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

1264

Output Tokens

620

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 agent is currently on track to fulfill the user's request. The initial trigger was to find flights from London to Paris for 'tomorrow'. Since 'tomorrow' is a relative date, the agent correctly identified the need to determine the specific date first. It used the 'calendar' tool in the previous cycle, which returned '2025-05-29'. The scratch pad correctly identifies the next logical step: using the 'flights' tool with the parameters 'London', 'Paris', and '2025-05-29'. The workflow is proceeding logically, moving from data gathering (date) to the primary task (flight search).

Response: The task is currently on track. The agent has successfully determined the specific date for 'tomorrow' (2025-05-29) using the calendar tool and is now ready to proceed with the 'flights' tool to find available options from London to Paris as requested. No errors or unnecessary loops have occurred so far.