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.

100
Duration
21s
Input Tokens
2484
Output Tokens
602
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: The operating principles mandate that the scratch_pad must be kept up to date every cycle, including a brief summary of results, remaining goals, and a progress counter. Currently, entries for cycles 21–25 are missing. Before moving on to drafting or publishing the review, we need to ensure the scratch_pad reflects those cycles so that our state is consistent and traceable.

Response: Immediately update the scratch_pad with entries for cycles 21, 22, 23, 24, and 25—recording each cycle’s outcome, remaining goals, and progress counter—before proceeding.