Opper

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.

Agents – cerebras/llama-4-maverick-17b-128e-instruct Task | Opper AI

Input Tokens

0

Output Tokens

0

Duration

0

Cost

0

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 is to inspect the PR diff again and determine the action to take. Based on the context provided, the agent is in cycle 25 and has already completed several steps in the review process, including gathering the diff, running tests and linting, performing security analysis, researching new dependencies, and drafting a review message. The current step is to publish the final review. The agent needs to use the 'github' tool to retrieve the PR diff again and verify its contents before proceeding to publish the review using 'discord.post_message' with the body stored in memory key 'draft_review_351'.

Response: To inspect the PR diff again, I will use the 'github.get_pull_request_diff' tool with the repo and PR number from the context. This will allow me to verify the diff contents before publishing the review.