Browse 12,955 Workflows

By iamvaar

Quick overview This workflow ingests irrigation telemetry via a webhook, enriches it with hyperlocal weather from Open-Meteo, uses Google Gemini to classify incident severity and generate remediation steps, then posts a work-order style alert to Slack and returns a structured response to the caller. How it works Receives irrigation telemetry (zone, moisture, pump state, last run time, and coordinates) via an HTTP POST webhook. Normalizes and fills missing sensor fields with defaults, then calls the Open-Meteo API to fetch recent and forecast precipitation and temperature for the provided location. Combines sensor and weather context into a prompt and sends it to Google Gemini (Gemini 3.1 Flash Lite) to produce a structured incident assessment (severity, title, root cause, SLA, action items, and escalation flag). Parses and augments the AI output by normalizing severity/SLA values and generating a unique ticket ID with timestamps and the original telemetry context. Routes the incident based on severity (CRITICAL, HIGH, ADVISORY, NORMAL) to set the appropriate dispatch channel, audience, urgency, and work order status. Builds a work-order payload (including SLA deadline) and posts a formatted incident alert message to a Slack channel. Responds to the original webhook request with the final structured ticket payload and processing status. Setup Add a Google Gemini (PaLM) API credential and ensure the workflow is configured to use the Gemini 3.1 Flash Lite model. Add Slack API credentials and select the target channel where incident alerts should be posted. Copy the webhook URL from the webhook trigger and configure your telemetry source to POST sensor readings and coordinates to it. An n8n automation workflow template by iamvaar.

By iamvaar

Quick Overview This workflow collects pool service visit notes via an n8n Form, looks up customer and history in Google Sheets, uses Google Gemini to structure the notes into a report, logs visits and work orders back to Sheets, and sends alerts via Gmail, Slack, and Telegram. How it works Receives a pool service visit submission from an n8n Form with customer ID, technician notes, and optional water readings. Looks up the customer in Google Sheets and sends a Telegram alert if the customer ID is unknown. Pulls the customer’s recent visit history from Google Sheets and combines it with the new readings to generate rule-based flags for out-of-range chemistry and high filter pressure. Sends the combined context to Google Gemini to extract structured fields (condition, issues, actions, follow-up, summaries) and validates the response against a strict JSON schema. Builds a visit record with an HTML customer report, calculates urgency, priority, and next visit date, and appends the visit to the Google Sheets Visits table (or logs a manual-review record and posts a Slack alert if the AI step fails). If follow-up is needed, creates a work order in the Google Sheets Work Orders table and updates the customer record with the latest status and next visit date. If the visit is urgent, posts an operations alert to Slack, and if the report needs manager approval it emails an approve/hold link via Gmail and waits for the decision before either sending the customer report email or marking it as held. Runs every morning (Mon–Sat) to pull open work orders from Google Sheets, builds a daily digest, and sends it to Telegram. Setup Create a Google Sheets spreadsheet with Customers, Visits, and Work Orders sheets (and matching column names used by this workflow), then add a Google Service Account credential with access to the spreadsheet and update the document ID if needed. Add a Google Gemini (Google PaLM) API credential and keep the model set to models/gemini-3.1-flash-lite (or update it consistently across the workflow). Add a Gmail OAuth2 credential, set the manager approval recipient email, and ensure the sender name and customer email field mapping match your business requirements. Add Slack and Telegram credentials, then replace YOUR_TELEGRAM_CHAT_ID and select the correct Slack channel for urgent alerts and AI-failure notifications. Edit the configuration constants in the code steps (company name/phone/brand color, chemistry thresholds, PSI limits, plan intervals, and Sunday skipping) to match your operating standards. An n8n automation workflow template by iamvaar.

