Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

100
Duration
15s
Input Tokens
3371
Output Tokens
194
Cost
$0.00
Context
Input
You need to list all open orders for a specific customer whose ID is `cust_42`. Which tool/method do you choose and what parameter object do you send?
Expected output
Use the **database** tool with parameters {"action": "list_orders", "customer_id": "cust_42"}.
Model output
Reasoning: The task is to list all open orders for a customer with ID 'cust_42'. The appropriate tool from the context is 'database', specifically the 'list_orders' method, which requires the customer_id parameter. Following the guidelines, I choose the 'database' tool to invoke the 'list_orders' method with the customer_id 'cust_42'. This approach efficiently retrieves all orders related to that customer, assuming it includes open orders. I will prepare the parameter object accordingly, ensuring it aligns with the required schema and constraints. This step is systematic and ensures the task is completed with minimal tool calls while maintaining accuracy.

Response: I will use the 'list_orders' method of the 'database' tool with the parameter object {'action': 'list_orders', 'customer_id': 'cust_42'} to retrieve all orders for the customer with ID 'cust_42'.