Workflow Templates

In this tutorial, I’ll walk you through a step-by-step N8N workflow that combines the power of OpenAI and Claude AI to generate professional, ready-to-use lead magnet plans for any niche. This workflow helps marketers, agencies, and freelancers create engaging lead magnets — such as guides, blueprints, and checklists — with zero manual writing and complete AI automation. Who is this for? Marketers and content strategists creating high-converting lead magnets Agencies looking to scale client content deliverables Freelancers offering marketing automation services Anyone who wants to combine AI + automation for efficient content creation What problem is this workflow solving? Manually writing lead magnets can be slow and inconsistent. This workflow eliminates that by: Using OpenAI and Claude AI to co-create detailed content frameworks Automating research, structure, and formatting of lead magnet documents Allowing full customization for different industries or audiences Reducing production time from hours to minutes What this workflow does This automation connects OpenAI, Claude AI, and Google Drive (or Docs) inside n8n to produce well-structured lead magnet documents. The process includes: Collecting a topic or niche input from a form or webhook. Generating an outline and content blocks using OpenAI. Refining, expanding, and organizing the text using Claude AI. Formatting the content and converting it to clean HTML or Google Docs format. Saving or uploading the final version to Google Drive or Notion. By the end of the tutorial, you’ll have a fully automated content agent that builds lead magnet plans from scratch — ready to deliver to clients or publish instantly. Setup Create Accounts: Sign up for n8n.io. Obtain API access for OpenAI, Claude (via OpenRouter), and Google Drive API. Add API Keys in n8n: Go to Credentials and add your OpenAI and Claude API keys securely. Build the Workflow: Use a Form Trigger or Webhook Node to capture topic input. Add OpenAI Node to generate structure and section ideas. Add HTTP Request Node for Claude API (OpenRouter) to expand sections into polished paragraphs. Use a Function Node to merge sections and format them into Markdown or HTML. Add Google Drive Node to upload or store the final file. Test Your Workflow: Input a test topic (e.g., “Dental Marketing Blueprint”). Wait for the AI to generate, merge, and store your lead magnet content automatically. How to customize this workflow to your needs Modify prompt templates to fit your target audience or writing style. Integrate Notion, Airtable, or Slack for automatic delivery. Add a scheduling trigger (e.g., weekly lead magnet generation). Incorporate branding or styling logic using Markdown → HTML conversion. Expand prompts for multilingual or niche-specific lead magnets. Notes This workflow requires API keys for both OpenAI and Claude (via OpenRouter). Ensure proper handling of text formatting nodes to avoid Markdown errors. Google Drive integration requires OAuth setup in n8n credentials. Works on both n8n Cloud and self-hosted environments. 🎥 Watch the Full Tutorial 👉 YouTube Video Tutorial

This workflow acts as an automated Social Media Content Strategist, allowing you to generate a complete, 5-slide Instagram carousel with a corresponding caption directly from a single idea sent via Telegram. Instead of writing complex prompts for each slide, the workflow uses a specialized AI Agent to interpret your topic, apply your specific brand guidelines, and generate a full, structured educational carousel automatically. By integrating a structured output parser, it ensures the AI generates a detailed plan for all 5 slides. These are then sent to an external, high-quality image generation API. A second AI agent simultaneously works on crafting an engaging, SEO-friendly caption for your post. Use cases are many: Automated Content Creation:** Generate a complete, ready-to-post Instagram carousel from a simple topic idea in minutes. Rapid Idea Visualization:** Quickly prototype different educational content pillars for your social media strategy. Brand Consistency:** Enforce a specific visual style, color palette, and mood across all AI-generated carousels through a central brand guideline node. Good to know Full Carousel Generation:** The workflow doesn't just make one image; it creates a complete 5-slide carousel, including the visual concepts and text overlays for each slide. Dual AI Agents:** It leverages two distinct AI personas: a "Senior Content Strategist" to structure the carousel and an "Instagram Copywriter" to write the caption. Polling System:** It includes a smart "Wait" and "Check Status" loop to handle the asynchronous nature of the external image generation API, ensuring it retrieves the content without errors once it's ready. Security:** It features a Chat ID filter on the trigger to ensure only authorized users can initiate the workflow. How it works Trigger: You send a content idea (e.g., "5 tips for better time management") to your configured Telegram bot. Validation: The workflow first checks if the message comes from an authorized Chat ID. Content Strategist (AI Agent): An AI agent takes your topic and the predefined "Brand Guideline" to create a detailed 5-slide plan, outputting a JSON object with prompts for both the visuals and text overlay of each slide. Caption Copywriter (AI Agent): In parallel, a second AI agent writes an engaging, SEO-friendly Instagram caption based on the carousel prompts. Image Generation: The workflow sends the 5 slide prompts to the external image generation API (Kie AI) to create the visuals. Status Polling: It waits for a set duration and then repeatedly checks the API with the unique task ID until the images are fully generated and ready for download. Delivery: The final high-resolution carousel images and the generated caption are sent back to you via Telegram, ready to be posted. Setup steps Telegram: Create a bot via @BotFather on Telegram. Get the API Token and add it to the Telegram Trigger node's credentials. Send a message from your account, run the workflow once, and copy your Chat ID from the output into the IF node to authorize yourself. OpenAI: Connect your OpenAI credentials to the "Generate Carousel Content" and "Generate Caption" nodes. Image Generation API (Kie AI): This workflow uses api.kie.ai for image generation. You will need to create an account with them to get an API key. Add this key as a new Header Auth Credential in n8n and select it in the "Generate Carousel Images" and "Retrieve Carousel Images" nodes. Brand Guideline: Open the "Set Brand Style" node and replace the placeholder text in the style variable with your specific brand colors, typography, and overall aesthetic. Execution: Activate the workflow and send a simple topic to your bot to start the content creation process. Requirements Telegram Bot API Token OpenAI API Key Kie.ai (or other image generation service) API Key n8n version with LangChain & AI Agent nodes support

🚀 Build Your Own Knowledge Chatbot Using Google Drive Create a smart chatbot that answers questions using your Google Drive PDFs—perfect for support, internal docs, education, or research. 🛠️ Quick Setup Guide** Step 1: Prerequisites n8n instance (cloud or self-hosted) Google Drive account (with PDFs) Supabase account (vector database) OpenAI API key PostgreSQL database (for chat memory) else remove the node Step 2: Supabase Setup Create supabase account (its free) Create a project Copy the sql and paste it in supabase sql editor -- Enable the pgvector extension to work with embedding vectors create extension vector; -- Create a table to store your documents create table documents ( id bigserial primary key, content text, -- corresponds to Document.pageContent metadata jsonb, -- corresponds to Document.metadata embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed ); -- Create a function to search for documents create function match_documents ( query_embedding vector(1536), match_count int default null, filter jsonb DEFAULT '{}' ) returns table ( id bigint, content text, metadata jsonb, similarity float ) language plpgsql as $$ #variable_conflict use_column begin return query select id, content, metadata, 1 - (documents.embedding <=> query_embedding) as similarity from documents where metadata @> filter order by documents.embedding <=> query_embedding limit match_count; end; $$; Step 3: Import & Configure n8n Workflow Import this template into n8n Add credentials: OpenAI API key Google Drive OAuth2 Supabase URL & service key PostgreSQL connection Set your Google Drive folder ID in triggers Step 4: Test & Use Add a PDF to your Drive folder → check Supabase for new entries Start the workflow and chat → ask questions about your documents. "What can you help me with?" Multi-turn chat → context is maintained per user ⚡ Features Auto-syncs new/updated PDFs from Google Drive Extracts, chunks, and vectorizes text Finds relevant info and answers questions Maintains chat history per user 📝 Troubleshooting Check folder permissions & IDs if no docs found Verify API keys & Supabase setup for errors Ensure PostgreSQL is connected for chat memory Tags: RAG, Chatbot, Google Drive, Supabase, OpenAI, n8n Setup Time: ~20 minutes