By iamvaar

Quick overview Youtube Video: https://youtu.be/s79Y5rty2WM This workflow ingests cold-chain temperature alerts via webhook, looks up client SLA rules in Google Sheets, assigns severity and dispatches an on-call technician via Twilio SMS, then tracks acknowledgements, escalations, and daily SLA reporting using Google Sheets, Twilio, and Gmail. How it works Receives a POST webhook alert, normalizes the payload, and rejects invalid requests with a 400 response. Looks up the client contract in Google Sheets and rejects unknown client IDs with a 404 response. Detects likely defrost-cycle spikes, logs an observation to Google Sheets, and returns a 202 response without dispatching. Computes severity and SLA deadlines, checks Google Sheets for existing open tickets for the same client/equipment, and suppresses duplicates with an audit log and 200 response. Matches an available certified technician from a Google Sheets roster and either creates an UNASSIGNED ticket and alerts the on-call lead via Twilio SMS or creates a DISPATCHED ticket, locks the technician as ON_JOB, and sends Twilio SMS messages to both technician and client. Accepts technician status updates (accept/decline/on-site/resolved) via a callback webhook, updates ticket and technician state in Google Sheets, logs the event, and returns an HTML confirmation page. Runs every 5 minutes to evaluate SLA progress, automatically reassign or escalate tickets, send Twilio escalation SMS/voice calls, and update Google Sheets ticket and technician records. Runs daily at 08:00 to calculate 24-hour SLA compliance from Google Sheets, archive a snapshot back to Google Sheets, and email an HTML report via Gmail. Setup Create Google Sheets tabs and columns for Clients_SLA, Technicians, Tickets_Dispatch, Escalation_Audit_Log, and SLA_Daily_Snapshots, then connect a Google Sheets Service Account credential with access to the spreadsheet. Add a Twilio credential and update the configured phone numbers (Twilio “from”, ops manager, on-call lead, admin, and client emergency contact fields in the sheet) to real values. Set your n8n public base URL in the configuration so the SMS callback links point to your reachable /webhook/tech-ack endpoint. Configure the source monitoring system to send alerts to the inbound webhook URL (/webhook/coldchain-alert) using the expected fields (client_id, current_temp_celsius or sensor_fault, equipment_type, and optional context). Add a Gmail OAuth2 credential and set the report recipient email address for the daily SLA report. Review and adjust operational thresholds (ack timeout minutes, defrost criteria, severity rules, and SLA tiers) to match your process and contracts. An n8n automation workflow template by iamvaar.

By iamvaar

Quick overview Youtube Video: https://youtu.be/Qd5CW0-TwS4 This workflow collects watch repair requests via an n8n form, syncs the customer to GoHighLevel, checks the uploaded photo with Sightengine, uses Google Gemini to generate a structured estimate and email draft, logs the ticket to Google Sheets, and emails the customer and shop via Gmail. How it works Receives a new watch repair request from an n8n form submission, including a required uploaded watch photo. Normalizes the submitted customer and watch details and looks up the contact in GoHighLevel, creating/updating the contact if it does not already exist. Reattaches the uploaded photo as binary data, extracts basic image metadata, and generates a unique repair ticket ID with a submission timestamp. Sends the photo to the Sightengine API to score whether it appears AI-generated and labels the request with an authenticity status. Uses Google Gemini (via an AI agent with structured output) to classify the issue, estimate price range and turnaround, determine if manual review is needed, and draft a short customer email. Logs the full ticket details, AI outputs, and review flags to a Google Sheets “Repair Tickets” worksheet. If manual review is required, emails the shop to review and sends the customer an acknowledgement; otherwise, emails the AI-generated estimate to the customer and notifies the shop that the estimate was sent. Setup Configure the n8n Form Trigger fields (or embed the form) and ensure file uploads are enabled for the watch photo. Add a GoHighLevel OAuth2 credential and confirm the workflow can search and upsert contacts in your GoHighLevel account. Add a Google Gemini (PaLM) API credential and keep the model set to models/gemini-3.1-flash-lite (or update it to your preferred Gemini model). Add a Gmail OAuth2 credential and update the shop notification recipient address(es) and shop identity fields (shop name/email) used in the messages. Add a Google Sheets Service Account credential, share the target spreadsheet with the service account, and update the spreadsheet ID and sheet name if you are not using the provided “Repair Tickets” sheet. Replace the hardcoded Sightengine api_user and api_secret values with your own Sightengine credentials. An n8n automation workflow template by iamvaar.

