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.

0
Duration
3s
Input Tokens
1284
Output Tokens
118
Cost
$0.00
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: The task is to find the cheapest flights from London to Paris for tomorrow and return the top 3 options. The flights.search_flights call has returned 6 available flights. The next logical step is to filter these flights by price to identify the cheapest options. The 'flights' tool has a method called 'filter_by_price' which can be used to achieve this. After filtering, we will select the top 3 cheapest flights and store them in memory.

Response: flights.filter_by_price