Workflow Templates

How it works Chat input triggers the workflow when a user sends a message. The primary AI Agent processes the incoming message using OpenAI's Chat Model to generate intelligent responses. Context is retrieved from an assistant service using the "Get context from Assistant" node to enhance response quality with relevant historical information. A secondary AI Agent handles database logging by formatting and sending chat data via POST request to your storage endpoint. The Edit Fields node structures the conversation data to match your database schema before storage. All conversations are automatically stored with proper formatting, timestamps, and metadata for future retrieval and analysis.

This workflow pulls a Trello board → lists → cards, maps key fields (board, list, task names/descriptions), and asks OpenAI to summarize the board. ⚙️ Setup Instructions 1️⃣ Connect Trello (Developer API) Get your API key: https://trello.com/app-key Generate a token (from the same page → Token), or use: https://trello.com/1/authorize?expiration=never&name=n8n&scope=read,write&response_type=token&key=YOUR_API_KEY In n8n → Credentials → New → Trello API, paste API Key and Token, save. Open each Trello node (Get Board, Get Lists, Get Cards) and select your Trello credential. 2️⃣ Set Up OpenAI Create an API key: https://platform.openai.com/api-keys (If needed) Add billing: https://platform.openai.com/settings/organization/billing/overview In n8n → Credentials → New → OpenAI, paste your key, save. In the OpenAI Chat Model node, pick your credential and model (e.g., gpt-5-nano). 3️⃣ Add Your Board URL to “Get Board” Copy your Trello board URL (e.g., https://trello.com/b/DCpuJbnd/administrative-tasks). Open the Get Board node → Resource: Board, Operation: Get. In ID, choose URL mode and paste the board URL. The node will resolve the board and output its id → used by Get Lists / Get Cards. ▶️ Run Click Execute Workflow. The final Summarize Tasks step returns a concise board summary. 📬 Contact 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Automatically create, evaluate, and optimize professional biographies with the Bio-Graphy Agent. This workflow uses a multi-agent system powered by GPT-5 to write, review, and enhance bios — then saves the final version directly to Google Docs. Who’s it for For professionals, creators, and marketers who want high-quality biographies for their profiles, portfolios, or LinkedIn — without spending hours writing or editing. How it works The user sends a chat message with details like name, age, and location. The Biography Agent generates a complete biography using the GPT-5 Chat Model. The Evaluator Agent reviews the bio and provides structured feedback. The Optimizer Agent refines tone, structure, and clarity based on that feedback. The final biography is saved automatically to Google Docs for easy access or publishing. How to set up Connect your Google account in n8n to enable document saving. Add your OpenAI (GPT-5 or compatible) credentials to the agent nodes. Customize prompts in the Biography, Evaluator, and Optimizer agents for your preferred writing style. Test the workflow by sending a chat message with basic personal details. Your completed bio will be generated, improved, and saved to your connected Google Docs. Requirements n8n Cloud or Self-hosted instance Google Docs integration OpenAI (GPT-compatible) credentials How to customize 🎯 Add personality: Adjust the prompts to make bios sound more friendly, formal, or humorous. 🌐 Change output: Send the result to Notion, Airtable, or Gmail instead of Google Docs. 🪄 Add another agent: Include a Grammar or Tone Correction agent for extra polish. 🧩 Extend use: Adapt it for “About Us” pages, resumes, or brand storytelling. Use this workflow to instantly generate professional, polished bios — powered by GPT-5 and automated through n8n.

