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

21s

Input Tokens

2677

Output Tokens

896

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: The high-level plan has 5 steps: 1) gather diff & CI outputs ✓, 2) security & style analysis ✓, 3) research dependency ✓, 4) publish review (current, cycle 25), 5) log completion (pending). We’re executing step 4 in cycle 25 and only need one more cycle to finish step 5. Therefore we remain on track with the plan and have only a few cycles left.

Response: less than 10 only few left