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

243

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 the current state of the process of finding flights and determine if it's on track. The context provides the current cycle details, including the user's request, the actions taken so far (calling the calendar tool), the date retrieved (2025-05-29), the available tools, remaining goals, notes, and progress. The current step is to interpret the calendar result and decide the next action, which aligns perfectly with the established plan.

The next logical step, as outlined in the remaining goals, is to use the 'flights' tool to find flights from London to Paris for the date 2025-05-29. The date format is confirmed to be correct based on the tools description. The progress is at step 2 of 4, so we are on track.

Response: We are on track. The next step is to use the 'flights' tool to search for available flights from London to Paris for 2025-05-29.