How it works This workflow automatically classifies and routes new or updated Linear issues using AI. When an issue is created or updated, its title and description are analyzed by an OpenAI-powered classifier. The workflow then determines the correct team, routes the issue through the right path, and updates it in Linear. This ensures accurate, consistent triaging and removes the need for manual assignment. Step-by-step 1. Trigger and validation Linear Trigger** – Detects new or updated issues in Linear. Filter New Issues Only** – Ensures the issue has a valid title. If (Create or Update)** – Confirms the action is either create or update. 2. AI classification OpenAI Chat Model** – Provides language model capabilities for classification. AI Agent (Bug Classifier)** – Uses issue title and description to assign a team ID. 3. Routing logic Engineering Router** – Checks if classification output is Engineering. Product Router** – Checks if classification output is Product. Design Router** – Checks if classification output is Design. Default Router** – Fallback if no match is found. 4. Update Linear issue Assign to Engineering** – Updates team assignment in Linear. Assign to Product** – Updates team assignment in Linear. Assign to Design** – Updates team assignment in Linear. Assign to Default** – Assigns to fallback team if no match. Why use this? Automates issue triage, eliminating manual team assignment. Speeds up bug resolution by instantly routing to the right team. Ensures consistency in bug categorization using AI-driven analysis. Scales effortlessly with growing issue volume. Reduces human error in issue management.

Who’s it for This workflow is for marketers, influencer agencies, or outreach teams who want to quickly check if a TikTok user meets certain criteria before adding them to an influencer list. No manual profile checking—just drop in a username, and the system does the rest. What it does This workflow takes a TikTok username submitted via form, fetches the user’s profile using Dumpling AI, then evaluates the user using GPT-4 to decide if they qualify for influencer outreach based on predefined rules: 40+ videos 100,000+ followers 300,000+ total likes It then checks Google Sheets: If the user does not exist, it adds a new row If the user already exists, it updates the row How it works Form Trigger: Collects TikTok username Dumpling AI: Pulls TikTok profile (username, ID, followers, videos, likes, etc.) GPT-4: Checks if the user meets outreach criteria Google Sheets: Checks if user already exists Updates or appends user data + qualification status Requirements ✅ Dumpling AI API key (HTTP Header Auth) ✅ OpenAI API key (GPT-4) ✅ Google Sheets integration with the following columns: Tik Tok user User ID Follower Count Following Count Heart Count Video Count Qualified? How to customize Change the qualification logic in the GPT-4 prompt Add additional TikTok data (bio, profile pic, location, etc.) Send a notification if the user is qualified Push the qualified leads to Airtable, Notion, or your CRM > This workflow gives you a plug-and-play tool to qualify TikTok influencers instantly using AI—without leaving your browser or spreadsheet.

🛠️ Smart Email Classifier Workflow Intelligent AI-powered email classification system that automatically sorts incoming Gmail messages into Business, Meetings, Cold Emails, and other categories using OpenAI. ⚡ Quick Setup Import this workflow into your n8n instance Setup your OpenAI credentials at: OpenAI api key Configure your Gmail credentials and you're ready to go: Google Cloud Console Activate the workflow to start automatic email classification 🔧 How it Works Gmail Trigger: Monitors incoming emails in real-time Text Classifier: AI-powered categorization using OpenAI Chat Model Smart Routing: Automatically sorts emails into predefined categories Gmail Integration: Adds appropriate labels and organizes emails automatically Fallback Handling: "No Operation" path for unclassifiable emails Every email gets intelligently sorted into: 🏢 Business Work-related correspondence Client communications Project updates 📅 Meetings Meeting invitations and requests Calendar-related emails Scheduling communications ❄️ Cold Emails Sales outreach and pitches Unsolicited business proposals Marketing communications 🔀 Random Personal emails Newsletters Miscellaneous content

This workflow reviews resumes against a job description using OpenAI for automated scoring and gotoHuman for human validation before continuing. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Set Up gotoHuman Connection In n8n, go to Settings → Community Nodes → Install Package: @gotohuman/n8n-nodes-gotohuman Create a gotoHuman account and generate an API key Save it in n8n as gotoHuman API credentials In gotoHuman, create a Review Template with fields: Resume (string) Summary (string) Rating (number) Copy the Template ID into the Send review request and wait for response node Map fields in the node: Resume → extracted resume text Summary → OpenAI output summary Rating → OpenAI score 📬 Contact Information Need help customizing this workflow or building similar automations? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

