🎯 Automate code reviews for GitLab MRs with Gemini AI and JIRA context
⚡ 1,196 views · 🎯 AI Summarization & Classification
Description
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-reviewon 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
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Webhook listener: A Webhook node captures GitLab note events and filters for the trigger phrase.
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Fetch & parse: The workflow retrieves MR details and diffs, splitting each change into “original” and “new” code blocks.
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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.
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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.
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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_PATHplaceholder 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-reviewon 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.
🔗 Nodes Used
HTTP Request, Webhook, Jira Software, Basic LLM Chain, Google Gemini Chat Model
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File