10-of-my-most-popular-text-to-image-series-prompts-78b0897e
generate a bunch of images, then you curate the results to handpick the best ones
Agent Debate Skill
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install 0xrichyrich/agent-debate打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Spawn multiple sub-agents to debate approaches and converge on the best solution.
Uses parallel sub-agents with file-based coordination to simulate adversarial debate. Each agent investigates independently, writes findings, then a synthesis agent reviews all positions and picks the winner.
Best for: architecture decisions, debugging, strategy, trade analysis
plans/debate-{id}/agent-{n}.md
plans/debate-{topic}/
├── question.md # The question being debated
├── agent-1.md # Agent 1's position
├── agent-2.md # Agent 2's position
├── agent-3.md # Agent 3's position (optional)
├── rebuttal-1.md # Agent 1's rebuttal (round 2)
├── rebuttal-2.md # Agent 2's rebuttal (round 2)
├── synthesis.md # Final synthesis and verdict
└── decision.md # Lead's final decision
3 agents, one round, synthesis. ~5 minutes.
1. Write question to plans/debate-{topic}/question.md
2. Spawn 3 agents simultaneously:
- Agent A: "Argue FOR approach X. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-1.md"
- Agent B: "Argue FOR approach Y. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-2.md"
- Agent C: "Argue FOR approach Z. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-3.md"
3. Wait for all to complete
4. Spawn synthesis agent:
"Read all positions in plans/debate-{topic}/. Score each on: feasibility (1-10), risk (1-10), speed (1-10), quality (1-10). Write verdict to plans/debate-{topic}/synthesis....
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
# Agent Debate Skill
Spawn multiple sub-agents to debate approaches and converge on the best solution.
## Overview
Uses parallel sub-agents with file-based coordination to simulate adversarial debate. Each agent investigates independently, writes findings, then a synthesis agent reviews all positions and picks the winner.
## Pattern: Competing Hypotheses
Best for: architecture decisions, debugging, strategy, trade analysis
### How It Works
1. **Lead defines the question** and spawns 2-4 debate agents
2. Each agent writes their position to `plans/debate-{id}/agent-{n}.md`
3. A synthesis agent reads all positions and produces a verdict
4. Lead reviews and acts on the verdict
### File Structure
```
plans/debate-{topic}/
├── question.md # The question being debated
├── agent-1.md # Agent 1's position
├── agent-2.md # Agent 2's position
├── agent-3.md # Agent 3's position (optional)
├── rebuttal-1.md # Agent 1's rebuttal (round 2)
├── rebuttal-2.md # Agent 2's rebuttal (round 2)
├── synthesis.md # Final synthesis and verdict
└── decision.md # Lead's final decision
```
### Usage
#### Single Round (Fast)
3 agents, one round, synthesis. ~5 minutes.
```
1. Write question to plans/debate-{topic}/question.md
2. Spawn 3 agents simultaneously:
- Agent A: "Argue FOR approach X. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-1.md"
- Agent B: "Argue FOR approach Y. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-2.md"
- Agent C: "Argue FOR approach Z. Read plans/debate-{topic}/question.md. Write your position with evidence to plans/debate-{topic}/agent-3.md"
3. Wait for all to complete
4. Spawn synthesis agent:
"Read all positions in plans/debate-{topic}/. Score each on: feasibility (1-10), risk (1-10), speed (1-10), quality (1-10). Write verdict to plans/debate-{topic}/synthesis....generate a bunch of images, then you curate the results to handpick the best ones
generate a bunch of images, then you curate the results to handpick the best ones
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