概要
This skill provides a structured framework for managing Python-based experiments within the Viterbo ecosystem. It enforces specific directory layouts for experiments and shared helpers, defines standardized stage entrypoints, and streamlines asset generation for LaTeX integration. By providing pre-configured linting, smoke testing, and data artifact management commands, it ensures that machine learning and data science projects remain maintainable, reproducible, and aligned with best practices like pure functions and detailed docstrings.
