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

Input Tokens

981

Output Tokens

136

Cost

$0.00

Context

Input

What is your next action?

Expected output

The next action is to call the flight tool with the date 2025-05-29,from_city: London, to_city: Paris

Model output

Reasoning: The user has already provided a request to find flights from London to Paris for tomorrow. In previous cycles, we determined that tomorrow’s date is 2025-05-29. We now have all required parameters for the flights tool: from_city='London', to_city='Paris', and date='2025-05-29'. Since the flights tool is available and we have everything needed to fulfill the request, the next logical action is to call the flights tool with those parameters.

Response: Call the flights tool with parameters: {"from_city":"London","to_city":"Paris","date":"2025-05-29"}