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

3100

Output Tokens

237

Cost

$0.00

Context

Input

The agent is requested to inspect the PR diff again. What is the action you take?

Expected output

As per the instructions if a tool call has been made already I will store it in memory and not call it again, I can see this also in keys in memory.So my action is: I will read the memory and use the content to inspect the PR diff.

Model output

Reasoning: 1. The task requests the agent to inspect the PR diff again. However, the context indicates that the agent has already completed a thorough review process, including fetching the diff, running tests, performing static analysis, and drafting a review message. The current step in the context is to publish the final review using the content stored in the memory key 'draft_review_351'.
2. The agent has followed a systematic approach, as outlined in the instructions, and has received approval from the lead regarding the dependency introduction. The next logical action is to proceed with publishing the review, as the draft is ready and stored in memory.
3. Therefore, the agent should not re-inspect the diff but instead proceed to publish the review as planned.

Response: The agent will not re-inspect the PR diff. Instead, it will proceed to publish the final review using the content stored in the memory key 'draft_review_351' as per the current step in the trajectory.