competing-hypothesis-matrix
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/competing-hypothesis-matrix多假设管理——系统生成与主假设竞争的替代解释,设计能区分它们的关键预测,并构建结构化比较矩阵,避免 confirmation bias。
SKILL.md
.github/skills/competing-hypothesis-matrixView on GitHub ↗
---
name: competing-hypothesis-matrix
description: "Tactic: 多假设管理——生成竞争假设,设计区分性预测,构建结构化比较矩阵"
version: 1.0.0
category: hypothesis-formation
type: tactic
campaign: hypothesis-formulation
sops:
- competing-hypothesis-generation
- discriminating-prediction-design
- hypothesis-comparison-matrix
dependencies:
skills:
- subagent-spawning
---
# Competing Hypothesis Matrix
多假设管理——系统生成与主假设竞争的替代解释,设计能区分它们的关键预测,并构建结构化比较矩阵,避免 confirmation bias。
## 编排意图
科学推理中最危险的偏差是只持有一个假设。本 tactic 强制 CC 在确定"最优"假设之前,先系统构建竞争假设,再设计能将它们区分开来的预测。
三步不可颠倒:先生成竞争假设(不允许跳过),再设计区分性预测(不允许只比较,不测试),最后构建比较矩阵(不允许只列举,不量化)。最终产出不是"哪个假设是对的",而是"用什么实验能区分它们"。
## 可用 SOPs
| SOP | 职责 | 何时调用 |
|-----|------|---------|
| competing-hypothesis-generation | 基于主假设,生成 ≥3 个与之竞争的替代假设(不同机制,相同或相似的现象预测范围) | 所有模式必选,首先执行 |
| discriminating-prediction-design | 为每对竞争假设设计区分性预测——找到一个观察结果,使两个假设预测不同 | 所有模式必选,在 competing-hypothesis-generation 之后 |
| hypothesis-comparison-matrix | 将所有假设和区分性预测组装为结构化比较矩阵,标注各假设对每个预测的预期结果 | 所有模式必选,最后执行 |
## 编排模式
**Simplified(S tier,1 个主假设)**
- 顺序执行全部 3 个 SOP;生成 ≥3 个竞争假设;设计 ≥2 个区分性预测;构建比较矩阵
- 适用:单一主假设,需要竞争性思维检验
**Standard(M tier,2-3 个主假设)**
- competing-hypothesis-generation 为每个主假设独立生成竞争假设;discriminating-prediction-design 跨主假设和竞争假设设计区分性预测;hypothesis-comparison-matrix 包含所有假设(主 + 竞争)
- 适用:已有多个候选假设,需要统一管理和比较
**Deep(L tier,复杂假设集)**
- 全部 3 个 SOP 执行;competing-hypothesis-generation 额外要求:至少 1 个竞争假设来自完全不同的理论框架;discriminating-prediction-design 额外要求:每个区分性预测标注所需实验规模和难度;hypothesis-comparison-matrix 额外输出:推荐的实验优先级(最有区分力的预测排前)
- 适用:假设空间复杂,需要为实验设计提供直接输入
## Minimum Yield
- ≥3 个竞争假设(与主假设解释相同现象但机制不同)
- ≥2 个区分性预测(每个预测对至少 2 个假设产生不同的预期结果)
- 结构化比较矩阵:假设 × 预测,每格标注预期结果方向(支持/反对/无关)
## Yield Report
执行结束后向调用方 strategy 报告:
- 竞争假设数 / 区分性预测数
- 最有区分力的预测(能同时区分最多假设对)
- 最难区分的假设对(预测几乎相同,需要极精细的实验设计)
- 推荐优先测试的假设(最易被证伪 + 区分性最强)
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