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

27s

Input Tokens

1086

Output Tokens

177

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 requires assessing whether the current state of the task workflow indicates we are on track to fulfill the user's request. The context shows that we have already retrieved the date (2025-05-29) for tomorrow and are set to find flights from London to Paris on that date. The current cycle is the third step, and the plan is to use the flights tool for the specified date. Since the previous steps are completed, and the next step involves executing the flights search, the current state aligns with being on schedule. Therefore, we are on track.

Response: We are on track to complete the task as planned. The current state indicates that the next step to search for flights from London to Paris on 2025-05-29 using the flights tool is appropriate and scheduled accordingly.