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Review a proposed ML plan against knowledge base best practices. Returns approvals, risks, and improvement suggestions.

When to Use

  • Before executing a plan: Validate your approach before writing code
  • Catching assumptions: Find incorrect assumptions about how a framework works
  • Risk assessment: Know what pitfalls or edge cases to watch out for

Parameters

Example

Returns: Approvals (what looks good), risks (e.g., learning rate too low for QLoRA), and improvement suggestions.