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Pydantic AI Software-Defined Control Test Harness

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

Linked challenge: Software-Defined Controls (SDC) Testing Agent with Pydantic AI

Format
Code-aware
Lines
9
Sections
3
Linked challenge
Software-Defined Controls (SDC) Testing Agent with Pydantic AI

Prompt source

Original prompt text with formatting preserved for inspection.

9 lines
3 sections
No variables
0 checklist items
from pydantic import BaseModel, Field
from pydantic_ai import Agent

class TestResult(BaseModel):
    control_loop: str
    test_cases_passed: int
    test_cases_failed: int
    status: str = Field(description='APPROVED_FOR_DEPLOYMENT or REJECTED')

agent = Agent('openai:gpt-4o', result_type=TestResult)
# Implement agent verification loop for SDC software components

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.