An MCP workflow for implementing deep-learning models from an engineering plan [R]

I have been working on an MCP workflow for implementing deep learning models from an engineering plan. This is useful for ml engineers etc. who want a more structured way to move from a deep-learning goal to a working implementation. The process starts with a plan written by the engineer. That plan defines what the system should do, how it should be divided into components and the intended implementation direction. The workflow then helps Codex to: