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.

Duration

Input Tokens

3604

Output Tokens

223

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 requires listing all open orders for customer ID 'cust_42'. Reviewing the available tools in the context, the 'database' tool is relevant for order-management data. It includes the 'list_orders' method, which takes 'action': 'list_orders' and 'customer_id' as required parameters. This method is designed to retrieve orders for a specific customer, and while the schema does not explicitly mention filtering for 'open' orders, it aligns with the task's need to list orders (assuming open status can be determined from the results or is implied). No other tool (e.g., email, calendar) is suitable for querying orders. Following the instructions: I inspected the schema first, plan to call exactly one tool (database with list_orders), and will persist results in memory after success. The parameter object is precise per the schema.

Response: Tool: 'database'
Method: 'list_orders'
Parameter object: {"action": "list_orders", "customer_id": "cust_42"}