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

1038

Output Tokens

117

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 wants available flights from London to Paris for tomorrow. The trajectory shows tomorrow’s date has already been resolved via calendar tool as 2025-05-29. Therefore the next logical step is to query the flights tool with from_city=London, to_city=Paris, date=2025-05-29. This is the most direct action toward fulfilling the request.

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