Browse 12,955 Workflows

By Hassan

Quick overview This workflow adds real-estate leads to a 5-touch Gmail drip campaign, uses Google Gemini to generate and classify all five emails upfront, sends them automatically on schedule, detects replies and stops the sequence instantly, and delivers a morning digest of all active. How it works Receives a new lead via a webhook request (or an optional Google Sheets row-added trigger) and normalizes the lead and property fields into a consistent format. Uses Google Gemini to pre-generate five personalized email subjects and bodies based on the lead, property address, and agent details. Creates a new sequence row in Google Sheets (Active Sequences) with the generated email content and sends Touch 1 via Gmail, then applies a Gmail label and stores the Gmail thread ID back in the sheet. Waits the configured number of days between touches, checks the current sequence status in Google Sheets, and sends Touches 2–5 via Gmail only if the sequence is still active, updating the sheet and applying the Gmail label after each send. Monitors Gmail for replies on the labeled threads, fetches the full thread from the Gmail API, and extracts the latest reply text. Uses Google Gemini to classify the reply sentiment (Hot, Neutral, or Unsubscribe), matches the reply to the active sequence (by thread ID or sender email), updates the sequence as Responded in Google Sheets, emails the agent a notification, and logs the event to a Sequence Log sheet. Runs daily on a schedule to pull all sequences from Google Sheets, builds an HTML digest of active and responded sequences, emails it to the agent via Gmail, and logs the digest to a Daily Digest Log sheet. Setup Create and connect credentials for Gmail OAuth2, Google Sheets OAuth2, and a Google Gemini (PaLM) API key. Create a Gmail label (for example, "drip-sequence") and update the workflow’s label configuration to match the label used by the Gmail trigger and label-applying steps. Create a Google Sheets spreadsheet with tabs/columns matching the workflow outputs (Active Sequences, Sequence Log, and Daily Digest Log) and fill in the target Spreadsheet ID and sheet/tab references in all Google Sheets steps. Update the agent configuration values (agent name, agent email, and the touch timing offsets) in the sequence configuration sections, and set the agent notification recipient email in the reply notification email. If using the webhook entry point, copy the production webhook URL and configure your lead source to POST leadName/leadEmail/propertyAddress (and optional property details) to that endpoint. Requirements Gmail label setup (required before first use): Create a label named drip-sequence in Gmail before activating. Go to Gmail → Settings → See all settings → Labels → Create new label → name it drip-sequence. This label is applied to every outgoing sequence email so incoming replies are detectable by the Gmail Trigger. The label name must exactly match the GMAIL_LABEL value in the Configuration node. Google Sheets setup: Create a Drip Campaign Manager sheet template and link its ID to all Sheets nodes. Three tabs are required. Tab 1 — Active Sequences — with these columns: Sequence ID, Lead Name, Email, Phone, Property Address, Property URL, Property Description, Lead Background, Touch 1 Subject, Touch 1 Body, Touch 2 Subject, Touch 2 Body, Touch 3 Subject, Touch 3 Body, Touch 4 Subject, Touch 4 Body, Touch 5 Subject, Touch 5 Body, Current Touch, Status, Start Date, Last Touch Date, Thread ID, Reply Received, Reply Sentiment, Agent Notified, Sequence Label. Tab 2 — Sequence Log — with columns: Date, Sequence ID, Lead Name, Touch Number, Email Subject, Status, Notes. Tab 3 — Daily Digest Log — with columns: Digest Date, Active Count, Completed Count, Responses Today, Digest Sent. Before going live: Update AGENT_NAME and AGENT_EMAIL in the Section A Configuration node. Update AGENT_EMAIL in the Section C Daily Digest Configuration node — keep both in sync. Confirm the Gmail label drip-sequence exists and matches GMAIL_LABEL in the Configuration node. Customization Adjust wait days between touches in the Configuration node — SEQUENCE_DAYS_2 through SEQUENCE_DAYS_5 — without any workflow changes. Edit the Gemini system prompt to change the strategic angle of any touch, adjust tone, change email length, or translate the entire sequence to another language. Stop any sequence at any time by setting Status = Stopped in the Active Sequences sheet — the loop exits cleanly on the next check. Edit pre-generated email content directly in Google Sheets before a touch sends — the workflow reads from Sheets at send time, not from the original Gemini output. Chain from any QualMatic lead qualification template (e.g., Templates #5, #6, and #10) — send an HTTP POST request to the Section A webhook URL with leadName, leadEmail, propertyAddress, propertyDescription, and leadBackground to add a Hot lead automatically. Add a sixth touch by extending the Prepare Remaining Touches Code node with a sixth item and adding SEQUENCE_DAYS_6 to the Configuration node. Additional info Pre-generation pattern. All five emails are generated by Gemini at the start of the sequence and stored in Google Sheets. Subsequent touches read their pre-written content from Sheets rather than calling Gemini again — one API call delivers the entire 21-day sequence. This means the sequence continues reliably even if the Gemini API is temporarily unavailable on Day 14 or Day 21. Editable before sending. Because all five emails are stored in Google Sheets immediately after generation, the agent can review and edit any email before it sends. Open the Active Sequences sheet, find the lead's row, and edit the Touch Subject or Body columns — the workflow reads the updated content at send time. Reply detection via Thread ID. The workflow stores the Gmail Thread ID when Touch 1 sends. When a reply arrives, it is matched to the correct sequence by Thread ID — more reliable than email address matching, which can fail with aliases or forwarded addresses. Loop architecture. Touches 2–5 are processed by a Split In Batches loop — one batch per touch. Each batch waits its configured number of days, checks the current sequence status in Sheets, and sends only if the status still matches the expected previous touch. If a lead has replied or the sequence was manually stopped, the loop exits without sending further emails. Manual sequence stop. Set Status = Stopped in the Active Sequences sheet at any time. The loop's status check will detect this on the next iteration and exit cleanly — no further emails send. The agent does not need to modify the workflow. Previous QualMatic Templates. Any of the following QualMatic templates can be used as a source for the webhook in Section A. Template#5 https://n8n.io/workflows/17258-qualify-facebook-lead-ads-and-send-follow-ups-with-gemini-gmail-and-sheets/ Template#6 https://n8n.io/workflows/17409-qualify-inbound-real-estate-leads-from-gmail-with-gemini-and-hubspot/ Template#10 https://n8n.io/workflows/18329-match-new-property-listings-to-buyer-leads-with-gemini-gmail-and-sheets/. An n8n automation workflow template by Hassan.

