Skill UI

This skill performs a deep, cross-model audit of experimental results to ensure integrity before claiming findings. It systematically checks for common fraud patterns, such as generating fake ground truths, misleading score normalization, or citing phantom results. Use it when evaluating reported experimental outcomes to ensure methodological rigor and trustworthiness.