npx skills add https://github.com/rysweet/amplihack --skill debate-workflow针对重要的架构决策、设计权衡以及存在多种有效方法的复杂问题,实施结构化的多视角辩论。
适用于:
避免用于:
视角数量:
3 - 默认(安全性、性能、简洁性)5 - 扩展(增加:可维护性、用户体验)7 - 全面(增加:可扩展性、成本)辩论轮次:
2 - 快速(立场 + 挑战)广告位招租
在这里展示您的产品或服务
触达数万 AI 开发者,精准高效
3 - 标准(立场 + 挑战 + 综合)4-5 - 深入(多次挑战/回应循环)收敛标准:
100% - 强共识(所有视角都同意)2/3 - 多数原则(三分之二同意)synthesis - 协调者综合最佳混合方案evidence - 遵循最有力的证据/论点安全性视角:
性能视角:
简洁性视角:
可维护性视角:
用户体验视角:
可扩展性视角:
成本视角:
决策界定模板:
# 决策:[简要标题]
## 问题
[一句话描述要辩论的问题]
## 背景
[为什么这个决策重要,背景信息]
## 约束条件
[不可协商的需求,技术限制]
## 评估标准
[我们将如何评判提出的解决方案]
## 需要包含的视角
[哪些观点最相关]
示例:
# 决策:用户分析数据存储策略
## 问题
我们应该使用 PostgreSQL(带 JSONB)、MongoDB 还是 ClickHouse 来存储和查询用户分析事件?
## 背景
- 预计上线时每天 1000 万事件
- 2 年内达到每天 1 亿事件
- 仪表板分析需要复杂查询
- 需要实时和历史报告
## 约束条件
- 必须至少处理每天 1000 万事件
- 仪表板查询延迟 < 200 毫秒
- 预算:每月 5000 美元基础设施
- 团队熟悉 PostgreSQL,不熟悉 ClickHouse
## 评估标准
1. 大规模性能
2. 查询灵活性
3. 运维复杂性
4. 大规模成本
5. 团队学习曲线
## 需要包含的视角
性能、成本、可维护性、可扩展性
初始立场要求:
第 1 轮输出结构:
## 安全性视角:[推荐]
支持论点:
1. [带证据的论点]
2. [带证据的论点]
3. [带证据的论点]
对替代方案的担忧:
- [替代方案 A]:[具体担忧]
- [替代方案 B]:[具体担忧]
假设:
- [假设 1]
- [假设 2]
挑战格式:
## [视角 A] 挑战 [视角 B]
挑战:[问题或反驳论点]
证据:[支持数据或示例]
要求:[什么会改变你的立场?]
回应格式:
## [视角 B] 回应 [视角 A]
回应:[回应挑战]
让步:[你同意或调整的要点]
反驳:[额外的证据或推理]
收敛分析:
## 一致领域
1. [共识点 1]
2. [共识点 2]
## 剩余分歧
1. [分歧 1]
- 安全性视角说:[立场]
- 性能视角说:[立场]
- 潜在解决方案:[混合方法]
## 已识别的混合方法
1. [混合选项 1]
- 结合了:[哪些视角]
- 权衡:[明确的成本/收益]
综合结构:
## 协调者综合
### 建议
[推荐方法的清晰陈述]
### 置信度
基于以下因素的[高/中/低]置信度:
- 共识水平:[X% 的视角同意]
- 证据质量:[强/中/弱]
- 风险水平:[如果错误,风险为低/中/高]
### 理由
[解释为何做出此建议]
### 获胜的关键论点
1. [影响决策的论点]
2. [影响决策的论点]
3. [影响决策的论点]
### 反对的关键论点(不同意见)
1. [最强的反驳论点]
2. [剩余的担忧]
### 实施指导
[如何执行此决策]
### 成功指标
[我们如何知道这是正确的选择]
### 重新审视触发条件
[需要重新考虑此决策的条件]
decisions/YYYY-MM-DD-decision-name.mdamplihack.memory.discoveries 中的 store_discovery() 存储到内存中决策记录模板:
# 决策记录:[标题]
日期:[YYYY-MM-DD]
状态:已接受
决策者:[包含的视角列表]
## 背景
[需要什么决策以及原因]
## 决策
[决定了什么]
## 后果
[由于此决策会发生什么]
## 考虑的替代方案
[辩论了哪些其他选项]
## 辩论摘要
[每个视角的关键论点]
## 不同意见
[哪些视角不同意及其原因]
## 审查日期
[何时重新审视此决策]
---
## 完整辩论记录
### 第 1 轮:初始立场
[所有视角的完整立场]
### 第 2 轮:挑战与回应
[所有挑战/回应交流]
### 第 3 轮:收敛分析
[共同点和混合方法]
### 协调者综合
[完整的综合文档]
成本: 多个代理循环,更长的决策时间 收益: 经过深思熟虑的决策,揭示隐藏风险 最适合: 难以逆转的决策
配置:
辩论摘要:
结果: 初始 MVP 使用 REST,v2 使用 GraphQL
配置:
辩论摘要:
结果: 70% 单元测试,30% 集成测试(多数同意)
配置:
辩论摘要:
结果: 采用无服务器,同时研究 k8s 选项
此工作流强制执行:
当复杂决策需要多视角分析时,此工作流取代 DEFAULT_WORKFLOW 的步骤 4(研究与设计)。实施(步骤 5)则按照共识决策进行。
每周安装次数
116
代码仓库
GitHub 星标数
39
首次出现
2026 年 1 月 23 日
安全审计
安装于
opencode105
codex100
cursor98
claude-code96
gemini-cli96
github-copilot94
Implement structured multi-perspective debate for important architectural decisions, design trade-offs, and complex problems where multiple valid approaches exist.
