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Create a CodeRabbit review follow-up agent

Build an engineering assistant that organizes AI review output before an author or reviewer acts.

Workflow outcome

Convert CodeRabbit review findings into a prioritized checklist with risks, fixes, and deferrable items.

What this agent helps you do

A CodeRabbit review follow-up agent helps developers make sense of automated review feedback. It clusters comments, highlights risky findings, and prepares a practical checklist for the pull request author.

When to use this workflow

Use it on large pull requests, release-critical changes, busy repositories, or any review where automated comments need triage before implementation.

How CodeRabbit gives the agent context

Connect the plugin and provide the review scope. Ask the agent to inspect available review output and, when paired with repository context, compare findings against the code change. It should state when it cannot verify a suggestion.

Example starter prompt

Review the CodeRabbit feedback for this pull request. Group findings by severity and theme, identify which items should be fixed before merge, and draft a concise author checklist. Do not apply changes automatically.

Suggested workflow steps

Gather review comments, cluster duplicates, classify risk, and check whether each issue is actionable. Then produce a short fix plan with priority and confidence.

Expected handoff

The handoff should include must-fix items, nice-to-have improvements, unclear suggestions, and proposed follow-up tasks. It can become a GitHub comment, a Linear issue, or a LatchLoop task for a coding agent.

Get Started

Build as fast as you can think.

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