priority-synthesis

name	priority-synthesis
description	SOP: synthesize all scoring data into a final gap priority list and attack-path suggestions
version	1.0.0
category	hypothesis-formation
type	sop
campaign	gap-prioritization
input	All scoring data (ImportanceScore[] + FeasibilityScore[] + NoveltyScore[] + ImpactScore[]) + AHP weight vector
output	PriorityList — ordered gap list, weighted composite scores, attack-path suggestions for the top N
dependencies	{"skills":["subagent-spawning"]}

Priority Synthesis

Synthesize all scoring data into a final gap priority list and attack-path suggestions.

HARD-GATE

- Input must contain all scoring dimensions for every gap (importance / feasibility / novelty / impact) - The weight vector must be normalized (sum to 1.0, ±0.001 tolerance allowed) - The output priority_list is sorted by composite score in descending order, with no ties (if scores are equal, sort by the feasibility sub-score) - The top N gaps (N = min(3, total_gaps)) must include attack-path suggestions

Pipeline

1. Precondition check: verify completeness of the scoring data for every gap; verify the weight vector is normalized
2. Weighted aggregation: for each gap, use the AHP weights to compute a weighted sum of the four dimension scores into a composite score
3. Sorting: sort by composite score descending; on ties, sort by the feasibility sub-score
4. Top-N attack-path suggestions: for the top N gaps, combine their strongest dimensions with novelty's differentiation_directions to generate concrete attack-path suggestions (method choice, data sources, expected breakthrough point)
5. Overall analysis: output score-distribution statistics and dimension-contribution analysis
6. Output: return the PriorityList object

Output Format

{
  "priority_list": [
    {
      "rank": 1,
      "gap_id": "gap_003",
      "gap_title": "...",
      "composite_score": 4.2,
      "dimension_scores": {
        "importance": 4.5