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0106. User Story: Add simple checks and documentation for ML behavior #611

Description

@aluczak

As a developer, I want basic safeguards around recommendation quality and stability, so that I can notice if the model or data degrades.

Acceptance criteria:

  • Documentation describes common failure modes and how to respond
  • Simple sanity checks (e.g., no empty recommendation lists) are in place
  • Guidance exists on when to retrain or roll back a model

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