概要
The Experiment Retrospective skill automates the process of analyzing post-experiment data to ensure every lesson learned is captured and applied. By scanning training reports and experiment logs, it extracts critical metrics, hyperparameter results, and failure modes to generate structured summaries. It intelligently updates troubleshooting guides and creates or refines result-based skills, transforming raw data into permanent institutional knowledge. This skill is essential for developers and data scientists who want to bridge the gap between running experiments and building robust, documented workflows.
