AI-Powered GitHub Commit Code Review Emailer - n8n Workflow

Use this comprehensive n8n workflow to automate code reviews. Triggered by GitHub push events, this n8n template utilizes the Groq AI model to analyze code diffs and instantly email a structured review summary via Gmail.

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Who is this best for?

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Software Development Teams requiring immediate feedback on new commits.
DevOps Engineers looking to integrate automated quality gates into their CI/CD pipelines using n8n.
Users of n8n who need an advanced example of combining webhooks, custom code, and large language models.
Technical leads seeking to monitor code quality across multiple repositories using a single n8n workflow.

Overview

Manual code review can be time-consuming and prone to human error. This n8n workflow solves this problem by creating an AI-driven, real-time code quality feedback loop. When a developer pushes code to a monitored GitHub repository, the n8n trigger instantly activates the automation. The workflow fetches the full commit details and passes the formatted code diff to an intelligent AI Agent using Groq. The agent analyzes functional issues, style, potential security flaws, and suggests improvements, returning a structured HTML summary. This entire process, managed by various n8n nodes, ensures rapid, consistent code feedback delivered directly to the reviewer's inbox via Gmail, making this one of the most useful n8n templates for modern teams.

How it Works

This powerful n8n workflow begins execution with the Github Trigger n8n node. This n8n trigger is configured to listen for 'push' events on a specific repository.


  1. Trigger & Data Parsing: When a push occurs, the Github Trigger captures the payload. The subsequent Parser n8n node extracts essential metadata (repo name, owner, commit ID).

  2. Fetching Commit Details: An HTTP Request n8n node then uses the commit ID to call the GitHub API, retrieving the detailed commit information, including the crucial patch/diff data.

  3. HTML Formatting (Code Node): A specialized Code n8n node takes the raw commit data and transforms it into a highly styled HTML output. This includes color-coding the code diff (green for additions, red for deletions) for optimal readability in an email client.

  4. AI Analysis (AI Agent Node): The AI Agent n8n node receives this formatted HTML. It is instructed via a strict system prompt to act as an expert code reviewer, focusing on functional, style, and security concerns. It utilizes the Groq Chat Model and a Simple Memory n8n node for processing, though the memory is optional for single-pass review.

  5. Output Combination: An Output Parser Code n8n node merges the original commit details (from the first Code node) and the strict HTML summary generated by the AI Agent.

  6. Final Notification: The finished HTML output is sent via the Gmail n8n node to the specified recipient (the reviewer or development team), completing the automated n8n workflow. The flow then concludes with the End Workflow n8n node.

Installation Guide

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  1. Importing the n8n template: Copy the provided JSON and paste it into your n8n instance using the 'New' menu -> 'Import from JSON'.

  2. GitHub Credentials: Set up credentials for the GitHub Trigger n8n node and the HTTP Request n8n node.

  3. Groq Setup: Configure the Groq Chat Model n8n node with your Groq API key.

  4. Github Trigger Configuration: Customize the repository URL and owner details in the Github Trigger n8n node to monitor your target project. Ensure the webhook is correctly set up in your GitHub repository settings to point to the n8n trigger URL.

  5. Gmail Setup: Configure the Gmail n8n node with your OAuth2 credentials. Update the sendTo parameter to the desired reviewer's email address.

  6. Activate: Save and activate the n8n workflow. It will now run automatically on every push event.

Node Details

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Github Trigger (n8n trigger):
Function: Starts the n8n workflow upon a 'push' event to a specific GitHub repository.
Key Configuration: Events set to push. Repository details must be manually updated to match your project.
HTTP Request (n8n node):
Function: Fetches detailed commit metadata, including file patches, using dynamic expressions referencing the commit ID provided by the n8n trigger data.
Key Configuration: Uses the GitHub OAuth2 credential type for secure API access. URL is dynamically generated to request commit data: =https://api.github.com/repos/{{ $json.body.repository.owner.name }}/.../commits/{{ $json.body.head_commit.id }}.
Code (Formatter n8n node):
Function: Transforms raw GitHub commit data (diffs) into color-coded, styled HTML for excellent email visualization. It separates added lines (+, green) and removed lines (-, red).
Key Configuration: Contains custom JavaScript logic (formatPatch and renderResponse) to structure metadata (repo info, author, message) and code diffs.
Groq Chat Model (n8n node):
Function: Provides the LLM backend for the AI Agent, utilizing the fast llama-3.1-8b-instant model for rapid code review generation.
Key Configuration: Requires a Groq API credential.
AI Agent (n8n node):
Function: Acts as the core intelligence. It takes the HTML-formatted code diff as input and generates a strict, structured code review based on the detailed prompt instructions.
Key Configuration: The system prompt forces the AI to check functional, style, security, and suggest improvements, and crucially, return its findings in one of two predefined HTML blocks.
Gmail (n8n node):
Function: Sends the final, combined HTML output (commit details + AI review) as an email notification.
Key Configuration: Subject is set to 'Code Review'. Message uses the final HTML output from the Output Parser n8n node.

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Updated: December 26 2025
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Created by

I'm a full stack developer passionate about building intelligent, scalable solutions that automate workflows and enhance productivity. I love working at the intersection of AI, APIs, and automation—using tools like n8n to streamline processes, integrate data, and unlock smarter decision-making. Whether it's crafting custom backend services or designing intuitive frontends, I’m always exploring ways to build more with less manual effort.

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