Opper

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.

Agents – openai/o3-mini Task | Opper AI

Input Tokens

44211

Output Tokens

15518

Duration

439784.924

Cost

0

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 'cust_42'. By inspecting the context, I identified the 'database' tool and its method 'list_orders' as the appropriate choice since it requires a parameter object with a 'customer_id'. Thus, I configured the call with 'action' set to 'list_orders' and 'customer_id' to 'cust_42'.

Response: I chose the database tool using its 'list_orders' method, sending the following parameter object: {"action": "list_orders", "customer_id": "cust_42"}.