consistency-check
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/consistency-check检验 pairwise 判断矩阵的传递一致性,识别不一致项并建议修正。
SKILL.md
.github/skills/consistency-checkView on GitHub ↗
---
name: consistency-check
description: "SOP: 检验 pairwise 判断矩阵的传递一致性,识别不一致项并建议修正"
version: 1.0.0
category: hypothesis-formation
type: sop
campaign: gap-prioritization
input: "n×n pairwise 判断矩阵(Saaty 标度值)+ 维度/gap 标签列表"
output: "ConsistencyReport — CR 值、不一致项列表及修正建议"
dependencies:
skills:
- subagent-spawning
---
# Consistency Check
检验 pairwise 判断矩阵的传递一致性,识别不一致项并建议修正。
## HARD-GATE
<HARD-GATE>
- 输入矩阵必须是方阵(n×n),n 在 [2, 9] 范围内
- 矩阵必须满足对角线全为 1 且 a[i][j] = 1/a[j][i](允许 0.001 浮点误差)
- CR 必须被计算并报告
- 若 CR > 0.1,inconsistent_pairs 列表不得为空
</HARD-GATE>
## Pipeline
1. **前置检查**: 验证矩阵为方阵;检查对角线和倒数性质;若违反则报告具体位置
2. **计算判断矩阵**: 确认输入矩阵有效
3. **计算一致性比率**: 列归一化 → 行均值(权重向量)→ 加权和向量 → λ_max → CI → CR(查 Saaty RI 表)
4. **识别不一致项**: 对每个三元组 (i, j, k),检验传递性 a[i][k] ≈ a[i][j] × a[j][k];偏差最大的对即为不一致项
5. **建议修正**: 对每个不一致项,建议将 a[i][j] 调整为使传递性成立的值
6. **输出**: 返回 ConsistencyReport 对象
## Output Format
```json
{
"labels": ["gap_001", "gap_002", "gap_003"],
"n": 3,
"lambda_max": 3.05,
"ci": 0.025,
"ri": 0.58,
"cr": 0.043,
"cr_acceptable": true,
"inconsistent_pairs": [],
"revision_suggestions": [],
"matrix_issues": []
}
```
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