By Swapnil Mandloi

Quick overview This workflow collects process-server attempt logs via an n8n form, updates a case tracker in n8n Data Tables, classifies field notes with OpenAI, escalates eligible cases for attorney approval in Slack, and drafts an affidavit saved to Google Drive and staged to a court e-filing HTTP API. How it works Receives a new service-attempt submission from an n8n Form trigger. Looks up the matching case in an n8n Data Table and computes the next attempt count, days until the SOL deadline, and whether alternate service is eligible. Uses OpenAI (gpt-4o-mini) to classify the attempt outcome notes into a single category (for example served successfully, wrong address, or no answer). If the case meets the alternate-service rule and is not already authorized or served, sends a Slack approval request to #case-approvals and waits for an attorney response. Sets the case status (served, alternate service authorized, pending/denied, or continuing attempts) and upserts the updated case record back into the n8n Data Table. If the case is ready to close (served or alternate service authorized), generates an affidavit-of-service text draft, saves it to Google Drive, and posts a draft filing payload to the court e-filing API via HTTP. Posts a one-line status update for the attempt to Slack in #case-tracking. Setup Create an n8n Data Table named process_serving_cases with columns used by the workflow (at least case_number, attempt_count, first_attempt_date, sol_deadline, alt_service_authorized, and case_status). Add OpenAI API credentials for the OpenAI chat model used by the text classifier. Add Slack credentials, and update the target channels (#case-approvals and #case-tracking) to match your workspace. Add Google Drive OAuth2 credentials and replace CASE_AFFIDAVITS_FOLDER_ID with the destination folder ID. Configure an HTTP Header Auth credential for the e-filing endpoint and replace the example URL (https://efile.courts.example/api/filings) and body fields to match your court/vendor API. Review and adjust the escalation rule in the attempt/SOL computation code (currently 3 attempts within 30 days, with SOL urgency at 14 days) to match your jurisdiction and policy. Requirements n8n Data Table: An active data table named process_serving_cases configured with the columns: case_number, attempt_count, first_attempt_date, sol_deadline, alt_service_authorized, and case_status. OpenAI API Key: Authenticated on the GPT-4o-mini for Outcome Classification chat model node (gpt-4o-mini, temperature 0) powering the Text Classifier. Slack Bot & User Token: Credentials configured for interactive attorney authorizations in Request Alt-Service Approval (sendAndWait in #case-approvals) and operational broadcasts in Post Case Status Update (#case-tracking). Google Drive OAuth2: Authenticated with write permissions for Save Affidavit to Drive targeting your dedicated storage directory (CASE_AFFIDAVITS_FOLDER_ID). Court E-Filing API Access: Header Auth credential or bearer API token configured for the Submit to Court E-Filing API HTTP Request node (POST /api/filings). Field Intake Data: Process server log submissions via the Form Trigger containing case_number, defendant, address, and unstructured outcome_notes. Customization Jurisdiction-Specific Diligence Rules: Adjust the escalation logic in Compute Attempt Count & SOL Countdown from the standard 3-attempt / 30-day threshold to reflect your state's statutory requirements for alternate/substitute service. Outcome Taxonomy Expansion: Add custom categories (such as hostile_dog, gated_community, or moved_no_forwarding) to Classify Attempt Outcome to match specific field server terminology. Attorney Approval Channel: Swap the Slack sendAndWait node with a Gmail sendAndWait step if your firm's managing attorneys prefer email-based sign-offs. Affidavit Legal Boilerplate: Customize the deterministic template in Generate Affidavit of Service Draft to include your county- or court-specific statutory declarations, notary blocks, or server certification statements. E-Filing Vendor Integration: Re-map the payload schema and endpoint in Submit to Court E-Filing API to match specific state court e-filing providers (e.g., Tyler Technologies Odyssey, One Legal, or InfoTrack). Additional info Statutory Compliance & Malpractice Protection: Alternate and substitute service methods require strict proof of due diligence; automated threshold tracking prevents premature alternate service applications and eliminates case dismissals caused by statute-of-limitations (SOL) lapses. Deterministic Document Generation: Affidavits of service are generated using deterministic code templates rather than LLM text generation to prevent factual hallucination, ensuring auditable accuracy for court submission. Fault Tolerance & Retries: All external network nodes (OpenAI model, Slack, Google Drive, and Court E-Filing HTTP Request) utilize onError=continueRegularOutput with 3 retries and a 2000 ms backoff to safeguard against temporary network drops. Data Security & Privacy: Field logs contain sensitive personal identifying information (PII), service addresses, and legal case numbers; access to the n8n Data Table, Drive archives, and notification channels should be strictly restricted to authorized legal ops personnel. API Cost Efficiency: Each attempt executes exactly one lightweight classification call via gpt-4o-mini, keeping operating expenses minimal while eliminating manual paralegal log reviews. An n8n automation workflow template by Swapnil Mandloi.

