scoring-matrix-construction
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/scoring-matrix-constructionConstructs a multi-dimensional scoring matrix for gap prioritization
- Solves the problem of biased gap prioritization using single-dimension scoring
- Depends on subagent-spawning and multiple scoring SOPs like importance-scoring
- Decides dimensions based on topic tier and domain relevance
- Delivers a complete matrix with scores, rationales, and weighted totals
SKILL.md
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---
name: scoring-matrix-construction
description: "Tactic: 编排多维度评分 SOP,为所有 gaps 构建综合评估矩阵"
version: 1.0.0
category: hypothesis-formation
type: tactic
campaign: gap-prioritization
sops:
- importance-scoring
- feasibility-scoring
- novelty-scoring
- impact-scoring
- ahrq-picme-assessment
dependencies:
skills:
- subagent-spawning
---
# Scoring Matrix Construction
编排多个评分维度 SOP,为每个 gap 构建多维度综合评估矩阵,作为排序决策的定量基础。
## 编排意图
单一维度评分容易产生偏差(例如纯按"重要性"排序会忽略可行性)。本 tactic 并行或串行调用各评分 SOP,在同一矩阵中对比所有 gaps 的多个维度得分,使优先级判断基于系统化证据而非直觉。
CC 根据 topic tier 选择覆盖维度数量;每个维度评分由专属 SOP 负责;评分完成后,CC 将各 SOP 产出汇总为单一矩阵格式。
## 可用 SOPs
| SOP | 职责 | 何时调用 |
|-----|------|---------|
| importance-scoring | 评估 gap 对领域的战略重要性(0-10) | 所有 tier 必选 |
| feasibility-scoring | 评估当前可用资源/方法下攻克 gap 的可行性(0-10) | 所有 tier 必选 |
| novelty-scoring | 评估 gap 的研究新颖性和原创贡献潜力(0-10) | 所有 tier 必选 |
| impact-scoring | 评估研究产出的潜在引用/应用影响(0-10) | M/L tier 增加 |
| ahrq-picme-assessment | 使用 AHRQ PiCMe 框架对临床/应用型 gap 做结构化评估 | L tier 或涉及 biomedical/health 领域时 |
## 编排模式
**Simplified(S tier,3 dims)**
- 调用:importance-scoring、feasibility-scoring、novelty-scoring
- 矩阵:gaps × 3 维度
- 并行执行所有 SOP,汇总结果
**Default(M tier,4 dims)**
- 调用:importance-scoring、feasibility-scoring、novelty-scoring、impact-scoring
- 矩阵:gaps × 4 维度
- 并行执行前 4 个 SOP,汇总结果
**Deep(L tier,5 dims + PiCMe)**
- 调用:全部 5 个 SOP
- 矩阵:gaps × 5 维度 + PiCMe 结构化评估附录
- 先并行执行前 4 个 SOP,PiCMe 串行在后(依赖领域确认)
## Minimum Yield
- 完整矩阵:所有 gaps × 所有维度均已填写得分(无空格)
- 每个评分单元均附有 1-2 句评分理由
- 矩阵包含加权合计列(默认等权重,除非上游提供权重)
- 产出格式:Markdown 表格 + 每个 gap 的评分摘要段落
## Yield Report
执行结束后向调用方 strategy 报告:
- 覆盖 gap 数量 / 评分维度数
- 得分分布(最高/最低/中位数)
- 评分差异最大的维度(供 sensitivity-testing 优先扰动)
- 评分置信度:哪些 gap 证据充分,哪些需要补充文献
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