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

17s

Input Tokens

4072

Output Tokens

299

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: 1. **Understand the Task**: The user requested to list all open orders for customer ID `cust_42`. The output must strictly adhere to the provided JSON schema, where the `response` field must be a string.

2. **Analyze the Requirements**: The task asks for two things:
   - Which tool/method to choose.
   - What parameter object to send.

   Both must be described in plain text within the `response` string, not as a structured object.

3. **Tool Selection**: The `database` tool is the correct choice because it includes the `list_orders` method, which is designed to retrieve orders for a given customer ID.

4. **Parameter Object**: The `list_orders` method requires:
   - `action`: `list_orders`
   - `customer_id`: `cust_42`

5. **Format the Response**: The final answer must be a clear, concise string describing the tool, method, and parameters.

Response: To list all open orders for customer ID `cust_42`, use the `database` tool with the `list_orders` method. The parameter object to send is: `{ "action": "list_orders", "customer_id": "cust_42" }`.