MN755 Mission Control TensorFlow Scaffolding
Purpose
Use Mission Control to scaffold TensorFlow or Keras code with real project structure, validation steps, and product-facing outputs instead of another disposable notebook.
The Codex chat agent is not the Mission Control Manager. It is the bridge between the user and the Mission Control Manager.
Use when
- The user wants to start a TensorFlow or Keras project.
- The repo needs a clean training, evaluation, and export skeleton.
- Product code matters more than demo-notebook theater.
Workflow
- Confirm the repo or requested feature actually needs TensorFlow.
- Ask Mission Control to choose a Keras-first starter shape for the product goal.
- Keep data loading, training, testing, export, and deployment surfaces separate.
- Require a validation loop that proves the scaffold runs before handoff.
Mission Control calls
Tools:
mission_control_start_taskmission_control_get_status
Resources:
mission-control://projects/{project_id}/codebase-mapmission-control://projects/{project_id}/validation-summary
Never do
- Do not treat TensorFlow scaffolding like generic Python boilerplate.
- Do not stop at
model.fit()if the user asked for a product path.
Example invocation
Use Mission Control to scaffold a Keras-first TensorFlow product workflow in this repo.