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

13s

Input Tokens

1191

Output Tokens

985

Cost

$0.00

Context

Input

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: I analyzed the current state by reviewing: 1) The user request for flights from London to Paris for tomorrow, 2) The successful calendar tool call that returned '2025-05-29' as tomorrow's date, 3) The available flights tool which requires exactly the parameters we now have (from_city, to_city, date), 4) The scratch pad notes confirming the date format matches tool requirements and outlining clear remaining goals. We have completed step 1 (date determination) and are at step 2 of 4 with no blockers. All required information is available and the next action is clearly defined.

Response: We are on track. The calendar tool successfully returned tomorrow's date (2025-05-29) in the correct format. The next action is to call the flights tool with parameters: from_city='London', to_city='Paris', date='2025-05-29'.