This n8n template transforms Upwork job postings into personalized Loom video outreach assets in under 60 seconds. Paste a job description and get a complete outreach package: video script, before/after comparison, automation flow diagram, and proposal snippet. Use cases include: AI/Automation agencies doing Upwork cold outreach, freelancers who personalize proposals with Loom videos, or anyone wanting to scale video prospecting with AI-generated scripts. Good to know Each job processed costs approximately $0.02-0.04 USD in Claude API fees (two API calls per job) Processing time is ~45-60 seconds per job The workflow uses Claude Sonnet for optimal cost/quality balance Generated scripts are starting points - review and personalize before recording How it works Submit an Upwork job via the built-in form (title, description, optional client name and URL) Claude AI analyzes the job to extract: industry classification, pain points, tools mentioned, budget/urgency signals, and competition level A second Claude call generates the complete outreach package based on the analysis All assets are saved to a Google Doc named by prospect Lead data is logged to Google Sheets for tracking Slack notification delivers the doc link and key insights What you get for each job: 90-120 second Loom video script (hook, credibility, walkthrough, CTA) Before/After process comparison with ROI calculations Automation flow diagram structure Upwork proposal opening snippet Visual prompts for Whimsical/Figma diagrams Quick reference card with pricing guidance How to use The form trigger creates a URL at your-n8n-instance/form/upwork-loom-generator Paste the full job description for best results - more context = better analysis Add the client name if visible for personalized script openings After generation, review the Google Doc and customize the script to your voice Use the visual prompts to create diagrams before recording your Loom Requirements Anthropic account** for Claude API access Google account** with Docs and Sheets enabled Slack workspace** for notifications Set up steps Anthropic credential - Create HTTP Header Auth credential with your API key (header name: x-api-key) Google credentials - Connect Google Docs and Google Sheets OAuth2 credentials Slack credential - Add Slack API credential with chat:write scope Update placeholders in nodes: Create Google Doc → Set your Google Drive folder ID Log to Google Sheets → Set your spreadsheet ID Both Slack nodes → Set your channel ID Create tracking sheet with columns: Timestamp, Prospect Name, Industry, Business Function, Pain Point, Tokens Used, Google Doc Link, Version Customising this workflow Edit the "MY BACKGROUND" section in the Claude - Generate Loom Assets node to match your experience and services Adjust industry-specific hourly rates and time savings in the prompt to match your market Modify the Loom script CTA to your preferred next step (calendar link, reply, etc.) Add additional integrations: Notion database, CRM, or calendar booking Swap Slack for Discord, Teams, or email notifications

Make your unstructured large documents LLM ready markdown using LandingAI Document Parsing. Automatically watches a Google Drive folder, submits new documents to Landing.ai for parsing, caches processed files in - Supabase to avoid reprocessing, and reliably polls results with retry and timeout handling. Use Cases Automated document ingestion for RAG pipelines Invoice, contract, or report parsing AI-powered document analysis workflows Knowledge base ingestion from Google Drive Preventing duplicate document processing in ETL pipelines External services: Google Drive Landing.ai Supabase Credentials Required Required Google Drive OAuth2 Landing.ai API (HTTP Bearer Token) Supabase API How it works Once the pdf land in google drive location it trigger and it convert pdf (even more then 200 pages to LLM ready markdown). It also check in database if the parsing is already done or not, this help to avoid any unnecessary landingAI api call. Setup Instructions Step 1: Google Drive Create or select a folder in Google Drive Copy the folder ID Update the Google Drive Trigger node with this folder ID Step 2: Landing.ai Create a Landing.ai account Generate an API key Add it in n8n as an HTTP Bearer Auth credential Update the organization-id header if required Step 3: Supabase Create a Supabase project Create a table named landing_parse_cache Add fields such as: file_id document_name mime_type file_size_bytes job_id job_status markdown uploaded_at workflow_run_id Connect Supabase credentials in n8n Expected Input A document uploaded into the configured Google Drive folder (PDF, DOCX, or other supported formats) Expected Output Parsed markdown content stored in Supabase Metadata including: File ID File name MIME type File size Job ID Processing status Early exit if the document already exists in cache Error Handling & Edge Cases Cache check to prevent duplicate processing Retry-based polling for async job completion Timeout detection for stuck jobs Large file output URL handling Detailed logging for debugging and audits Customization Ideas Push parsed output to a vector database Trigger Slack or email notifications Store results in cloud storage (S3, GCS) Extend into a RAG or AI agent pipeline Categories Document Processing AI & LLM Knowledge Management Automation Difficulty Level Advanced Happy Automating - from Alok

