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.

Input Tokens

Output Tokens

Duration

Cost

Context

Input

After calling database.get_customer with customer_id 'CUST789', you received: {\"customer_id\":\"CUST789\",\"name\":\"Sarah Chen\",\"email\":\"sarah.chen@email.com\",\"account_status\":\"active\"}. You stored this with key 'customer_info'. Then database.list_orders with customer_id 'CUST789' returned: {\"orders\":[],\"message\":\"No orders found for customer\"}. You stored this with key 'customer_orders'. The customer claims they have an ongoing purchase needing address change. How should you handle this discrepancy and what is your next action?

Expected output

Reasoning: There's a discrepancy - customer claims ongoing purchase but 'customer_orders' shows no orders found. This could indicate: wrong customer ID, order under different account, or customer confusion. I need to gather more information before proceeding. Next action: Call email.draft_email to politely ask Sarah Chen to provide her order number or confirmation email, explaining we need to locate her order to assist with the address change.

Model output

Reasoning: The customer claims to have an ongoing purchase, but the database indicates no orders exist for this customer. This is a discrepancy that needs to be investigated. The immediate next step is to verify the customer's claim by asking for the order ID. This will allow me to check the database for that specific order.

Response: Ask the customer for the order ID to verify their purchase.