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

2891

Output Tokens

648

Cost

$0.01

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: I reviewed the scratch_pad protocol in the provided instructions. To fix the missing updates, I must retroactively document the actions and outcomes of cycles 21 through 25 to maintain accurate tracking before finalizing the review.

Response: According to the 'Scratch_pad protocol' in the operating principles, you should immediately update the `scratch_pad` to include the missing records for cycles 21-25. This involves documenting the current step and brief summary of the result (drafting the review, requesting user input, waiting, receiving approval), the remaining goals (finalizing and publishing the review), any notes and assumptions, and the progress counter before taking the next action.