Tasks

Operator constructs Task(description='research the competitor', agent=researcher) with no expected_output.

expected_output is required by CrewAI and shapes the agent's task-completion criterion. Set a concrete, observable expected_output (e.g., 'A markdown table of 5 competitors with name/funding/HQ columns'). Missing or vague expected_output leaves the agent guessing when to stop — verify the field is …

Task B needs Task A's output as input. Operator passes context=[task_a] on Task B.

context=[task_a] causes Task A's output to be appended to Task B's prompt at execution time. Verify the dependency by inspecting the prompt B receives. If task_a fails, task_b should not silently start with empty context — surface the upstream failure.

Task is supposed to produce a typed result. Operator sets output_pydantic=CompetitorReport (a Pydantic model with name/funding/hq).

CrewAI coerces the agent's final output into CompetitorReport via JSON parsing + Pydantic validation. On ValidationError, the framework either retries with the schema in context or raises. Downstream consumers should read task.output.pydantic, not task.output.raw — and treat absence of pydantic as …