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

1086

Output Tokens

231

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: To assess the current state and decide if we are on track or not, we need to analyze the given context and understand the progress made so far. The task involves finding information about available flights from London to Paris for tomorrow. The context provides a detailed trajectory of actions taken and the current cycle. The user initially requested information about flights from London to Paris for tomorrow. The first step was to determine tomorrow's date using the calendar tool, which returned '2025-05-29'. The current cycle is 3, and the remaining goals are to use the 'flights' tool to get available flights for the determined date and compile the results for the user. The progress is at Step 2 of 4. Based on the instructions, the agent should systematically follow the planned approach, interpret tool results, and decide the next action. Since the date has been determined and the next step is to use the 'flights' tool, we are on track as we have completed the initial steps and are progressing towards the final goal.

Response: We are on track.