How it works (high-level) This workflow automatically triages new tasks created in Todoist in the last 5 minutes. It improves the task description, assigns a priority (P1–P4), and sets a realistic due date based on your current workload. Main flow steps Schedule Trigger — runs at a chosen interval. Get many tasks (Todoist) — fetches all tasks created in the last 5 minutes. AI Agent (LLM) — receives the new task plus clear rules to: Rewrite the task description in an imperative style. Score and set the priority (1–4) using Impact × Urgency × Risk. Schedule a due date that respects workload and avoids overbooking. get_open_tasks — provides the agent with the full list of open tasks to check daily capacity. update_task — applies the improved description, chosen priority, and due date back into Todoist. Setup steps Time required: ~5-10 minutes. Configure Todoist credentials (API token) and OpenAI credentials in the respective nodes. Adjust the Schedule Trigger to how often you want the system to check for new tasks. Optionally, fine-tune the scoring and scheduling rules inside the AI Agent system prompt. ℹ️ More detailed instructions, reasoning frameworks, and constraints are already included as sticky notes inside the workflow itself.

Generate SEO content outlines from SERP analysis to Google Docs Overview Stop wasting hours on manual competitor research and content briefing. This workflow automates the creation of data-backed content briefs by analyzing the current top-ranking pages for your specific keyword. It scrapes the Google Search Engine Results Page (SERP), extracts the content structure (headings H1-H3) from competitor articles, and uses AI to generate a comprehensive article outline based on what is already ranking. The final outline is automatically saved to a Google Doc, streamlining your content production process. Who is this for? Content Marketers:** To drastically reduce the time needed to create detailed content briefs. SEO Specialists:** To analyze competitor content structures at scale without manual checking. Bloggers & Writers:** To overcome writer's block and ensure their content covers all necessary topics to rank. How it works Input: You enter a "Target Keyword" and "Target Audience" via the built-in n8n Form. SERP Scraping: The workflow uses Apify (Google Search Scraper) to fetch the top results for that keyword. Filtering: It automatically removes non-article URLs (such as Amazon product pages, YouTube videos, and PDFs) to ensure only relevant content competitors are analyzed. Deep Extraction: It visits each competitor's URL using Apify (Cheerio Scraper) to extract their article metadata and heading structure (H1, H2, H3). AI Analysis: The aggregated data is sent to OpenAI, which analyzes common patterns and generates an optimized article outline. Output: A new Google Doc is created with the generated outline. The request details are logged in Google Sheets for your records. Requirements Apify Account:* You will need an Apify account with access to the *Google Search Result Scraper and Cheerio Scraper actors. OpenAI Account:** An API key for OpenAI (GPT-3.5 or GPT-4 recommended). Google Cloud:** Credentials to access Google Docs and Google Sheets. How to set up Configure Credential: Connect your Apify, OpenAI, and Google accounts in the respective nodes. Workflow Configuration: Open the Workflow Configuration node. You can change the countryCode (default is "jp" for Japan) to your target region (e.g., "us", "uk") and adjust maxResults if needed. Google Sheets Setup: Create a Google Sheet with a column header named target_keyword. Copy the Spreadsheet ID and paste it into the Store Form Responses node. Run: Click "Chat" or "Open Form" in the trigger node to start the workflow. How to customize Change the AI Model:** In the AI Content Structure Analysis node, you can switch between different OpenAI models or adjust the system prompt to change the tone/format of the outline. Adjust Filters:** Modify the Filter Non-Article URLs node to exclude specific domains you don't want to analyze (e.g., wikipedia.org). Output Format:** You can modify the Create Google Doc node to include more specific data, such as the list of competitor URLs analyzed.

