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Define Pydantic Schemas

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Orchestrate a CrewAI Industrial Feasibility Squad with Pydantic AI for GCC Green Iron Projects

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Linked challenge
Orchestrate a CrewAI Industrial Feasibility Squad with Pydantic AI for GCC Green Iron Projects

Prompt source

Original prompt text with formatting preserved for inspection.

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Define two Pydantic classes: `ProjectImpact` (with fields for carbon_footprint, water_usage, and local_jobs) and `FeasibilityReport` (which aggregates `ProjectImpact` and a list of `Risks`).

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.