By iamvaar

Quick overview Youtube Video: https://youtu.be/CPAekWNslrc This workflow receives elevator complaints and technician service reports via webhooks, looks up and updates records in Google Sheets, uses Gemini to triage issues and extract structured diagnostics, then notifies technicians via WhatsApp and clients via Gmail while keeping tickets, service logs, and parts inventory in sync. How it works Receives an elevator complaint via a POST webhook and looks up the elevator record and recent service history in Google Sheets. Uses Google Gemini to classify the complaint severity (P1–P3), required technician skill level, and a technician-ready summary. Selects an available technician from a Google Sheets technician roster based on skill level, territory, and current workload, then generates a ticket ID, SLA deadline, and dispatch message. Appends a new ticket to the Google Sheets Tickets sheet, updates the elevator’s current status in the registry, and either marks the technician “On Job” and sends the dispatch via WhatsApp plus a confirmation email via Gmail, or emails an unassigned-ticket alert when no technician is available. Receives a technician report via a second POST webhook, retrieves the ticket, elevator details, and parts catalog from Google Sheets, and sends the technician notes to Google Gemini to extract root cause, work performed, parts used, safety flags, and closure status. Appends a service log in Google Sheets, updates the elevator registry (status and maintenance dates), updates/close the ticket, frees the technician back to “Available,” and emails the client a service update. Decrements inventory quantities for any catalog-matched parts used and sends a Gmail reorder alert when stock falls at or below the defined reorder threshold. Setup Create a Google Sheets service account credential in n8n and ensure the target spreadsheet contains the required tabs/columns (Elevators, Technicians, Tickets, Service_Logs, Inventory_Parts) and is shared with the service account email. Add a Google Gemini (Google PaLM) API credential for the two AI steps (triage and technician-note extraction). Add a WhatsApp Business Cloud credential and set the correct Phone Number ID and technician recipient number(s) for dispatch messages. Add a Gmail OAuth2 credential and update the sender account and recipient fields used for client confirmations, service updates, and low-stock/reorder alerts. Copy the two webhook URLs (complaint intake and technician report) and configure your intake form/app and technician reporting method to POST the expected fields (elevator_id/complaint_text and ticket_id/notes/technician_id). An n8n automation workflow template by iamvaar.

By Rahul Joshi

Quick Overview This workflow monitors Swiggy and Zomato reviews via an HTTP feed polled every 30 minutes or a webhook, uses OpenAI to analyze sentiment and draft replies, logs results to Google Sheets, and sends Telegram/Gmail alerts for critical reviews plus a weekly dish-level sentiment report. How it works Triggers every 30 minutes to fetch reviews from an HTTP endpoint or receives pushed reviews via a webhook. Normalizes incoming Swiggy/Zomato payloads into a consistent review format with IDs, ratings, text, dates, and ordered items. Loads previously logged review IDs and your menu from Google Sheets, then filters out duplicates and attaches the menu list for dish matching. Sends each new review and menu context to OpenAI (gpt-4o-mini) to classify sentiment/urgency, extract dish mentions and issues, and generate a suggested public reply and internal action. Writes one row per review to the Google Sheets “Reviews Log” tab and one row per dish mention to the “Dish Mentions” tab. Sends critical reviews (low rating or high urgency) to Telegram and escalates them via Gmail, while non-critical reviews are posted to Telegram as ready-to-paste reply drafts. Every Monday at 9 AM, reads the last two weeks from Google Sheets, aggregates week-over-week platform and dish sentiment, uses OpenAI to write insights, emails the full HTML report via Gmail, posts a Telegram summary, and archives the report to the “Weekly Reports” tab. Setup Create a Google Sheets file with tabs named “Reviews Log”, “Dish Mentions”, and “Weekly Reports”, and a separate menu sheet (for example “Menu”) that includes a dish name column (for example dish_name). Add credentials in n8n for Google Sheets, Gmail, Telegram (bot token), OpenAI, and (if using the poller) HTTP Header Auth for your review-feed endpoint. Update the configuration values in “Set Monitor Config” and “Set Report Config” (sheet IDs, menu sheet ID, Telegram chat ID, escalation/owner email addresses, brand voice, and thresholds). If using the webhook intake, copy the webhook URL from “Receive Reviews via Webhook” and configure your review source to POST reviews to /restaurant-reviews. Replace https://YOUR-REVIEW-FEED.example.com/reviews?since=last_30_min with your real review-feed URL if using the scheduled poll. An n8n automation workflow template by Rahul Joshi.

