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

16s

Input Tokens

3450

Output Tokens

1622

Cost

$0.01

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 retrieving all open orders for a specific customer (ID: cust_42). Reviewing the available tools in the context, the 'database' tool is the only one capable of accessing order-management data. Within this tool, the 'list_orders' method is specifically designed to retrieve orders for a given customer. According to the JSON schema provided for the database tool, the 'list_orders' action requires exactly two parameters: 'action' (const: 'list_orders') and 'customer_id' (string). While the schema does not explicitly show a 'status' parameter to filter for 'open' orders specifically, I must work with the parameters available in the schema. Therefore, I will invoke the database tool with the list_orders action and provide the customer_id 'cust_42'. The filtering for 'open' status would either be handled by the method itself or require post-processing of the returned list.

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