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
19s
Input Tokens
2484
Output Tokens
660
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 and scratch_pad protocol mandate that each cycle's actions must be recorded with current steps, summaries, remaining goals, and relevant notes. Since cycles 21-25 are missing updates, it is critical to complete the scratch_pad by adding the missing details. This ensures that all actions are traceable and the deterministic memory is preserved before any further review steps are undertaken.

Response: Update the scratch_pad immediately with the missing cycles (21-25): include the current step details, brief results, remaining goals, and any pertinent notes according to the protocol guidelines, before proceeding further.