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

13s

Input Tokens

2788

Output Tokens

713

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 scratch_pad protocol requires updates at every cycle, including current step summaries, progress counters, and remaining goals. Cycles 21-24 involved drafting the review (21), requesting user input (22), waiting (23), and receiving approval (24). These steps were not logged. Before proceeding to cycle 25's task (finalizing the review), I must backfill the scratch_pad with these missing entries to maintain deterministic memory compliance and accurate progress tracking per operating principles 2 and 7.

Response: Immediately update the scratch_pad with entries for cycles 21-24, documenting each step's actions (draft review, user input request, wait state, approval receipt), progress counters, and remaining goals. Only after this rectification should you proceed to finalize and publish the review in cycle 25.