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Implement Tool Definitions and Integration
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Conversational Commerce Agent with LangGraph & Gemini 2.5 Pro
Format
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Linked challenge
Conversational Commerce Agent with LangGraph & Gemini 2.5 Pro
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
For each identified agent, define the necessary tools (e.g., `search_products`, `add_to_cart`, `process_payment`, `confirm_order`). Implement the Python functions for these tools that interface with your simulated e-commerce backend. Ensure robust error handling within these tool implementations to simulate real-world API failures. Connect these tools to your Gemini 2.5 Pro agents via LangGraph's tool-calling capabilities.
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.