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Implement Error Handling with Extended Thinking

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Linked challenge: Orchestrate an AutoGen Agent Swarm for LLM Fine-Tuning & Deployment with Claude Opus 4.1 and MCP

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Linked challenge
Orchestrate an AutoGen Agent Swarm for LLM Fine-Tuning & Deployment with Claude Opus 4.1 and MCP

Prompt source

Original prompt text with formatting preserved for inspection.

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Implement the extended thinking and self-correction mechanism for the `Error_Recovery_Scenario`. When an agent encounters a simulated 'insufficient cloud quota' error during resource provisioning, it should use Claude Opus 4.1's reasoning capabilities to analyze the error, determine a corrective action (e.g., try provisioning a smaller GPU instance), and communicate the resolution to other agents.

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.