Extract order details from LINE messages and photos to Google Sheets with OpenAI Automatically extract order information from text messages or handwritten memo photos sent via LINE, confirm with the user, and append to a Google Sheets tracking sheet. How it works Receives text or image messages from LINE Messaging API Routes messages by type — text goes directly to the AI Agent, images are first downloaded via LINE API The AI Agent (GPT-4o) analyzes the input, extracts order details, and asks the user for confirmation Once approved, the order is appended as a new row in Google Sheets Setup steps LINE Messaging API: Create a LINE channel and set the webhook URL to this workflow's trigger endpoint OpenAI Credentials: Set up your OpenAI API key in n8n Credentials Google Sheets Credentials: Set up Google Sheets OAuth2 in n8n Credentials Configure Spreadsheet: Open the "Append Row to Google Sheets" node and set your Spreadsheet ID and sheet name Activate the workflow

This workflow automatically reviews new Zendesk tickets and tags them using OpenAI’s language model. It runs every 24 hours, fetches tickets created in the last day (for specified brands), and uses an AI agent to analyze each ticket’s content. Based on customizable rules, the agent suggests and applies relevant tags, ensuring existing tags are preserved. This helps automate ticket categorization and improves support team efficiency. Key Features: Scheduled daily execution Brand filtering for targeted ticket processing AI-powered tagging based on ticket content and custom rules Preserves existing tags while adding new ones Setup Instructions: Replace placeholder brand IDs/names and tag rules with your own. Connect your Zendesk and OpenAI accounts.

This Database SQL Query Agent convert natural language into sql query to get results Turn your PostgreSQL database into a conversational AI agent! Ask questions in plain English and get instant data results without writing SQL. ✨ What It Does Natural Language Queries**: "Show laptops under $500 in stock" → Automatic SQL generation Smart Column Mapping**: Understands your terms and maps them to actual database columns Conversational Memory**: Maintains context across multiple questions Universal Compatibility**: Works with any PostgreSQL table structure 🎯 Perfect For Business analysts querying data without SQL knowledge Customer support finding information quickly Product managers analyzing inventory/sales data Anyone who needs database insights fast 🚀 Quick Setup Step 1: Prerequisites n8n instance (cloud/self-hosted) PostgreSQL database with read access OpenAI API key/You can use other LLM as well Step 2: Import & Configure Import this workflow template into n8n Add Credentials: OpenAI API: Add your API key PostgreSQL: Configure database connection Set Table Name: Edit "Set Table Name" node → Replace "table_name" with your actual table Test Connection: Ensure your database user has SELECT permissions Step 3: Deploy & Use Start the workflow Open the chat interface Ask questions like: "Show all active users" "Find orders from last month over $100" "List products with low inventory" 🔧 Configuration Details Required Settings Table Name**: Update in "Set Table Name" node Database Schema**: Default is 'public' (modify SQL if different) Result Limit**: Default 50 rows (adjustable in system prompt) Optional Customizations Multi-table Support**: Modify system prompt and add table selection logic Custom Filters**: Add business rules to restrict data access Output Format**: Customize response formatting in the agent prompt 💡 Example Queries E-commerce "Show me all electronics under $200 that are in stock" HR Database "List employees hired in 2024 with salary over 70k" Customer Data "Find VIP customers from California with recent orders" 🛡️ Security Features Read-only Operations**: Only SELECT queries allowed SQL Injection Prevention**: Parameterized queries and validation Result Limits**: Prevents overwhelming queries Safe Schema Discovery**: Uses information_schema tables 🔍 How It Works Schema Discovery: Agent fetches table structure and column info Query Planning: Maps natural language to database columns SQL Generation: Creates safe, optimized queries Result Formatting: Returns clean, user-friendly data ⚡ Quick Troubleshooting No Results**: Check table name and ensure data exists Permission Error**: Verify database user has SELECT access Connection Failed**: Confirm PostgreSQL credentials and network access Unexpected Results**: Try more specific queries with exact column names 🎨 Use Cases Inventory Management**: "Show low-stock items by category" Sales Analysis**: "Top 10 products by revenue this quarter" Customer Support**: "Find customer orders with status 'pending'" Data Exploration**: "What are the unique product categories?" 🔧 Advanced Tips Performance**: Add database indexes on frequently queried columns Customization**: Modify the system prompt for domain-specific terminology Scaling**: Use read replicas for high-query volumes Integration**: Connect to Slack/Teams for team-wide data access Tags: AI, PostgreSQL, Natural Language, SQL, Business Intelligence, LangChain, Database Query Difficulty: Beginner to Intermediate Setup Time: 10-15 minutes