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

53302

Output Tokens

5628

Duration

183626.217

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: Based on the operating principles, specifically the 'Scratch_pad protocol', I notice that the scratch_pad is missing updates for cycles 21-25. The operating principle clearly states that at every cycle, the scratch_pad must be updated. Since the scratch_pad is incomplete, the immediate action is to rectify this before proceeding with any other tasks.

Response: To rectify the missing updates for cycles 21-25, I would need to systematically update the scratch_pad with the key information from those cycles. This includes:

- Cycle 21: Drafted initial Markdown review (draft_review_351)
- Cycle 22: Uncertainty about architecture board sign-off, triggered user input request
- Cycle 23: Waiting for response
- Cycle 24: Received lead's approval with guidance to flag migration risks

The proper next step would be to use the memory tool to retrieve these details and comprehensively update the scratch_pad before continuing with the review process.