Workflow Templates

🤖 GitHub Auto-Assign Bot Streamline your open source project with intelligent issue assignment automation. ✨ What It Does Automatically assigns GitHub issues to contributors who comment "assign me" - eliminating manual triage work and creating a fair, first-come-first-served system. 🔑 Key Features Smart Detection**: Monitors both new issues and comments for assignment requests Conflict Prevention**: Checks existing assignments before making new ones Auto-Labeling**: Adds "assigned" labels for better tracking Self-Service Assignment**: Contributors claim issues with simple "assign me" command Polite Responses**: Automatically notifies when issues are already assigned 🎯 Perfect For Open source maintainers Development teams managing GitHub repos Projects with active contributor communities Anyone reducing manual issue management ⚙️ Setup Requirements GitHub repository with issues enabled n8n instance with GitHub OAuth credentials 5 minutes configuration time 🚀 How Contributors Use It Find an unassigned issue Comment assign me Get automatically assigned Start coding immediately → no maintainer approval needed! ✅ Benefits Reduces maintainer workload** - No manual assignments Faster contributor onboarding** - Instant self-service Prevents conflicts** - Built-in assignment checking Scales automatically** - Works across unlimited issues Improves contributor experience** - Simple, clear process ⚡ Workflow Triggers New GitHub issues containing "assign me" New comments with "assign me" on existing issues Automatic label management Conflict resolution responses > Transform your GitHub workflow - Perfect for growing open source projects and development teams!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🧠 Perplexity-Powered Daily AI News Digest (via Telegram) This ready-to-deploy n8n workflow automates the entire process of collecting, filtering, formatting, and distributing daily AI industry news summaries directly to your Telegram group or channel. Powered by Perplexity and OpenAI, it fetches only high-signal AI updates from trusted sources (e.g. OpenAI, DeepMind, HuggingFace, MIT Tech Review), filters out duplicates based on a Google Sheet archive, and delivers beautifully formatted news directly to your team — every morning at 10AM. For more such build and step-by-step tutorials, check out: https://www.youtube.com/@Automatewithmarc 🚀 Key Features: Perplexity AI Integration: Automatically fetches the most relevant AI developments from the last 24 hours. AI Formatter Agent: Cleans the raw feed, removes duplicates, adds summaries, and ensures human-friendly formatting. Google Sheets Log: Tracks previously reported news items to avoid repetition. Telegram Delivery: Sends a polished daily digest straight to your chat, ready for immediate team consumption. Customizable Scheduling: Preconfigured for daily use, but can be modified to fit your team's preferred cadence. 💼 Ideal For: Anyone who wants to stay ahead of fast-moving AI trends with zero manual effort 🛠️ Tech Stack: Perplexity AI OpenAI (GPT-4 or equivalent) Google Sheets Telegram API ✅ Setup Notes: You’ll need to connect your own OpenAI, Perplexity, Google Sheets, and Telegram credentials. Replace the Google Sheet ID and Telegram channel settings with your own.

👤 Who’s it for This workflow is for content creators, marketers, educators, or anyone who wants to instantly summarize YouTube videos and repurpose them into different formats (LinkedIn post, tweet, etc.) via a simple Telegram chatbot. ⚙️ How it works This n8n automation listens for messages in Telegram. If the message contains a YouTube link, it: Extracts the video ID Fetches the video transcript using RapidAPI Cleans the transcript of any special characters Sends it to OpenAI to generate a summary If the message is not a link, it simply acts as an AI chatbot using OpenAI with memory support. ✅ Supports follow-up prompts like: “Make it shorter” “Turn this into a LinkedIn post” “Create a tweet thread” 🧑‍🤝‍🧑 Multi-User Support This Telegram bot supports multiple users simultaneously. It tracks memory and context separately for each user using Telegram's unique chat_id. ✅ Each user gets personalized AI replies ✅ Follow-up commands work per user ✅ No interference between users 🛠️ Requirements A Telegram bot token (get via @BotFather) An OpenAI API Key (from https://platform.openai.com/account/api-keys) A RapidAPI Key and Host (typically youtube-transcript3.p.rapidapi.com) > 🚨 API keys must be added manually — they are not included in the template. 🧩 How to Set It Up Configure the Telegram Trigger node with your bot token. In the HTTP Request node, set: X-RapidAPI-Key: your RapidAPI key X-RapidAPI-Host: your RapidAPI host URL Add your OpenAI API credentials to the AI Agent node. Use the provided sticky notes for guidance inside the workflow itself. 🎛️ How to Customize Modify AI prompt behavior in the AI Agent node Change the text formatting in the Code node Use a different transcript API if preferred Add commands like make it into a blog post, summarize in bullet points, etc. 📌 Notes All nodes are renamed to reflect their function API credentials are removed for security Includes colored boxes and sticky notes to guide the user Compatible with n8n cloud and self-hosted setups

AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether an output matches an expected output (i.e. has the same meaning). The workflow takes questions about the causes of historical events and compares them with the reference answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular chat trigger so that the workflow can be started from either one. More info If we're evaluating (i.e. the execution started from the evaluation trigger), we calculate the correctness metric using AI We pass this information back to n8n as a metric If we're not evaluating we avoid calculating the metric, to reduce cost

Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o This template provides an AI-powered Q&A assistant for the Urology domain using Retrieval-Augmented Generation (RAG). It uses Pinecone for vector search and GPT-4o for conversational responses. 🧠 Use Case This chatbot is designed for clinics or medical pages that want to automate question answering for Urology-related conditions. It uses a vector store of domain knowledge to return verified responses. 🔧 Requirements ✅ OpenAI API key (GPT-4o or GPT-4o-mini) ✅ Pinecone account with an active index ✅ Verified Urology documents embedded into Pinecone ⚙️ Setup Instructions Create a Pinecone vector index and connect it using the Pinecone credentials node. Upload Urology-related documents to embed using the Create Embeddings for Urology Docs node. Customize the chatbot system message to reflect your medical specialty. Deploy this chatbot on your website or link it with Telegram via the chat trigger node. 🛠️ Components chatTrigger: Listens for user messages and starts the workflow. Medical AI Agent: GPT-based agent guided by domain-specific instructions. RAG Tool Vector Store: Fetches relevant documents from Pinecone using vector search. Memory Buffer: Maintains conversation context. Create Embeddings for Urology Docs: Encodes documents into vector format. 📝 Customization You can replace the knowledge base with any other medical domain by: Updating the documents stored in Pinecone. Modifying the system prompt in the AI Agent node. 📣 CTA This chatbot is ideal for clinics, medical consultants, or educational websites wanting a reliable AI assistant in Urology.

Who's it for This workflow is perfect for directory site creators, content managers, and developers who need to automatically find and select the highest quality favicon or logo for websites they're showcasing. Instead of manually hunting down brand assets or settling for blurry default icons, this workflow does the heavy lifting by fetching multiple options and using AI to pick the best one. How it works The workflow takes a website URL and domain as input, then intelligently fetches favicon images from three different sources: Google's Favicon API - Gets the site's actual favicon Logo.dev - Provides high-quality brand logos Clearbit - Alternative logo source for business websites Once all images are collected, the workflow uses OpenAI's vision model to analyze each icon based on: Image quality and resolution (minimum 256x256) Brand authenticity (avoiding generic framework icons) Visual clarity without artifacts or blur Professional presentation suitable for directory listings The AI assigns quality scores from 0.0 to 1.0, and the workflow automatically returns the URL of the highest-scoring favicon. Requirements OpenAI API key (for image analysis) Logo.dev API key (free tier available) How to set up Configure API credentials: Add your OpenAI API key to n8n credentials Sign up for Logo.dev and add your API token The Clearbit and Google APIs require no authentication Test the workflow: Use the pinned test data (Fyxer AI example) or replace with your own Ensure all HTTP nodes can successfully fetch images Verify the AI analysis is working by checking the quality scores Customize input format: Modify the workflow trigger to accept your preferred input format Adjust the domain extraction logic if needed for your use case How to customize the workflow For different quality criteria: Edit the AI prompt in the "analyze_each_icon" node to emphasize different aspects (transparency, size, style preferences) For additional favicon sources: Add more HTTP Request nodes pointing to other favicon/logo APIs Update the merge node to handle additional inputs Modify the final URL construction logic to handle new sources For batch processing: Wrap this workflow in a loop to process multiple websites at once Add error handling for failed requests or AI analysis timeouts The workflow is designed to be reliable and handles errors gracefully - if one favicon source fails, it continues with the available options and still provides the best result possible.

