priority-synthesis
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/priority-synthesis综合所有评分数据产出最终 gap 优先级列表及攻击路径建议。
SKILL.md
.github/skills/priority-synthesisView on GitHub ↗
---
name: priority-synthesis
description: "SOP: 综合所有评分数据产出最终 gap 优先级列表及攻击路径建议"
version: 1.0.0
category: hypothesis-formation
type: sop
campaign: gap-prioritization
input: "全部评分数据(ImportanceScore[] + FeasibilityScore[] + NoveltyScore[] + ImpactScore[])+ AHP 权重向量"
output: "PriorityList — 有序 gap 列表、加权综合分、前 N 个攻击路径建议"
dependencies:
skills:
- subagent-spawning
---
# Priority Synthesis
综合所有评分数据产出最终 gap 优先级列表及攻击路径建议。
## HARD-GATE
<HARD-GATE>
- 输入必须包含所有 gap 的全部评分维度(importance / feasibility / novelty / impact)
- 权重向量必须归一化(和为 1.0,允许 ±0.001 误差)
- 输出 priority_list 按综合分降序排列,不得有并列(若分数相同则按 feasibility 子分排序)
- 前 N 个 gap(N = min(3, total_gaps))必须附带攻击路径建议
</HARD-GATE>
## Pipeline
1. **前置检查**: 验证所有 gap 的评分数据完整性;验证权重向量归一化
2. **加权汇总**: 对每个 gap,用 AHP 权重对四维评分加权求和得到综合分
3. **排序**: 按综合分降序排列;同分则按 feasibility 子分排序
4. **前 N 名攻击路径建议**: 对排名前 N 的 gap,结合其优势维度和 novelty 的 differentiation_directions,生成具体攻击路径建议(方法选择、数据来源、预期突破点)
5. **整体分析**: 输出分数分布统计、维度贡献分析
6. **输出**: 返回 PriorityList 对象
## Output Format
```json
{
"priority_list": [
{
"rank": 1,
"gap_id": "gap_003",
"gap_title": "...",
"composite_score": 4.2,
"dimension_scores": {
"importance": 4.5,
"feasibility": 3.8,
"novelty": 4.0,
"impact": 4.2
},
"attack_path": {
"recommended_approach": "方法建议(1-2句)",
"data_sources": ["数据来源1", "数据来源2"],
"expected_breakthrough": "预期突破点(1句)",
"estimated_timeline": "预估时间框架"
}
}
],
"statistics": {
"total_gaps": 5,
"score_range": [2.1, 4.2],
"mean_score": 3.3,
"top_dimension": "importance"
},
"synthesis_notes": "综合分析说明(3-5句)"
}
```
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