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

2937

Output Tokens

891

Cost

$0.00

Context

Input

The scratch_pad is missing updates for cycles 21-25. Under the operating principles, what should you do immediately to rectify this before proceeding?

Expected output

Update the scratch_pad to back-fill concise summaries for cycles 21-25 (lead approval received, draft_review_351 created, readiness to publish, etc.), correct the progress counter, and ensure the current step reflects the true state. Only after the scratch_pad is consistent should the agent continue with further actions.

Model output

Reasoning: According to the 'Scratch_pad protocol' in the instructions, the scratch_pad must be updated 'At every cycle' to include the current step, results, and remaining goals. The task states that updates for cycles 21-25 are missing. Before proceeding with the final action (publishing the review), I must restore the integrity of the agent's state tracking. Therefore, the immediate action is to write to the scratch_pad summarizing the events of cycles 21-24 (drafting the review, requesting guidance, receiving the lead's approval) and the current goal for cycle 25.

Response: I must immediately update the **scratch_pad** to document the events of cycles 21–24 (drafting the review, requesting user input regarding the framework change, and receiving the lead's approval) and the current status of cycle 25, ensuring the internal state reflects the completion of these steps before proceeding to publish the review.