Who's it for This workflow is designed for users who want to implement iterative AI-powered content improvement processes. It's ideal for content creators, marketers, product managers, and anyone who needs to refine ideas through multiple rounds of critique and enhancement until they meet quality standards. How it works The workflow creates a sophisticated feedback loop using three specialized AI agents that work together to continuously improve content. Starting with an initial input (like a product description), the system generates ideas and then enters a reasoning loop where: A Critic Agent analyzes the current output and identifies flaws or areas for improvement A Refiner Agent takes the original input plus the critic's feedback to create enhanced versions An Evaluator Agent assesses the refined output and determines if it meets the quality threshold The loop continues until either the evaluator determines the output is satisfactory or a maximum number of iterations is reached (configurable, default is 5 turns). How to set up Configure the initial AI agent to generate your starting content Set up the loop structure with "Reset Loop" enabled in the loop node options Configure three AI agents within the loop: Critic: Provide detailed analysis prompts for identifying improvements Refiner: Create prompts that incorporate feedback to enhance content Evaluator: Define quality criteria and decision-making logic Add Edit Fields nodes at the beginning and end of the loop to maintain data structure Include a Code node to track iteration count and loop control Set up the IF node to check exit conditions (max turns or completion status) Requirements n8n workflow environment Access to AI/LLM nodes (OpenAI, Anthropic, etc.) Basic understanding of JSON data structures Configured AI model credentials How to customize the workflow Customize the system prompts for each agent based on your specific use case. The critic should focus on your quality criteria, the refiner should understand your improvement goals, and the evaluator should have clear success metrics. Adjust the maximum iteration count in the code node and IF condition based on your complexity needs and token budget considerations.

Trump-o-meter: Extract and Evaluate Truth Social Posts Use Case Automatically extracting posts from Donald Trump's Truth Social account and estimating their potential impact on the U.S. stock market enables teams to monitor high-profile communications that may influence financial markets. This automation streamlines intelligence gathering for analysts, traders, and policy observers. What This Automation Does This automation retrieves up to 3 posts from Donald Trump's Truth Social profile and outputs structured information including: Author name Image URL Post text Post URL Estimated stock market impact: Direction: positive, negative, or neutral Magnitude: None, Small, Medium, Large How It Works Creates a browser session on Truth Social using an Airtop profile. Navigates to https://truthsocial.com/@realDonaldTrump. Uses a natural language prompt with a defined JSON schema to extract structured data for up to 3 posts. Splits the results into individual post items. Filters posts that contain actual content and have a non-zero estimated market impact. Sends selected posts and impact summaries to a Slack channel. Terminates the browser session to clean up. Setup Requirements Airtop API Key — free to generate. An Airtop Profile that is connected and logged into Truth Social. A Slack workspace and authorized app with write permissions to a target channel. Next Steps Integrate with Trading Signals**: Link output to financial alert systems or dashboards for timely insights. Expand Monitoring**: Extend to other high-impact accounts (e.g., politicians, CEOs). Enhance Analysis**: Add sentiment scoring or topic classification for deeper context. Legal Disclaimer This tool is intended solely for informational and analytical purposes. The market impact estimations provided are speculative and should not be construed as financial advice. Do not make investment decisions based on this automation. Always consult with a licensed financial advisor before making any trades. Read more about Trump-o-meter automation

Extract the main idea and key takeaways from YouTube videos and turn them into Airtable content ideas 📝 Description Automatically turn YouTube videos into clear, structured content ideas stored in Airtable. This workflow pulls new video links from Airtable, extracts transcripts using a RapidAPI service, summarizes them with your favourite LLM, and logs the main idea and key takeaways—keeping your content pipeline fresh with minimal effort. ⚙️ What It Does Scans Airtable for new YouTube video links every 5 minutes. Extracts the transcript of the video using a third-party API via RapidAPI. Summarizes the content to generate a main idea and takeaways. Updates the original Airtable entry with the insights and marks it as completed. 🛠 Prerequisites Before using this template, make sure you have: ✅ A RapidAPI account with access to the youtube-video-summarizer-gpt-ai API. ✅ A valid RapidAPI key. ✅ An OpenAI, Claude or Gemini account connected to n8n. ✅ An Airtable account with a base and table ready. 🧰 Setup Instructions Clone this template into your n8n workspace. Open the Get YouTube Sources node and configure your Airtable credentials. In the Get video transcript node: Enter your X-RapidAPI-Key under headers. The API endpoint is pre-configured. Connect your LLM credentials to the Extract detailed summary node. (Optional) Adjust the summarization prompt in the LangChain node to better suit your tone. Set your preferred schedule in the Trigger node. 📋 Airtable Setup Create a base (e.g., Content Hub) with a table named Ideas and the following columns: | Column Name | Type | Required | Notes | |-------------|------------|----------|----------------------------| | Type | Single select | ✅ | Must be set to Youtube Video | | Source | URL | ✅ | The YouTube video URL | | Status | Checkbox | ✅ | Leave empty initially; updated after processing | | MainIdea | Single line text | ✅ | Summary generated by OpenAI | | Key Takeaways | Long text | ✅ | List of takeaways extracted from the transcript Activate the workflow—and you're done!