Build an intelligent WhatsApp assistant that automatically responds to customer messages using AI. This template uses the Evolution API community node for WhatsApp integration and OpenAI for natural language processing, with built-in conversation memory powered by Redis to maintain context across messages. > ⚠️ Self-hosted requirement: This workflow uses the Evolution API community node, which is only available on self-hosted n8n instances. It will not work on n8n Cloud. What this workflow does Receives incoming WhatsApp messages via Evolution API webhook Filters and processes text, audio, and image messages Transcribes audio messages using OpenAI Whisper Analyzes images using GPT-4 Vision Generates contextual responses with conversation memory Sends replies back through WhatsApp Who is this for? Businesses wanting to automate customer support on WhatsApp Teams needing 24/7 automated responses with AI Developers building multimodal chat assistants Companies looking to reduce response time on WhatsApp Setup instructions Evolution API: Install and configure Evolution API on your server. Create an instance and obtain your API key and instance name. Redis: Set up a Redis instance for conversation memory. You can use a local installation or a cloud service like Redis Cloud. OpenAI: Get your API key from platform.openai.com with access to GPT and Whisper models. Webhook: Configure your Evolution API instance to send webhooks to your n8n webhook URL. Customization options Modify the system prompt in the AI node to change the assistant's personality and responses Adjust the Redis TTL to control how long conversation history is retained Add additional message type handlers for documents, locations, or contacts Integrate with your CRM or database to personalize responses Credentials required Evolution API credentials (self-hosted) OpenAI API key Redis connection

🏥 Clinic WhatsApp Customer Service Bot This workflow automates patient communication for medical clinics using the WhatsApp Business API. It supports appointment booking, rescheduling, service inquiries, follow-ups, and document submissions. The workflow includes AI capabilities, appointment management, human escalation logic, memory storage, and CRM synchronization. Good to know Supports text, voice notes, images, and document uploads. Uses an AI agent powered by GPT-4o-mini with retrieval-augmented generation for accurate answers. Includes sentiment and frustration detection to trigger human takeover. Conversation history and lead details are stored for context and follow-up. Appointment booking includes slot validation to reduce errors and conflicts. How it works The workflow receives WhatsApp messages through a webhook connection. The AI agent processes the message and identifies the intent: 📅 Appointment booking or rescheduling ❓ Service or doctor inquiry 📎 Document submission (e.g., lab results, insurance) 🤝 Human support request If the request is informational, the AI responds using GPT-4o-mini with RAG from Pinecone to ensure clinic-specific accuracy. If the request relates to booking, the workflow: Checks availability in Data Tables Validates slot selection Confirms, updates, or cancels the appointment If the user is confused, frustrated, or explicitly asks for a human, automation is paused and a staff member is notified. Voice messages are transcribed using Whisper API and images are processed using Vision API. All interactions are logged and synced to Google Sheets for CRM tracking. Requirements WhatsApp Business API access with active credentials OpenAI API key for GPT-4o-mini, Whisper, and Vision models Pinecone account for vector storage Google Sheets and Gmail for logging and notifications n8n instance (Cloud or self-hosted) Data Tables enabled for memory, appointments, and lead management

