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

1082

Output Tokens

312

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 have reviewed the provided context and task to assess the current state and determine if we are on track. The user's request is to find information about available flights from London to Paris for tomorrow. The context indicates that we are in cycle 3 of the process. In the past trajectory, we identified the need to determine tomorrow's date and successfully used the calendar tool, which returned '2025-05-29'. The current step is to interpret this result and decide the next action. The remaining goals are to use the 'flights' tool to get available flights for the specified date and then compile and present the results to the user. Progress is noted as step 2 of 4, indicating we are midway through the process. The date format from the calendar tool matches the required format for the flights tool (YYYY-MM-DD), so no additional conversion is needed. Based on this analysis, we are on track as we have completed the initial step of obtaining the date and are ready to proceed to the next logical step of searching for flights. There are no deviations or issues in the workflow so far, and the plan aligns with the user's goal.

Response: We are on track. The date for tomorrow has been confirmed as '2025-05-29' using the calendar tool. The next step is to use the 'flights' tool to search for available flights from London to Paris on this date, followed by compiling and presenting the results to the user.