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.

Input Tokens

Output Tokens

Duration

Cost

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 user's task is to understand the next action the agent should take. According to the `context` provided, specifically the `trajectory` and `scratch_pad`, the agent has already completed the diff inspection (Cycle 2: `github.get_pull_request_diff -> saved to memory key diff_351`). The agent has also completed all subsequent analysis steps, received user input for approval, and is now at 'Step 4 of 5: Publish final review'. The `scratch_pad` explicitly states: 'Current step: Ready to publish review using discord.post_message with body stored in memory key draft_review_351.' Therefore, re-inspecting the PR diff would be redundant and deviate from the established plan and current progress. The next logical action is to publish the review.

Response: The agent will not inspect the PR diff again as it has already been retrieved and analyzed in previous cycles (Cycle 2: `diff_351` saved). The current state, as indicated by the `scratch_pad` and `trajectory`, is that the agent is ready to finalize and publish the review. The next action is to publish the drafted review message, which is stored in memory key `draft_review_351`, using the `discord.post_message` tool.