This n8n template from Intuz provides a complete and automated solution to transform your team's inbox management. It acts as an intelligent agent that reads incoming Gmail messages, uses AI to determine their category, and automatically routes them to the correct Slack channel—even creating new channels on the fly for new topics. Who's this workflow for? Customer Support Teams Sales & Lead Management Teams Operations & Project Management Teams Any team that uses Slack as a central hub for communication and triaging tasks. How it works 1. Monitor New Emails: The workflow continuously checks a specified Gmail account for new, unread emails. It automatically filters out spam, drafts, and duplicates. 2. AI Categorization: Each new email's subject and body are sent to an AI model (like Llama 3 via OpenRouter). The AI analyzes the content and assigns a category based on a predefined list (e.g., sales, marketing, accounts, internal). 3. Find or Create Slack Channel: The workflow then checks your Slack workspace to see if a channel corresponding to the AI's category already exists (e.g., #sales). 4. Route the Email: If the channel exists: The workflow posts a formatted summary of the email, a link to the original message in Gmail, and a "Reply" button directly into the existing channel. If the channel does NOT exist: The workflow automatically creates a new public channel (e.g., #new-category), invites a designated user, and then posts the email summary. Key Requirements to Use This Template 1. n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow uses the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed. 2. Gmail Account: An active Gmail account with API access enabled. 3. Slack Workspace & App: A Slack workspace where you have permission to install apps. A Slack App with a Bot Token that has the following scopes: channels:read, channels:manage, chat:write, groups:write, and users:read. 4. OpenRouter Account: An account with OpenRouter to access various AI models like Llama 3. You will need an API key. Setup Instructions 1. Gmail Configuration: In the "Capture Gmail Event" (Gmail Trigger) node, connect your Gmail account using OAuth2 credentials. 2. OpenRouter AI Configuration: In the "OpenRouter Chat Model" node, create a new credential and add your OpenRouter API key. 3. Slack Configuration: Create a Slack App: Go to api.slack.com/apps, create a new app, and install it to your workspace. Set Permissions: In your app's "OAuth & Permissions" settings, add the following Bot Token Scopes: channels:read, channels:manage, chat:write, groups:write, users:read. Reinstall the app to your workspace after adding them. Get Bot Token: Copy the "Bot User OAuth Token" (it starts with xoxb-). Connect in n8n: In all Slack nodes in the workflow, create a new credential and paste this Bot Token. Set User to Invite: In the "Invite a user to a channel" node, replace the placeholder User ID (U0A6ULM7CGK) with the Slack Member ID of the user you want to be automatically invited to new channels. 4. Activate the Workflow: Save the workflow and toggle the "Active" switch to ON. Your intelligent email routing system is now live! Support If you need help setting up this workflow or require a custom version tailored to your specific use case, please feel free to reach out to the template author: Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

📸🍽️ Telegram Food Photo → 🤖 Gemini Vision AI → 📊 Nutrition Data → 📄 Google Sheets + 🗂️ Drive What this workflow does 📸 Snap and send a photo of your meal via Telegram 🧠 Gemini Vision AI analyzes the image and estimates calories, protein, carbs, and fats 🤖 AI Agent structures the data with meal name, description, and timestamp 📄 Auto-logs nutrition data to Google Sheets for tracking 🗂️ Saves original meal photos to Google Drive with timestamped filenames 💬 Sends instant Telegram reply with full nutrition breakdown Why it's useful ⚡ Track nutrition in seconds—no manual entry or food databases 📊 Build a complete meal history with photos and macros in one place 🎯 AI estimates portion sizes and hidden ingredients (oils, sauces) 🏋️ Perfect for fitness tracking, meal prep, or health monitoring 📱 Works entirely through Telegram—no extra apps needed How it works 📲 Telegram Trigger → receives meal photo 🗂️ Google Drive → saves image with timestamp 🔎 Gemini Vision → analyzes food, estimates portions and macros 🤖 AI Agent → structures output (meal name, calories, protein, carbs, fats) 📄 Google Sheets → appends row with all nutrition data 💬 Telegram Reply → confirms with full breakdown What you'll need 🤖 Telegram Bot token 🧠 Google Gemini API key (includes Vision capabilities) 🔐 Google OAuth for Sheets + Drive 📊 Google Sheet with columns: Meal_Name, Date, Meal_description, Calories, Proteins, Carbs, Fats Setup steps 🔗 Connect credentials: Telegram, Google Gemini, Google Sheets, Google Drive 📄 Create Google Sheet with nutrition columns (see format above) 🗂️ Create Google Drive folder for meal photos 🧭 Update sheet ID and Drive folder ID in workflow 🧪 Test: send a meal photo via Telegram and check Sheet + Drive Customization ideas 📈 Daily summary: add scheduled workflow to calculate daily totals 🎯 Goal tracking: set IF conditions to alert when over/under calorie targets 📊 Charts: connect to Data Studio/Looker for visual progress tracking 🏃 Fitness integration: sync with MyFitnessPal or fitness apps Who it's for 🏋️ Fitness enthusiasts tracking macros without manual logging 🥗 Meal preppers analyzing portion sizes and nutrition 💪 Athletes monitoring calorie and protein intake 🩺 Health-conscious individuals building meal history 👨‍🍳 Nutritionists collecting client food data Quick Setup Guide - Before You Start - What You Need: 🔗 Telegram Bot (create via @BotFather) 🧠 Google Gemini API key with Vision enabled (get it here) 🔐 Google account for Sheets and Drive access 📊 Basic spreadsheet to track your meals Want help customizing? 📧 anirpoke@gmail.com 🔗 LinkedIn

