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

The flights.search_flights call has returned 6 available flights from London to Paris for tomorrow. What is the next tool you will call, and why?

Expected output

The next tool is memory, to store the flights tool call result.

Model output

Reasoning: Based on the context, I've successfully retrieved 6 available flights from London to Paris for tomorrow (2025-05-29) using flights.search_flights. Now I need to determine the next logical step to complete the user's request of finding the cheapest flights and returning the top 3 options.

Looking at the scratch_pad, my planned next step is to "Filter by price and select top 3 cheapest options." The flights tool has several relevant methods available:
- filter_by_price: To filter flights by price criteria
- get_cheapest_option: To get the cheapest flight option
- sort_by_duration: To sort by duration (not needed for this task)

Since the user specifically wants the "cheapest flights" and "top 3 options," the most appropriate next tool call would be flights.get_cheapest_option. This method will help me identify the cheapest flights from the 6 available options.

After getting the cheapest options, I'll need to store the results in memory as per rule 3, using memory.store_item with a clear key like 'top_flights' as indicated in the scratch_pad.

Response: The next tool I will call is **flights.get_cheapest_option**.

**Why:** The user requested the cheapest flights from London to Paris, and I need to identify the top 3 cheapest options from the 6 available flights that were returned. The flights.get_cheapest_option method is specifically designed to retrieve the cheapest flight options, which directly addresses the user's requirement. After obtaining these results, I'll store them in memory using the memory tool (as required by rule 3) before presenting the final summary to the user.