By Oneclick AI Squad

Quick overview This workflow runs on a schedule to health-check a web app, and when it detects an outage it gathers recent GitHub context and source files, asks Anthropic Claude to propose a fix, then creates a GitHub branch and pull request and notifies Slack via an incoming webhook. How it works Runs every 2 minutes on a schedule and requests the configured health-check URL. Evaluates the HTTP response against the expected status code and stops if the app is healthy. When unhealthy, fetches recent commits and GitHub Actions workflow runs for the configured repository and branch. Selects a small set of candidate source files and retrieves their contents from GitHub. Sends the outage details, recent GitHub context, and fetched file contents to Anthropic Claude to generate a root-cause diagnosis, PR text, and file change proposals. If Claude proposes changes, creates a new GitHub branch, commits the updated file contents to that branch, and opens a pull request into the base branch. Posts an incident message to Slack with the diagnosis and PR link, or posts a separate Slack message when no confident fix is proposed. Setup Create a GitHub API credential with access to read repository contents and create branches, commits, and pull requests, then set the repo owner/name and base branch in the configuration values. Add an HTTP Header Auth credential for the Anthropic API (and set the Anthropic model if needed). Replace the Slack incoming webhook URL in both Slack notification requests with your own Slack webhook endpoint. Update the health-check URL, expected status code, timeout, and max diagnostic file limit to match your application and desired sensitivity. An n8n automation workflow template by Oneclick AI Squad.

By Oneclick AI Squad

Quick overview This workflow crawls a website from its sitemap, extracts on-page content and links, uses Anthropic Claude to identify keywords and entities, stores everything as an SEO knowledge graph in Postgres, then posts crawl health stats to a Slack channel. How it works Triggers manually or on a weekly schedule to start a crawl using the configured seed URL, sitemap URL, page limit, and Slack channel. Fetches sitemap.xml, parses and deduplicates page URLs (optionally same-domain only), and batches them for processing up to the max page count. For each page URL, downloads the HTML and extracts the title, meta description, H1s, body text, and outbound links. Sends the page content to Anthropic Claude to return structured JSON for primary/secondary keywords, named entities, and topic categories. Writes the page node plus keyword, entity, and link relationships into Postgres tables (seo_pages, seo_keywords, seo_entities, seo_page_keywords, seo_page_entities, seo_page_links). After all pages are processed, queries Postgres for digital-twin stats (pages, unique keywords, entities, internal links, orphan pages) and posts the summary to Slack. Setup Create a Postgres database and add an n8n Postgres credential, then create the required tables and constraints used by the queries (seo_pages, seo_keywords, seo_entities, seo_page_keywords, seo_page_entities, seo_page_links, including the ON CONFLICT keys). Add an HTTP Header Auth credential for the Anthropic API (x-api-key) and ensure the selected model name in the config matches your Anthropic access. Add a Slack credential, set or create the target channel, and update seedUrl, sitemapUrl, maxPages, sameDomainOnly, anthropicModel, and slackChannel in the crawl configuration. An n8n automation workflow template by Oneclick AI Squad.

