ML/AI Delivery Lifecycle Management

The mcaf-ml-ai-delivery skill provides a comprehensive framework for managing the complexities of machine learning and artificial intelligence project lifecycles within Claude Code. It streamlines the transition from initial data exploration and feasibility studies to model training, inference, and MLOps. By enforcing a rigorous iterative planning process known as the Ralph Loop, the skill ensures that product, data, and model assumptions are clearly separated, while integrating responsible AI and data quality checks directly into the development workflow. This results in highly traceable experiments, validated model artifacts, and professional documentation.

Key Features

Use Cases