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Automate Code Reviews for GitLab MRs with Gemini AI and JIRA Context

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Created by: Evgeny Agronsky || jenyok

Evgeny Agronsky

Last update

Last update 16 hours ago

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What it does

Automates code review by listening for a comment trigger on GitLab merge requests, summarising the diff, and using an LLM to post constructive, line‑specific feedback. If a JIRA ticket ID is found in the MR description, the ticket’s summary is used to inform the AI review.

Use cases

  • Quickly obtain high‑quality feedback on MRs without waiting for peers.
  • Highlight logic, security or performance issues that might slip through cursory reviews.
  • Incorporate project context by pulling in related JIRA ticket summaries.

Good to know

  • Triggered by commenting ai-review on a merge request.
  • The LLM returns only high‑value findings; if nothing critical is detected, the workflow posts an “all clear” message.
  • You can swap out the LLM (Gemini, OpenAI, etc.) or adjust the prompt to fit your team’s guidelines.
  • AI usage may incur costs or be geo‑restricted depending on your provider n8n.io.

How it works

  • Webhook listener: A Webhook node captures GitLab note events and filters for the trigger phrase.

  • Fetch & parse: The workflow retrieves MR details and diffs, splitting each change into “original” and “new” code blocks.

  • Optional JIRA context: If your MR description includes a JIRA key (e.g., PROJ-123), the workflow fetches the ticket (and parent ticket for subtasks) and composes a brief context summary.

  • LLM review: The parsed diff and optional context are sent to an LLM with instructions to identify logic, security or performance issues and suggest improvements.

  • Post results: Inline comments are posted back to the MR at the appropriate file/line positions; if no issues are found, a single “all clear” note is posted.

How to use

  • Import the template JSON and open the Webhook node. Replace the REPLACE_WITH_UNIQUE_PATH placeholder with your desired path and configure a GitLab project webhook to send MR comments to that URL.
  • Select your LLM credentials in the Gemini (or other LLM) node, and optionally add JIRA credentials in the JIRA nodes.
  • Activate the workflow and comment ai-review on any merge request to test it.
  • For each review, the workflow posts status updates (“AI review initiated…”) and final comments.

Requirements

  • A GitLab project with a generate Personal Access Token (PAT) stored as an environment variable (GITLAB_TOKEN).
  • LLM credentials (e.g., Google Gemini) and optional JIRA credentials.

Customising this workflow

  • Change the trigger phrase in the Trigger Phrase Filter node.
  • Modify the LLM prompt to focus on different aspects (e.g., style, documentation).
  • Filter out certain file types or directories before sending diffs to the LLM.
  • Integrate other services (Slack, email) to notify teams when reviews are complete.