Opper

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.

Input Tokens

Output Tokens

Duration

Cost

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 explicitly require that at *every* cycle the scratch_pad be brought up to date with:  • the current step and a short result summary  • remaining goals  • notes / assumptions  • a progress counter (e.g. “Step 5 of 7”).  Because cycles 21-24 were executed but never recorded, our very next action in the Think-Plan-Act-Check loop must be to rectify the missing log before doing anything else.  Concretely, that means opening the scratch_pad and appending entries for cycles 21, 22, 23, 24 and the current cycle 25, summarising what happened in each and indicating the current remaining tasks (finalise review, post to Discord, mark complete).  Only after the scratch_pad is consistent with reality should we proceed with further review actions.

Response: Immediately update the scratch_pad with concise entries for cycles 21-25 (including current progress, results, remaining goals and the step counter) so that it accurately reflects the project state before taking any further action.