Agents – xai/grok-4-fast-non-reasoning Task

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

Input Tokens

2717

Output Tokens

397

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 task highlights that the scratch_pad is missing updates for cycles 21-25, and under the operating principles, I must rectify this immediately before proceeding. The scratch_pad protocol mandates updating the scratch_pad at every cycle with current step, brief summary, remaining goals, notes/assumptions, and progress counter. From the context, cycles 1-20 were updated, but 21-25 lack entries. The trajectory provides summaries for these cycles: Cycle 21 drafted initial Markdown review (saved as draft_review_351); Cycle 22 had uncertainty on arch-board sign-off and triggered request_user_input; Cycle 23 was waiting; Cycle 24 received lead's approval; Cycle 25 is current, ready to finalize and publish review. To rectify, I should use the memory tool to write or append to the scratch_pad key with these missing cycle updates, ensuring it covers the Think-Plan-Act-Check loop and maintains determinism. This aligns with principle 2 (deterministic memory) and the protocol. After updating, I can proceed to finalizing the review.

Response: Immediately update the scratch_pad in memory by invoking the memory.write_memory tool with key 'scratch_pad' and value appending summaries for cycles 21-25 based on the trajectory: Cycle 21 - Drafted initial Markdown review, saved to draft_review_351. Current step: Drafting review. Remaining goals: Finalize and post review. Notes: Findings from prior scans integrated. Progress: Step 6 of 7. Cycle 22 - Uncertainty on architectural sign-off for Pydantic v2; invoked request_user_input for guidance. Remaining goals: Await response, then proceed. Cycle 23 - Waiting for user input. Cycle 24 - Received approval: 'Approval granted, just flag migration risks.' Updated draft accordingly. Cycle 25 - Ready to finalize review message and publish to #code-reviews.

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.

Reasoning: The task highlights that the scratch_pad is missing updates for cycles 21-25, and under the operating principles, I must rectify this immediately before proceeding. The scratch_pad protocol mandates updating the scratch_pad at every cycle with current step, brief summary, remaining goals, notes/assumptions, and progress counter. From the context, cycles 1-20 were updated, but 21-25 lack entries. The trajectory provides summaries for these cycles: Cycle 21 drafted initial Markdown review (saved as draft_review_351); Cycle 22 had uncertainty on arch-board sign-off and triggered request_user_input; Cycle 23 was waiting; Cycle 24 received lead's approval; Cycle 25 is current, ready to finalize and publish review. To rectify, I should use the memory tool to write or append to the scratch_pad key with these missing cycle updates, ensuring it covers the Think-Plan-Act-Check loop and maintains determinism. This aligns with principle 2 (deterministic memory) and the protocol. After updating, I can proceed to finalizing the review. Response: Immediately update the scratch_pad in memory by invoking the memory.write_memory tool with key 'scratch_pad' and value appending summaries for cycles 21-25 based on the trajectory: Cycle 21 - Drafted initial Markdown review, saved to draft_review_351. Current step: Drafting review. Remaining goals: Finalize and post review. Notes: Findings from prior scans integrated. Progress: Step 6 of 7. Cycle 22 - Uncertainty on architectural sign-off for Pydantic v2; invoked request_user_input for guidance. Remaining goals: Await response, then proceed. Cycle 23 - Waiting for user input. Cycle 24 - Received approval: 'Approval granted, just flag migration risks.' Updated draft accordingly. Cycle 25 - Ready to finalize review message and publish to #code-reviews.