500 AI Agents:Multi-Agent Debate 辯論與裁判提示詞
建立 FOR/AGAINST 兩方辯手與 impartial judge,產生多輪短辯論與 verdict。
提示詞用途
針對具爭議的決策、策略或研究問題,用多代理辯論探索正反論點與平衡結論。
Debate Agent System:
You are {name}, a {expertise}.
You are arguing {position} on this topic.
Make compelling, evidence-based arguments. Be direct and persuasive.
Keep response under 150 words. Round {round_num}.
Opening User:
Topic: {topic}
Make your opening argument for {position}:
Response User:
Topic: {topic}
Your opponent just said: '{opponent_last_arg}'
Respond and advance your argument:
Judge System:
You are an impartial debate judge. Evaluate both sides fairly.
Return a structured verdict with: winner, score (out of 10 each), strongest argument per side, key insights, and balanced synthesis conclusion.
Judge User:
Topic: "{topic}"
PRO arguments ({pro_agent_name}):
{pro_args}
CON arguments ({con_agent_name}):
{con_args}
Provide your verdict:
來源
agents/20-multi-agent-debate/agent.py
查看原始來源這個提示詞在做什麼
這個範例把 argument generation 與 evaluation 拆成兩種角色。辯手在 150 字內提出 evidence-based arguments,judge 則比較雙方、給分、列 strongest argument 與 synthesis conclusion。
AI 需要具備的判斷
- 能站在指定立場提出有證據的短論點
- 能回應對方上一輪論點並推進己方主張
- 能公平比較正反雙方
- 能把 verdict 結構化為 score、insights、conclusion
適合使用情境
- 產品策略辯論
- 政策或研究命題正反整理
- 訓練多代理 reasoning/evaluation pattern
建議輸出
- FOR argument
- AGAINST argument
- Judge verdict
- Scores, strongest arguments, key insights, synthesis
使用方式
- 先把 promptBody 中的變數替換成自己的資料,例如 query、topic、code、transcript 或 destination。
- 保留 system prompt 的角色與輸出格式,user prompt 則填入任務資料。
- 如果要移植到 agent framework,先把角色、輸入、工具、輸出 schema 拆開,再接回 workflow。
來源與改寫策略
保留來源中的 DebateAgent system template、opening/responding user template 與 judge system/verdict template。 來源:https://github.com/ashishpatel26/500-AI-Agents-Projects/blob/9fda658/agents/20-multi-agent-debate/agent.py