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

3046

Output Tokens

939

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: According to the provided instructions and operating principles, the agent must avoid redundant tool calls. Specifically, the 'Scratch_pad protocol' and general principles state that if a tool output has already been fetched and stored, the agent should check the memory instead of invoking the original tool again. The trajectory shows that the PR diff was fetched in Cycle 2 and saved to the memory key 'diff_351'. Therefore, to inspect the diff again, the agent should retrieve it from the deterministic long-term store using the memory tool.

Response: The agent should call the tool action memory.read_memory(key='diff_351') because the diff was already fetched in Cycle 2 and stored in memory, and the instructions explicitly forbid using a tool with the same inputs twice when the result is available in memory.