Rank and critique metamaterial design hypotheses using weighted multi-factor scoring. Use when you need to prioritize which hypothesis to simulate first.
Score and rank hypotheses to determine the best first CST simulation trial.
When this skill is invoked (typically after hypothesis generation):
Score each hypothesis using six weighted factors:
Formula: Score = 0.25E + 0.25T + 0.15P + 0.10C + 0.10F + 0.15R
descending.
Generate a recommendation: which hypothesis to try first and why, noting trade-offs with alternatives.
Use your domain expertise to critique the ranking:
Run via Python:
cd D:/Claude && python -c "
from target_to_hypothesis.skills.hypothesis_ranker import rank_hypotheses
# ranked = rank_hypotheses(hypotheses, evidence_grades, llm_fn=my_llm_fn)
"
D:/Claude/target_to_hypothesis/skills/hypothesis_ranker.py
D:/Claude/target_to_hypothesis/config/scoring_weights.yaml