Automated YouTube Shorts Creator with yt-dlp & FFmpeg Description How It Works • Downloads videos/music from YouTube using yt-dlp • Merges assets with dynamic text overlays • Automatically uploads to YouTube as Shorts (9:16 format) • Tracks everything in Google Sheets Set Up Steps (~10 minutes) Install yt-dlp and FFmpeg in your n8n environment Connect Google Sheets (for video/music pools) Set up YouTube OAuth credentials Configure text overlay font (NotoSerif included) Key Features Dual Pipeline System Video Downloader (MP4) + Music Downloader (MP3 with thumbnails) Random pairing for endless combinations Professional Text Overlays Dynamic line wrapping for perfect 9:16 formatting Customizable fonts/colors YouTube API Integration Automatic upload with metadata (titles/descriptions) Privacy/license controls Google Sheets Tracking Logs download paths, YouTube URLs, timestamps Prevents duplicate processing

Google Calendar AI Agent with Dynamic Scheduling Version: 1.0.0 n8n Version: 1.88.0+ Author: Koresolucoes License: MIT Description An AI-powered workflow to automate Google Calendar operations using dynamic parameters and MCP (Model Control Plane) integration. Enables event creation, availability checks, updates, and deletions with timezone-aware scheduling [[1]][[2]][[8]]. Key Features: 📅 Full Calendar CRUD: Create, read, update, and delete events in Google Calendar. ⏰ Availability Checks: Verify time slots using AVALIABILITY_CALENDAR node with timezone support (e.g., America/Sao_Paulo). 🤖 AI-Driven Parameters: Use $fromAI() to inject dynamic values like Start_Time, End_Time, and Description [[3]][[4]]. 🔗 MCP Integration: Connects to an MCP server for centralized AI agent control [[5]][[6]]. Use Cases Automated Scheduling: Book appointments based on AI-recommended time slots. Meeting Coordination: Sync calendar events with CRM/task management systems. Resource Management: Check room/equipment availability before event creation. Instructions 1. Import Template Go to n8n > Templates > Import from File and upload this workflow. 2. Configure Credentials Add Google Calendar OAuth2 credentials under Settings > Credentials. Ensure the calendar ID matches your target (e.g., ODONTOLOGIA group calendar). 3. Set Up Dynamic Parameters Use $fromAI('Parameter_Name') in nodes like CREATE_CALENDAR to inject AI-generated values (e.g., event descriptions). 4. Activate & Test Enable the workflow and send test requests to the webhook path /mcp/:tool/calendar. Tags Google Calendar Automation MCP AI Agent Scheduling CRUD Screenshots License This template is licensed under the MIT License. Notes: Extend multi-tenancy by adding :userId to the webhook path (e.g., /mcp/:userId/calendar) [[7]]. For timezone accuracy, always specify options.timezone in availability checks [[8]]. Refer to n8n’s Google Calendar docs for advanced field mappings.

How It Works: This n8n template automates the process of tracking design changes in Figma and updating relevant Jira issues. The template is triggered when a new version is created in Figma via a custom plugin. Once the version is committed, the plugin sends the design details to an n8n workflow using a webhook. The workflow then performs the following actions: Fetches the Jira issue based on the provided issue link from Figma. Adds the design changes as a comment to the Jira issue. Updates the status of the Jira issue based on the provided task status (e.g., "In Progress", "Done"). This streamlines the workflow, reducing the need for manual updates and ensuring that both the design team and developers have the latest design changes and task statuses in sync. How to Use It: Set up the Figma Plugin: Install the Figma Commit Plugin from GitHub. In the plugin, fill out the version name, design link, Jira issue link, and the task status. Commit the changes in Figma, which will trigger the webhook. Set Up the n8n Workflow: Import this template into your n8n instance. Connect the Figma Trigger node to capture version updates from Figma. Configure the Jira nodes to retrieve the issue and update the status/comment based on the data sent from the plugin. Automate: Once the version is committed in Figma, the workflow will automatically update the Jira issue and keep both your Figma design and Jira tasks in sync! By integrating Figma, Jira, and n8n through this template, you’ll eliminate manual steps, making collaboration between design and development teams more efficient.