By Oneclick AI Squad

Quick overview This workflow exposes a header-authenticated webhook API that simulates the SEO traffic impact of merging, creating, or removing pages using baseline metrics from Postgres, then generates a validated strategy narrative with OpenAI and logs the run back to Postgres. How it works Receives a POST request on the /seo-what-if-simulate webhook using header authentication. Validates the request body (tenant/site, horizon, and merge/new/remove actions) and returns a structured 400 response if any rules fail. Queries Postgres for the latest per-page SEO metrics snapshot for the provided tenantId and siteId, then returns a structured 404 if no snapshot exists. Builds a baseline site model (totals, clusters, CTR calibration, and existing cannibalization) and runs merge, new-page, and removal simulations in parallel to calculate per-action deltas and risk flags. Aggregates all simulation results into a month-by-month forecast with expected/low/high click bands, verdict, confidence, per-action breakdown, and warnings. Uses OpenAI (via a LangChain LLM chain) to turn the computed forecast into an executive narrative and validates the LLM JSON output with a deterministic fallback if needed. Inserts the simulation run and full result into Postgres for auditing and responds to the webhook with a 200 JSON payload containing the forecast and narrative. Setup Create and configure the Postgres tables used by the workflow (seo_page_metrics as the source snapshot and seo_simulation_runs for logging). Add Postgres credentials in n8n that can read from seo_page_metrics and insert into seo_simulation_runs. Add an OpenAI credential (or compatible OpenAI API key) for the GPT-4.1 chat model used to generate the strategy narrative. Configure the webhook’s header-auth authentication in n8n and pass the same header from your calling application when invoking /seo-what-if-simulate. Ensure your seo_page_metrics snapshot data includes the expected columns (url, clicks, impressions, avg_position, backlinks, word_count, cluster_id, primary_keyword, internal_links_in) and is populated per tenantId/siteId before calling the API. An n8n automation workflow template by Oneclick AI Squad.

By Swapnil Mandloi

Quick overview This workflow receives scale calibration results via webhook, calculates NIST Handbook 44-style tolerance deviations, uses OpenAI to classify each device outcome, and routes compliant, out-of-tolerance, condemned, and invalid submissions to Google Drive, Gmail, HTTP state registry endpoints, and Google Sheets with a consolidated audit log. How it works Receives a POST webhook submission containing a visit ID, technician details, and an array of device calibration readings. Splits the payload into one item per device and calculates deviation percent, a tolerance band by device class, and a numeric status hint. Validates required fields and appends malformed readings to an “Invalid Submissions” tab in Google Sheets. Sends valid readings (including deviation math and technician notes) to an OpenAI text classifier to choose compliant, out_of_tolerance_fail, or condemned. For compliant devices, stores a certificate file in Google Drive and files a certification update to the state registry via HTTP. For out-of-tolerance devices, sends an urgent Gmail alert to the owner and opens a compliance case in Google Sheets. For condemned devices, submits a decommission notice to the state registry via HTTP and logs the decommission record in Google Sheets, then merges all outcomes and appends one consolidated audit-log row per visit in Google Sheets. Setup Create credentials for Google Sheets, Google Drive, Gmail, OpenAI, and an HTTP header-auth/API key for your state weights-and-measures registry endpoints. Update the webhook URL in your technician mobile app or source system to POST to this workflow’s production webhook path. Replace the placeholder state registry API URLs and ensure the request bodies match your jurisdiction’s required fields. Set the Google Drive destination folder and confirm the Google Sheets document and tab names (Invalid Submissions, Compliance Cases, Decommissioned Devices, Consolidated Audit Log). Update the Gmail recipient address (and any CC/BCC requirements) for out-of-tolerance notifications and run a test submission with multiple readings to validate each branch. Requirements Google Workspace Accounts: OAuth2 connections for Google Drive (certificate PDF archiving), Google Sheets (case tracking, decommission records, audit logs), and Gmail (dispatching urgent out-of-tolerance alerts). OpenAI API Key: Configured on the chat model supporting the Text Classifier (gpt-4.1-mini). State Regulatory API / Auth: HTTP Header Auth or API keys configured for the target weights-and-measures submission endpoints (File State Registry Update and Submit Decommission Notice). Upstream Mobile Payload: An incoming JSON webhook payload containing visit_id, technician, and an array of readings (including device_id, site, device_class, test_load, measured_reading, and technician_notes). Customization Full NIST HB44 Tolerance Tables: Expand the logic in Compute Tolerance Deviation from the demo 3-class structure to reflect your state's complete tolerance bands based on specific division sizes and capacities. On-Site Adjustment Handling: Introduce a 4th classification category (adjusted_in_field) if technicians can calibrate and re-verify equipment during the same site visit. Re-Test Routing: Add a fourth branch to Route By Compliance Status for equipment marked for scheduled follow-ups rather than immediate decommission or pass/fail outcomes. Automated Customer Summaries: Add an HTML-to-PDF generation step right after Append Consolidated Audit Log to automatically bundle all visit results into an email attachment for the facility manager. Regulatory CC Rules: Add mandatory state notification inboxes to the CC field in Send Urgent Out Of Tolerance Alert where local statutes require instant disclosure. Additional info Resilience & Retries: Every storage, notification, HTTP, and AI node includes continueRegularOutput with 3 retries on a 2-second backoff to prevent dropped visit data during temporary API drops. Filing Endpoints: The state registry URLs are placeholders. In states without public REST APIs for weights and measures, swap the HTTP nodes for direct email submissions or scheduled batch exports. Cost Footprint: Evaluates one lightweight classification call (gpt-4.1-mini) per tested scale—processing a 10-device site visit costs less than a penny in API usage. An n8n automation workflow template by Swapnil Mandloi.

