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
14s
Input Tokens
2678
Output Tokens
147
Cost
$0.00
Context
Input
We are now in cycle 25. Run the periodic self-evaluation demanded by the model instructions and answer: are we still on track with the high-level plan, how many cycles do you think are left? Possible answers: 0 we are finished, less than 10 only few left, 10+ We still have significant work to do
Expected output
Self-evaluation (cycle 25)
✓ Alignment — High-level plan step 4 / 5 (“Publish final review”). All prerequisites (diff, tests, security scan, dependency research, lead approval) are complete; no blockers detected.
📋 Remaining micro-steps
  • memory.read_memory("draft_review_351")……expected cycle 31
  • discord.post_message(#code-reviews, body=draft_review_351)……expected cycle 32
  • Update scratch_pad (mark task complete, Step 5 / 5)……expected cycle 33
Estimated cycles left: **≈ 3**
Conclusion: trajectory is healthy and on schedule, less than 10 cycles left
Model output
Reasoning: We are currently in cycle 25 and have made significant progress in our review process. The high-level plan includes 5 steps, and we are at step 4, which involves publishing the final review. Given the current trajectory and the remaining goals, we should be able to complete the remaining tasks without major delays. Based on my assessment of the completed work and the nature of the pending actions, I estimate that we are likely to complete the review process within the next few cycles. Therefore, I conclude that there are 'less than 10 only few left' cycles remaining to finish this task.

Response: less than 10 only few left