By Syed Maaz Saeed

Quick overview This workflow runs on demand or on weekday mornings to pull Competition and Markets Authority (CMA) merger case updates from GOV.UK, write a dated timeline into Google Sheets, and generate an email-friendly summary plus an attached HTML timeline report via SMTP. How it works Runs manually or on a cron schedule at 08:00 Monday–Friday (workflow timezone). Builds a list of GOV.UK CMA case API URLs from your configured case paths and validates that they are unique and correctly formatted. Fetches each case’s GOV.UK JSON content and extracts dated milestones from change history, attachments, and dated HTML entries while marking deadlines as planned. Creates a status row per case (including parse errors or “needs review” flags) and generates stable row keys for upserting. Upserts all status and milestone rows into a Google Sheets “Timeline” tab using the Row Key column to update existing entries without deleting history. Builds an HTML email summary and a full HTML timeline report for this run and prepares the report as an attached .html file. Sends the digest email with the HTML attachment via SMTP (when the email node is enabled). Setup Create a Google Sheet with a “Timeline” tab. Copy the exact column names from the “Google Sheets Headers and First Run” sticky note into row 1, including “Row Key”. Connect Google Sheets credentials to “Upsert Sheets Timeline Rows”. In “Set Email and Sheet Config”, enter your spreadsheet ID, sheet name, sender and recipient addresses, and CMA case list. Run manually and check the sheet rows and HTML attachment produced by “Format Timeline as HTML”. For email delivery, connect SMTP credentials and enable “Email Timeline Digest”, which is disabled by default. Confirm the workflow timezone, which defaults to Europe/London. Adjust the weekday 08:00 schedule if needed, then activate/publish the workflow after your manual test succeeds. Requirements An n8n instance with access to GOV.UK Google Sheets credentials with permission to edit the destination spreadsheet. Valid GOV.UK CMA merger case paths. SMTP credentials only if email delivery is enabled. No AI model, community nodes or GOV.UK API key required Customization Replace the sample cases with the CMA merger cases you want to track. Change the schedule, timezone, destination spreadsheet and email addresses Adapt milestone extraction rules and HTML report styling Additional info Two historical CMA cases are included as examples. The workflow covers GOV.UK CMA case pages only. Email delivery is disabled until configured. The HTML report contains the current run’s extracted entries. Google Sheets retains previous milestone rows; changed or removed source entries are not automatically deleted. Planned dates remain labelled as planned. Verify important dates against the linked official source. An n8n automation workflow template by Syed Maaz Saeed.

By Intuz

Quick overview This workflow answers finance questions received on WhatsApp (via WAHA) or Telegram by fetching data from Xero, drafting a validated response with OpenAI, optionally posting the result to Slack, and persisting conversation state in an n8n Data Table. How it works Receives an incoming message from WhatsApp via a WAHA webhook (with HMAC verification) or from a Telegram bot trigger. Normalizes the incoming message into a consistent format, applies workflow configuration, and blocks unauthorized senders based on an allowed-users list. Loads the prior conversation state from an n8n Data Table and decides whether the message is a Slack-share follow-up (Yes/No/post) or a new finance request. For new requests, uses OpenAI to classify the intent (accounts receivable, cash position, or bills due this week) and replies with help text if the intent is unknown. Retrieves the connected Xero organisations, selects the correct Xero tenant, and queries the relevant Xero endpoints to build a canonical text summary for the requested report. Uses OpenAI to rewrite the canonical Xero summary as a concise chat response and validates it against the canonical numbers before asking whether to post the update to Slack. Saves the updated conversation state and sends the reply back to the originating channel (WhatsApp via WAHA or Telegram), posting the previous answer to Slack if the user confirms. Setup Connect credentials for Xero OAuth2, OpenAI, Slack, and Telegram, and add HTTP Header Auth credentials for the WAHA send API. Configure WAHA to send message events to the workflow’s webhook URL and set the matching HMAC SHA-512 secret and WAHA base URL. Create an n8n Data Table named “Finance Bot Conversation State” with columns for stateKey, userId, channel, chatId, lastIntent, lastResponse, and pendingSlackConfirmation. Update the workflow configuration values for allowed users, the Slack channel ID, and (if you have multiple Xero organisations) the Xero tenant ID. Additional info Connect with us: Website: https://www.intuz.com/n8n-workflow-automation-templates/ Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz For Custom Workflow Automation Get Started: https://n8n.partnerlinks.io/intuz. An n8n automation workflow template by Intuz.