By Atharva Ashtekar

Quick overview This workflow runs twice on weekdays (or manually) to read shipping-ready orders from a Google Sheets “Orders” tab, optionally fetch tracking details from ShipStation, and send a tracking email via Gmail, then records the sent timestamp back in the sheet to prevent duplicates. How it works Runs on a weekday schedule at 08:30 and 16:30 or starts manually. Loads workflow configuration and reads the Orders tab from Google Sheets (or uses built-in demo orders if the sheet isn’t connected). Filters for rows with Stage set to “Shipped” that have a confirmation timestamp and have not had a shipping email recorded yet. For each eligible order, uses the tracking number on the sheet if present, otherwise queries the ShipStation API for carrier, tracking number, and ship date when enabled. Stops the order if no tracking number is found, and separately surfaces any rows marked “Shipped” without a confirmation timestamp. Composes a shipping and installation email (including tracking details and installation info derived from product rules) and sends it via Gmail in test/live modes. Updates the Google Sheet row with carrier, tracking, ship date, and a “Ship email sent” timestamp so future runs skip it. Setup Add Google Sheets credentials and set the spreadsheet ID and tab name in the config so the workflow can read and update your Orders board. Add Gmail credentials and set the From name and optional Reply-To/test email values in the config. Ensure your Google Sheet includes the expected columns (for example Stage, Confirmation sent, Carrier, Tracking no., Shipped date, and Ship email sent) and that your team marks orders as “Shipped” in the Stage column. (Optional) Add ShipStation API credentials and enable ShipStation in the config to fetch tracking automatically when the sheet row doesn’t include it. Review preview/test/live mode settings in the config (TEST_RUN and TEST_EMAIL) before enabling the schedule. Customization Part 2 of a 2 parts Shopify, Etsy or Square - Order to Ship Engine. An n8n automation workflow template by Atharva Ashtekar.

By Atharva Ashtekar

Quick overview This workflow receives Shopify, Etsy, or Square order webhooks, normalizes them into a single order format, logs new orders to a Google Sheets “Orders” board, and sends a Gmail confirmation email with an estimated ship window based on SKU lead-time rules. How it works Receives an incoming order via an HTTP webhook endpoint. Detects whether the payload is from Shopify, Etsy, or Square, normalizes it into a common order structure, and rejects orders missing required details (including Square orders where a deposit hasn’t been captured). Loads existing orders from Google Sheets (or a built-in demo board when the sheet is not configured) and deduplicates by a unique “source|order-no” order key. Validates every line item against configured SKU rules and calculates a working-day ship window from the longest lead time plus buffers, holding orders with unknown SKUs when configured to do so. Writes a single-row order record to the Google Sheets board (or outputs a demo preview instead of writing when the board is not enabled). Sends a confirmation email via Gmail in test/live mode and then updates the Google Sheets row to mark the order as confirmed with a timestamp and “Confirmed” stage. Returns a JSON response to the calling storefront to stop webhook retries, including for held, rejected, duplicate, demo, or preview outcomes. Setup Create a Google Sheet with an “Orders” tab and column headings that match the workflow’s configured columns (including “Order key”, “Stage”, and “Confirmation sent”). Add Google Sheets credentials and set the target Spreadsheet ID and tab name in the config (then set BOARD_READY to true). Add Gmail credentials and set your sender details (From name and optional Reply-To) plus TEST_RUN/TEST_EMAIL to control preview, test, or live sending. Update PRODUCT_RULES to include every SKU you sell (and decide whether to hold orders with missing rules). Copy the production webhook URL and configure it as the order webhook endpoint in Shopify, Etsy, and/or Square. Customization Part 1 of a 2 parts Shopify, Etsy or Square - Order to Ship Engine. An n8n automation workflow template by Atharva Ashtekar.

