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

1148

Output Tokens

367

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: 1. The task is to assess progress, not to finish it. 2. The context indicates we are in cycle 3, step 2 of 4, with the calendar result obtained. 3. Remaining goals are clear: invoke flights tool, then present results. 4. No errors or blockers have been reported. 5. Therefore the workflow is on track and the immediate next action is to call the flights tool.

Response: We are on track. The calendar step has completed successfully, returning the correct date (2025‑05‑29). The next required action is to query the flights tool for available flights from London to Paris on that date, which will fulfill the remaining goal. The process is proceeding as planned and is on schedule.