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Evez Debate Framework

该 Skill 提供多智能体辩论框架,支持支持、反对、综合、魔鬼代言人和专家等角色进行多轮辩论;裁判按证据、逻辑、新颖性、完整性等标准打分,最终返回每轮赢家、整体赢家、共识点、未解决问题和置信度。

evezart
evezart
热度 25.22
最近更新 2026-05-12 20:26:50
分类:开发依赖:代码执行 / 第三方 API / 内部调用大模型应用场景:代码生成 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add evez-debate-framework
Metadata
name
evez-debate-framework
description
Framework where multiple AI agents debate to reach better conclusions through adversarial reasoning. Use when building multi-agent systems, consensus-seeking AI, red-teaming with structured opposition, or improving LLM output quality through debate. Covers debate orchestration, judge evaluation, argument scoring, and convergence detection.

Multi-Agent Debate Framework

Multiple agents debate topics to reach stronger conclusions through adversarial reasoning.

Quick Start

from debate import Debate, Agent, Judge

debate = Debate("Should we use microservices?")
debate.add_agent(Agent("pro", stance="support", model="gpt-4o"))
debate.add_agent(Agent("con", stance="oppose", model="claude-sonnet-4"))
debate.add_agent(Agent("synth", stance="synthesize", model="gemini-2.5-pro"))
debate.set_judge(Judge(criteria=["evidence", "logic", "completeness"]))

result = debate.run(rounds=3)
# Returns: winner, consensus, key_arguments, confidence

How It Works

  1. Proposition: Pro agent argues for the topic
  2. Opposition: Con agent argues against
  3. Rebuttal: Each agent responds to the other's points
  4. Synthesis: Synth agent finds common ground
  5. Judgment: Judge evaluates all arguments and declares outcome

Debate Config

Debate(
    topic="Your question",
    rounds=3,                    # Number of debate rounds
    max_words_per_turn=500,      # Limit argument length
    convergence_threshold=0.7,   # Auto-stop when consensus reached
    judge_criteria=["evidence", "logic", "novelty", "completeness"],
)

Agent Stances

  • support — Argues in favor
  • oppose — Argues against
  • synthesize — Finds middle ground
  • devil_advocate — Argues weakest points to strengthen them
  • expert — Provides domain-specific knowledge

Judge

Evaluates arguments on configurable criteria and produces:

  • Winner per round
  • Overall winner
  • Consensus points
  • Unresolved issues
  • Confidence score