By Ruth Olatunji

Quick overview This workflow receives a category and location via webhook, uses Apify to scrape recent Google Maps reviews, ranks businesses with unanswered low-star reviews, stores the opportunities in Supabase (Postgres), creates and shares a Google Sheet report, and returns the results and sheet link in the webhook response. How it works Receives a POST webhook request containing a business category and location (and optional rating/review count/result limits). Validates and normalizes the input parameters, then creates a “running” request record in Supabase (Postgres). Calls Apify’s Google Maps Reviews Scraper to fetch reviews for the requested search term and captures errors if the scrape fails. Groups the scraped reviews by business and identifies low-star (≤2) reviews that have no owner reply. Scores and ranks businesses that meet the minimum rating and review-count thresholds, then stores the top results as opportunities in Supabase. Creates a new Google Sheet, writes the headers and ranked opportunities into it, and shares the sheet publicly as read-only. Marks the request as completed in Supabase and responds to the webhook with the ranked results and the Google Sheet URL. Setup Add credentials for Supabase Postgres, an Apify HTTP Header Auth token (Authorization: Bearer ), Google Sheets OAuth, and Google Drive OAuth. Create the Supabase tables automation_requests and opportunities with the columns expected by the workflow (including UUID automation_requests.id and JSONB fields like input_json and opportunities.evidence). Configure the webhook URL in the calling app (for example, Lovable) and send at least category and location in the POST body (optionally min_rating, min_review_count, and max_results). Review the Google Drive sharing behavior before activation, since the workflow grants “anyone with the link” reader access to the created sheet. An n8n automation workflow template by Ruth Olatunji.

By Benzy

Quick overview This workflow runs daily, reads your n8n instance via the n8n API, checks every workflow’s configured error workflow handler for common silent failures, and sends a grouped status report to Telegram when issues are found (or always, if configured). How it works Runs every day at 08:00 using a schedule trigger. Sets runtime options such as the Telegram chat ID and whether to send an “all clear” message. Fetches all workflows from your instance using the n8n API. Analyzes each active, non-archived workflow that has an error workflow configured and verifies the referenced handler exists, has a published version, and contains an Error Trigger node. Builds an HTML-formatted report grouped by broken handler and listing the affected producer workflows, then decides whether a message should be sent. Sends the report to Telegram when problems exist (or when “alertWhenClean” is enabled), otherwise ends without posting. Setup Enable the n8n public API on your self-hosted instance and add n8n API credentials with permission to read workflows. Create a Telegram bot, add Telegram credentials in n8n, and paste your target chat ID into the Settings step. Review the schedule time and adjust the schedule trigger if you want a different cadence. Optionally set “alertWhenClean” to true if you want a daily confirmation message even when no issues are found. Requirements Self-hosted n8n with the public API enabled, and an n8n API credential with read access to workflows Customization Set alertWhenClean to true in the Settings node for a daily all clear instead of silence. An n8n automation workflow template by Benzy.