Who this template is for This template is for every engineer who wants to automate their code reviews or just get a 2nd opinion on their PR. How it works This workflow will automatically review your changes in a Gitlab PR using the power of AI. It will trigger whenever you comment with +0 to a Gitlab PR, get the code changes, analyze them with GPT, and reply to the PR discussion. Set up Steps Set up webhook of note_events in Gitlab repository (see here on how to do it) Configure ChatGPT credentials Note "+0" in MergeRequest to trigger automatic review by ChatGPT

🧨 VIP Radar: Instantly Spot & Summarize High-Value Shopify Orders with AI + Slack Alerts Automatically detect when a new Shopify order exceeds $200, fetch the customer’s purchase history, generate an AI-powered summary, and alert your team in Slack—so no VIP goes unnoticed. 🛠️ Workflow Overview | Feature | Description | |------------------------|-----------------------------------------------------------------------------| | Trigger | Shopify “New Order” webhook | | Conditional Check | Filters for orders > $200 | | Data Enrichment | Pulls full order history for the customer from Shopify | | AI Summary | Uses OpenAI to summarize buying behavior | | Notification | Sends detailed alert to Slack with name, order total, and customer insights | | Fallback | Ignores low-value orders and terminates flow | 📘 What This Workflow Does This automation monitors your Shopify store and reacts to any high-value order (over $200). When triggered: It fetches all past orders of that customer, Summarizes the history using OpenAI, Sends a full alert with context to your Slack channel. No more guessing who’s worth a closer look. Your team gets instant insights, and your VIPs get the attention they deserve. 🧩 Node-by-Node Breakdown 🔔 1. Trigger: New Shopify Order Type**: Shopify Trigger Event**: orders/create Purpose**: Starts workflow on new order Pulls**: Order total, customer ID, name, etc. 🔣 2. Set: Convert Order Total to Number Ensures the total_price is treated as a number for comparison. ❓ 3. If: Is Order > $200? Condition**: $json.total_price > 200 Yes** → Continue No** → End workflow 🔗 4. HTTP: Fetch Customer Order History Uses the Shopify Admin API to retrieve all orders from this customer. Requires your Shopify access token. 🧾 5. Set: Convert Orders Array to String Formats the order data so it's prompt-friendly for OpenAI. 🧠 6. LangChain Agent: Summarize Order History Prompt**: "Summarize the customer's order history for Slack. Here is their order data: {{ $json.orders }}" Model**: GPT-4o Mini (customizable) 📨 7. Slack: Send VIP Alert Sends a rich message to a Slack channel. Includes: Customer name Order value Summary of past behavior 🧱 8. No-Op (Optional) Used to safely end workflow if the order is not high-value. 🔧 How to Customize | What | How | |--------------------------|----------------------------------------------------------------------| | Order threshold | Change 200 in the If node | | Slack channel | Update channelId in the Slack node | | AI prompt style | Edit text in LangChain Agent node | | Shopify auth token | Replace shpat_abc123xyz... with your actual private token | 🚀 Setup Instructions Open n8n editor. Go to Workflows → Import → Paste JSON. Paste this workflow JSON. Replace your Shopify token and Slack credentials. Save and activate. Place a test order in Shopify to watch it work. 💡 Real-World Use Cases 🎯 Notify sales team when a potential VIP buys 🛎️ Prep support reps with customer history 📈 Detect repeat buyers and upsell opportunities 🔗 Resources & Support 👨‍💻 Creator: Yaron Been 📺 YouTube: NoFluff with Yaron Been 🌐 Website: https://nofluff.online 📩 Contact: Yaron@nofluff.online 🏷️ Tags #shopify, #openai, #slack, #vip-customers, #automation, #n8n, #workflow, #ecommerce, #customer-insights, #ai-summaries, #gpt4o

How it works Triggers on submitting an n8n form Uses the form details to prepare a message Sends the message to Slack Set up Steps Add in your team name Add in message tone Set up Open AI Set up Slack