Multi-Agent Debate — Adversarial Reasoning for Better Decisions

I will build a multi-agent debate system — where multiple agents with different assigned perspectives argue for their position, challenge each other's reasoning, and a judge agent evaluates the arguments to reach a reasoned conclusion — for decision support, risk analysis, or complex reasoning tasks where a single agent's perspective is systematically biased. Agent debate systems are particularly valuable for decision support in contexts where the consequences of a one-sided analysis are significant — investment decisions, policy analysis, technical architecture choices, and risk assessments all benefit from a structured adversarial process that surfaces counter-arguments a single-perspective analysis misses.

The system covers advocate agent configuration with assigned perspectives, structured debate rounds with response and counter-response, argument quality assessment, a judge agent evaluating argument merit, and a decision report summarising the debate and reasoned conclusion.