By Tushar Rayamajhi

Quick overview This workflow turns Facebook Messenger messages into a clothing sales flow powered by Google Gemini, with carts and orders stored in n8n Data Tables, payments handled via Stripe Checkout, customer memory stored in Postgres, and an embedded admin dashboard for products, orders, escalations, and configuration. How it works Receives Meta webhook requests for a Facebook Page, verifies the webhook handshake, immediately acknowledges events, and filters for real customer messages. De-duplicates incoming messages, briefly waits to combine multiple quick messages from the same customer, and records the customer’s latest activity in n8n Data Tables. Looks up or creates the customer record and finds (or creates) the customer’s current open cart order in the Sales Orders table. Uses a Google Gemini agent with Postgres chat memory plus tools backed by n8n Data Tables to list/search products (via a pgvector index), fetch live product details, manage cart items, and save delivery details. When the customer confirms the order, re-validates prices, variants, stock, and delivery details, then creates a Stripe Checkout Session and sends a “Pay Now” button in Facebook Messenger. On Stripe webhook events or the payment return page, verifies the Stripe signature, marks the order as Paid, records order line items, reduces inventory stock, and sends a payment confirmation message back in Messenger. If the agent escalates a question, it creates an escalation record for the admin inbox and later delivers admin answers in chat; nightly cleanup removes old message IDs, stale cart lines, and marks old Draft orders as Abandoned. Setup Add credentials for Google Gemini (PaLM API), Postgres (for chat memory and the pgvector product index), and Google Drive OAuth2 (for hosting product photos). Publish the workflow and set it as its own error workflow in the workflow settings. Open your-n8n-url/webhook/shop-admin and press Create database and first login. Sign in with admin / admin, then choose your own username and password straight away. In the admin dashboard, configure your Meta app (App ID, App Secret, Verify Token) and connect a Facebook Page so it subscribes to the workflow’s /webhook/chat endpoint. In the admin dashboard, connect Stripe with a restricted or secret key so the workflow can create Checkout Sessions and receive events on /webhook/shop-stripe-webhook. Add products (including price, stock, sizes/colors, and images) and run a full re-sync so the pgvector search index is populated for semantic product search. Test with a Messenger tester account: send a test order and pay with Stripe test card 4242 4242 4242 4242. Use a live Stripe key only after a full test order works. Requirements n8n reachable over https (n8n Cloud, or self-hosted with a public URL) Supabase project (Postgres with pgvector); the free plan is enough Google Gemini API key (the free key allows only about 20 requests a day, so enable billing for real customers) Google Drive account (OAuth2) for product photos, optional Meta developer app (Business type) and a Facebook Page you manage Stripe account (test mode is fine to start) Customization Change store name, tone, language and shop information (hours, delivery charge, returns) on the Assistant page. Change how long the workflow waits to group quick messages on the Wait For More Messages node. Change the nightly cleanup rules. Replace the Gemini chat model with another chat model, keeping the tools and memory connected. Additional info Walkthrough video (2 min): https://drive.google.com/file/d/1HchY8S2IfqyadX-hvK1-ZiTB1pnUUkCl/view?usp=sharing The admin website has a built-in Setup guide page with live status. Facebook and Stripe are connected from that website, so they need no n8n credential. While your Meta app is in Development mode only app admins, developers and testers can chat with the bot. Messenger only allows replies within 24 hours of the customer's last message. An n8n automation workflow template by Tushar Rayamajhi.

