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

2845

Output Tokens

188

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: The task requires inspecting the PR diff again for PR #351. From the trajectory and scratch_pad, the diff was already fetched in Cycle 2 and saved to memory under the key 'diff_351'. Following the operating principles, I must avoid redundant tool calls and instead use the memory tool to retrieve existing data deterministically. The high-level plan shows that the current step is to publish the review, but this request interrupts to re-inspect the diff, likely to verify something before finalizing. Therefore, the first action is to read the stored diff from memory to inspect it without re-fetching. After reading, I can analyze it as needed and proceed to update the review if necessary, but the immediate action is the memory read.

Response: Use the 'memory' tool with action 'read_memory' and key='diff_351' to retrieve and inspect the stored PR diff.