USE FOR:
AVOID FOR:
Number of Perspectives:
3 - Default (security, performance, simplicity)5 - Extended (add: maintainability, user-experience)7 - Comprehensive (add: scalability, cost)Debate Rounds:
2 - Quick (position + challenge)3 - Standard (position + challenge + synthesis)4-5 - Deep (multiple challenge/response cycles)Convergence Criteria:
100% - Strong consensus (all perspectives agree)2/3 - Majority rule (two-thirds agreement)synthesis - Facilitator synthesizes best hybridevidence - Follow strongest evidence/argumentsSecurity Perspective:
Performance Perspective:
Simplicity Perspective:
Maintainability Perspective:
User Experience Perspective:
Scalability Perspective:
Cost Perspective:
Decision Framing Template:
# Decision: [Brief Title]
## Question
[One-sentence question to be debated]
## Context
[Why this decision matters, background information]
## Constraints
[Non-negotiable requirements, technical limitations]
## Evaluation Criteria
[How we'll judge proposed solutions]
## Perspectives to Include
[Which viewpoints are most relevant]
Example:
# Decision: Data Storage Strategy for User Analytics
## Question
Should we use PostgreSQL with JSONB, MongoDB, or ClickHouse
for storing and querying user analytics events?
## Context
- 10M events/day expected at launch
- 100M events/day within 2 years
- Complex queries for dashboard analytics
- Real-time and historical reporting needed
## Constraints
- Must handle 10M events/day minimum
- Query latency < 200ms for dashboards
- Budget: $5K/month infrastructure
- Team familiar with PostgreSQL, not ClickHouse
## Evaluation Criteria
1. Performance at scale
2. Query flexibility
3. Operational complexity
4. Cost at scale
5. Team learning curve
## Perspectives to Include
Performance, Cost, Maintainability, Scalability
Initial Position Requirements:
Round 1 Output Structure:
## Security Perspective: [Recommendation]
Arguments For:
1. [Argument with evidence]
2. [Argument with evidence]
3. [Argument with evidence]
Concerns About Alternatives:
- [Alternative A]: [Specific concern]
- [Alternative B]: [Specific concern]
Assumptions:
- [Assumption 1]
- [Assumption 2]
Challenge Format:
## [Perspective A] challenges [Perspective B]
Challenge: [Question or counter-argument]
Evidence: [Supporting data or examples]
Request: [What would change your position?]
Response Format:
## [Perspective B] responds to [Perspective A]
Response: [Address the challenge]
Concession: [Points where you agree or adjust]
Counter: [Additional evidence or reasoning]
Convergence Analysis:
## Areas of Agreement
1. [Consensus point 1]
2. [Consensus point 2]
## Remaining Disagreements
1. [Disagreement 1]
- Security says: [position]
- Performance says: [position]
- Potential resolution: [hybrid approach]
## Hybrid Approaches Identified
1. [Hybrid Option 1]
- Combines: [which perspectives]
- Trade-offs: [explicit costs/benefits]
Synthesis Structure:
## Facilitator Synthesis
### Recommendation
[Clear statement of recommended approach]
### Confidence Level
[High/Medium/Low] confidence based on:
- Consensus level: [X% of perspectives agree]
- Evidence quality: [Strong/Moderate/Weak]
- Risk level: [Low/Medium/High if wrong]
### Rationale
[Explanation of why this recommendation]
### Key Arguments That Won
1. [Argument that swayed decision]
2. [Argument that swayed decision]
3. [Argument that swayed decision]
### Key Arguments Against (Dissenting Views)
1. [Strongest counter-argument]
2. [Remaining concern]
### Implementation Guidance
[How to execute this decision]
### Success Metrics
[How we'll know if this was the right choice]
### Revisit Triggers
[Conditions that would require reconsidering this decision]
decisions/YYYY-MM-DD-decision-name.mdstore_discovery() from amplihack.memory.discoveriesDecision Record Template:
# Decision Record: [Title]
Date: [YYYY-MM-DD]
Status: Accepted
Decision Makers: [List perspectives included]
## Context
[What decision was needed and why]
## Decision
[What was decided]
## Consequences
[What happens because of this decision]
## Alternatives Considered
[What other options were debated]
## Debate Summary
[Key arguments from each perspective]
## Dissenting Opinions
[Perspectives that disagreed and why]
## Review Date
[When to revisit this decision]
---
## Full Debate Transcript
### Round 1: Initial Positions
[Complete positions from all perspectives]
### Round 2: Challenges and Responses
[All challenge/response exchanges]
### Round 3: Convergence Analysis
[Common ground and hybrid approaches]
### Facilitator Synthesis
[Complete synthesis document]
Cost: Multiple agent cycles, longer decision time Benefit: Well-reasoned decisions, surface hidden risks Best For: Decisions that are expensive to reverse
Configuration:
Debate Summary:
Result: REST for initial MVP, GraphQL for v2
Configuration:
Debate Summary:
Result: 70% unit, 30% integration (Majority agreed)
Configuration:
Debate Summary:
Result: Serverless with k8s option researched
This workflow enforces:
This workflow replaces Step 4 (Research and Design) of the DEFAULT_WORKFLOW when complex decisions require multi-perspective analysis. Implementation (Step 5) proceeds with the consensus decision.
Weekly Installs
116
Repository
GitHub Stars
39
First Seen
Jan 23, 2026
Security Audits
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