feasibility-scoring

name	feasibility-scoring
description	SOP: assess the attackability of a research gap, identify bottlenecks, and output a feasibility score
version	1.0.0
category	hypothesis-formation
type	sop
campaign	gap-prioritization
input	GapRecord — a single normalized gap record
output	FeasibilityScore — dimension scores, composite score (1-5), bottleneck list and rationale
dependencies	{"skills":["subagent-spawning"]}

Feasibility Scoring

Assess the attackability of a research gap, identify bottlenecks, and output a feasibility score.

HARD-GATE

- The input must be a GapRecord with status: "complete" - The output composite score must be within the [1, 5] range - The bottleneck list (bottlenecks) must exist; if there are no bottlenecks it is an empty array [] - Each sub-dimension must carry at least 1 sentence of textual rationale

Pipeline

1. Pre-check: verify the completeness of the input GapRecord
2. Method-availability assessment: is the existing methodological toolbox sufficient to attack this gap (1-5); reference: are there mature algorithms/frameworks to reuse
3. Data-accessibility assessment: are the required datasets/corpora publicly available (1-5); reference: existence of public datasets, data-scale requirements
4. Resource-requirement assessment: are compute/experiment resource needs within a reasonable range (1-5); reference: GPU needs, lab equipment, funding
5. Time-horizon assessment: can it be completed within a typical PhD/project cycle (1-5); reference: expected workload, dependency-chain length
6. Composite scoring: equal-weighted average of the four dimensions, kept to one decimal place; extract the main bottlenecks (dimensions with score ≤ 2)
7. Output: return the FeasibilityScore object

Output Format

{
  "gap_id": "gap_001",
  "dimension_scores": {
    "method_availability": { "score": 4, "rationale": "..." },
    "data_accessibility": { "score": 2