By Shisan Hua

Quick overview This workflow runs manually to validate 1–5 text-to-video briefs, optionally submits them to a video-generation provider API with idempotency keys, and outputs a review-ready manifest with job status and result URLs. How it works Starts when you manually run the workflow to process a configured batch of video briefs. Validates each brief (job ID format/uniqueness, prompt length, allowed duration, aspect ratio, and seed) and stops if any input is invalid. Expands the batch into per-brief requests that include a deterministic Idempotency-Key and the provider API base URL. If running in demo mode, generates offline fixture results with example video URLs and marks each job as completed. If running in live mode, sends one POST request per brief to the provider API using HTTP Header Auth and captures the full HTTP response. Classifies each live response (accepted, rejected, provider error, or ambiguous) and compiles a review manifest with job metadata, provider job IDs, and any result URLs. Setup Decide whether to run in demo mode (no credentials, no network calls) or live mode (real provider requests). For live mode, set providerBaseUrl to your HTTPS video-generation endpoint and set allowPaidProcessing=true after reviewing provider pricing. Create an n8n HTTP Header Auth credential with your provider API key/token and select it on the HTTP Request step. Update the configured briefs array to include 1–5 jobs with supported durationSeconds (5/6/8/10) and aspectRatio (16:9/9:16/1:1). Requirements An authorized video-generation API and an n8n HTTP Header Auth credential are required only for live mode. Customization Adapt the generic request and response fields to the provider contract; adjust supported durations, aspect ratios, and the batch limit after validating provider rules. Additional info Created by Shisan Hua, who works on Dola AI Video: https://www.dolai.video/. This workflow uses a generic authorized provider contract and does not claim that Dola AI Video exposes a public API. Demo mode is offline and makes no paid requests. An n8n automation workflow template by Shisan Hua.

By Michael Matthews

Quick overview This workflow receives a “job done” webhook and uses Twilio to send the customer a Google review request by SMS after a configurable delay, respecting quiet hours and preventing repeat requests by checking your Twilio message history. How it works Receives a POST webhook containing the customer’s phone number, name, and job details. Validates the input and settings, calculates a send time based on your delay and quiet hours, and immediately responds to the webhook with the scheduled send time or an error reason. If required details are missing (for example an invalid phone number or missing review link), sends an SMS to the owner via Twilio explaining why the request will not be started. Waits until the scheduled send time. Uses the Twilio API to look up your account and fetch recent outbound messages to that customer from your Twilio number within the repeat window. If an earlier text to that customer carried your review link (failed sends don't count), skips sending and texts the owner that it was skipped. If no prior ask is found, sends the review request SMS via Twilio. If Twilio refuses it, the owner gets a text with Twilio's reason; if it goes out, the owner gets a text unless owner updates are turned off. Setup Add a Twilio API credential (Account SID/Auth Token) and select it on all Twilio and Twilio HTTP Request steps in the workflow. In “Your settings”, set your Twilio phone number (From), owner cell number (To for updates), time zone, Google review link, and the review message template. Adjust behavior settings as needed (delay minutes, quiet hours, repeat-days window, and whether owner updates are enabled). Activate the workflow, copy the production webhook URL, and configure your field app/form/Zapier (or other system) to POST {phone, name, job} to it when a job is completed. Requirements A Twilio account with a number that can text your customers (in the US that means A2P 10DLC registration or a verified toll-free number) Your Google review link, from your Google Business Profile An n8n instance that can receive webhooks (Cloud or self-hosted) A field app, form, CRM or Zap that can send a POST request when a job is marked done Customization Change delay_minutes in Your settings to send sooner or later after the job (default 120 minutes) Rewrite review_text in Your settings; {name}, {business}, {job} and {link} are filled in for you Move quiet_start and quiet_end to match your hours (default 8 PM to 8 AM) Change repeat_days to ask repeat customers more or less often (default 90 days) Set owner_updates to false to hear only when an ask is skipped or fails. An n8n automation workflow template by Michael Matthews.