By Kanishq Sharma

Quick overview This workflow manually updates a specific Supabase row via custom RPCs, captures verified before/after snapshots, and records the change as a recovery receipt in Rewind using HTTP requests. How it works Runs manually to start a single test update. Sets the Supabase project URL, Rewind base URL, table alias, target row UUID, patch fields, and connection name, then validates these inputs. Calls a Supabase REST RPC to read the current row revision and verifies a valid version is returned. Calls a Supabase REST RPC to apply the patch only if the expected version matches, returning atomic before/after snapshots and the new revision. Builds and validates a Rewind operation payload including idempotency key, resource identifier, and the captured snapshots and revision. Sends the payload to the Rewind API to record the operation for later approval and recovery. Setup Use a development Supabase project, n8n, and a Rewind account. From https://rewind.kanishq.dev/#connect download and run the connector SQL, then the disposable demo-table SQL. Create an HTTP Header Auth credential in n8n with the Supabase server secret as apikey. Select it on Read row and Capture update. Keep credentials only in n8n; none are included in this template. Create an HTTP Header Auth credential in n8n for Rewind using Authorization: Bearer , and select it for the Rewind recording request. Update the Supabase project origin URL, Rewind base URL, alias, row UUID, patch JSON, and connection name in the configuration step to match your environment and Rewind worker connection. Customization Only adapt registered tables and existing scalar fields after testing. Updates only: no inserts, deletes, messages or pre-install recovery. Leave schedules inactive until tested. Additional info Recovery is a separate workflow. A person reviews and approves the recorded change in Rewind; approval queues work. The matching worker checks the current revision before restoring. Verify the actual Supabase row after the worker runs. Check active/5 becomes inactive/3 and returns to active/5. Repeat with a later edit to confirm conflict protection. If receipt delivery fails, retry only Record operation with saved input; never repeat the provider update. Try one disposable recovery with the complete setup guide, using the approved recovery companion after capture and human approval. An n8n automation workflow template by Kanishq Sharma.

By Inistate

Quick overview This workflow runs every morning to find Inistate entries stuck in a specific approval state for longer than a set number of days, then emails an HTML digest of the stale items via SMTP. How it works Runs every morning at 9:00 on a schedule. Reads configuration values for the target Inistate state name, stale-day threshold, and email recipients. Queries Inistate for entries in the configured state that have not been updated since the calculated cutoff date. Aggregates the returned entries into a single list. Builds an email subject and an HTML table summarizing each stale entry (ID, last updated, updated by, and assignees). Sends the digest email via SMTP to the configured recipients. Setup Add an Inistate credential, then select the target workspace, module, and (if needed) a listing the account can access in the Inistate node. Update the Settings values for the exact approval state name, the number of days that counts as stale, the recipient email address, and the from address. Add an SMTP email credential in the email-sending node and verify your mail server allows the chosen from address. An n8n automation workflow template by Inistate.

By Tom Hester

Quick overview Check a completed Apify crawl before refreshing a chatbot or knowledge base. This manual workflow verifies the source run, audits its export for missing required pages and other quality failures, then routes PASS or BLOCK without writing to your destination. How it works Runs when triggered manually in n8n. Reads your configured Apify crawl run ID, namespace, expected URLs, and the explicitly reviewed failed-request count, then stops if any required configuration is missing or indicates crawl failures. Calls the Apify API to verify the specified actor run finished successfully and has an available dataset to audit. Starts an Apify Crawl Quality Gate actor run with the dataset ID and your URL expectations, waiting briefly for it to finish. Fetches the audit REPORT from the Apify key-value store and validates that it matches the expected schema and source run. Routes to PASS (connect your refresh here) when the report gate passes, or to BLOCK to keep the current knowledge base when it fails. Setup Create an Apify API token and add it to n8n as an HTTP Header Auth credential (Authorization: Bearer ) used by all Apify HTTP requests. In the Configure source step, set your finished Apify run ID, a stable namespace, and a list of required expected URLs (and optionally a previous manifest). Review the crawl’s failed-request count in Apify and enter it as upstreamFailedRequests (must be 0 for the workflow to proceed). Attach your knowledge base/chatbot refresh workflow only to the PASS branch, and persist the returned report.manifest only after a successful refresh. Requirements n8n and an Apify account with access to a completed crawler run and its dataset. The workflow template is free. Each real completed Crawl Quality Gate audit, including a BLOCK result, costs $0.10. This workflow caps the audit charge at $0.10 and does not retry automatically. Other platform costs may apply. Customization Set the required URLs and stable namespace for your source. Optionally supply a manifest saved after a previous successful refresh. Connect only PASS to your destination update; keep existing data on BLOCK or errors. Scheduling, destination writes and persistent manifest storage are not included. Additional info For agencies and developers refreshing chatbots or knowledge bases from existing Apify crawls. A free synthetic demo and setup guide are available at https://apify.com/obeying_laureate/crawl-quality-gate. The audit checks supplied rules, including required-page coverage, duplicates, recorded failures and short text; PASS does not prove whole-site completeness or authorize deletion. Test BLOCK by adding an absent required URL before connecting a destination. Verified on n8n 2.6.4. An n8n automation workflow template by Tom Hester.