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

12s

Input Tokens

3783

Output Tokens

1133

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: To fulfill the request of listing all open orders for a specific customer, I analyzed the available tools in the context. The 'database' tool is described as capable of reading and updating order-management data. Specifically, the 'list_orders' method within the 'database' tool schema is designed to retrieve a list of orders given a 'customer_id'. Therefore, I selected the 'database' tool and constructed the parameter object with the required 'action' set to 'list_orders' and the 'customer_id' set to 'cust_42' as specified in the prompt.

Response: I choose the `database` tool with the method `list_orders`. The parameter object to send is:

```json
{
  "action": "list_orders",
  "customer_id": "cust_42"
}
```