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

1115

Output Tokens

215

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 task is to assess whether we are on track based on the current state. The user requested flight information from London to Paris for tomorrow. In the previous cycle, the calendar tool was used successfully to determine that tomorrow's date is '2025-05-29'. This date is in the correct YYYY-MM-DD format required by the flights tool. The next logical step is to use the flights tool with the parameters from_city='London', to_city='Paris', and date='2025-05-29'. Since this action aligns with the remaining goals and follows a systematic approach, we are on track. No deviations or issues have been encountered so far. The plan is progressing as expected.

Response: We are on track. The date for tomorrow has been correctly retrieved as 2025-05-29. The next step is to query the flights tool for available flights from London to Paris on that date.