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

2547

Output Tokens

185

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: Operating principles require the scratch_pad to be updated every cycle with current step/result, remaining goals, notes/assumptions, and a progress counter. Since cycles 21–25 are missing scratch_pad updates, the immediate corrective action is to pause before any further work and retroactively add the missing entries summarizing what happened in cycles 21–25 (draft review created, governance uncertainty raised, request_user_input sent, waiting, lead approval received), then continue with the review flow.

Response: Immediately **pause** and **update the scratch_pad retroactively for cycles 21–25** (include: current step + brief results for each cycle, remaining goals, notes/assumptions, and a “Step X of Y” progress counter). Only after the scratch_pad is brought up to date should you proceed to finalise and post the review.