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

10s

Input Tokens

1140

Output Tokens

219

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: The user wants to assess the current state and determine if the task is on track. The context provided outlines the progress of a flight search task. The current state shows that the date for the flight search has been successfully retrieved using the calendar tool (2025-05-29). The remaining goals are to use the 'flights' tool to find flights from London to Paris for the retrieved date and then present the results. The current cycle is step 2 of 4, and the progress indicates we are moving towards the next logical step, which is using the flights tool. Therefore, we are on track to fulfill the user's initial request.

Response: We are on track. The calendar tool has successfully returned tomorrow's date as '2025-05-29'. The next step is to use the flights tool to search for flights from London to Paris for this date, and then compile and present the results to the user.