-ai-engineering --skill prism-debate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables teams and AI systems to explore propositions by running multiple fixed-worldview agents in structured rounds, surfacing diverse arguments and counterarguments to improve decision quality.

Core Features & Use Cases

3-5 agents with distinct worldviews engage around a proposition, track positions, and provide rebuttals across rounds.
Supports quick verdict, autonomous rounds, and user-participatory modes for collaborative debate and decision validation.
Useful for product decisions, policy discussions, risk analysis, and requirement validation where multiple perspectives are valuable.

Quick Start

Initiate prism-debate on a topic and let 3-5 agents present, rebut, and track positions through iterative rounds.

Frequently Asked Questions about prism-debate

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

FAQPage Schema

How does multi-agent adversarial debate work for decision support?▼

Multi-agent adversarial debate works by assigning 3-5 fixed worldviews to distinct agents who present arguments, rebut, and track positions across iterative rounds to synthesize a final verdict with evidence.

What is structured round-based debate used for in product validation and policy analysis?▼

Structured round-based debate is used to surface balanced arguments for or against a proposition, improving decision quality and clarity for product validation, policy analysis, and risk assessment.

How do I run a multi-agent debate to analyze diverse viewpoints on a proposition?▼

To run a multi-agent debate, initiate the process by loading a proposition, allowing 3-5 agents to engage in iterative rounds of rebuttals, and synthesizing the final tracked positions into a verdict.

Can I participate in the adversarial analysis rounds, or is it fully autonomous?▼

You can participate in adversarial analysis rounds using the user-participatory mode for collaborative debate, or select autonomous rounds and quick verdict modes for fully automated decision validation.

When should I use multi-agent position tracking for decision-making instead of a single AI agent?▼

Use multi-agent position tracking when diverse viewpoints are required to improve clarity, as it surfaces counterarguments through adversarial analysis that a single agent approach would likely miss.

What are the limitations of using fixed worldviews in multi-agent debate?▼

Fixed worldviews limit agents to their assigned perspectives, meaning the final synthesized verdict depends entirely on the breadth and appropriateness of the initial worldviews loaded for the proposition.