Workflow Templates

Use cases are many: Automate Gmail tasks such as sending, replying, labeling, deleting, and fetching emails — all with AI assistance. Perfect for YouTubers managing viewer emails, sales teams handling inquiries, freelancers responding to client requests, or professionals keeping their inbox organized. Good to know At time of writing, each Gemini request is billed per token. See Gemini Pricing for updated details. The workflow uses Gmail labels (e.g., youtube-viewers, sales-inquiry, meeting-request, potential-clients, collaboration-requests) for classification — make sure these exist in your Gmail account. How it works Chat Trigger**: You interact with the agent via a chat interface (webhook). AI Agent**: Gemini-powered assistant interprets your instructions (send, reply, label, delete, fetch emails). Email Actions**: Based on your request, the assistant uses Gmail tools to act on emails (Send, Reply, Label, Delete, Get Many). Contact Lookup**: If only a name is provided, the agent checks Google Sheets for the matching email address. If not found, it prompts you to add it. Memory**: A buffer memory stores chat context so the assistant can maintain continuity across multiple interactions. Labeling**: Emails can be auto-labeled for better organization (e.g., client inquiries, meeting requests). How to use Send commands like: “Reply to John’s email with a follow-up about the project.” “Label Sarah’s email as potential-client.” “Delete the latest spam email.” The Gmail Agent will handle the request instantly and keep everything logged properly. Requirements Gmail account connected with OAuth2 credentials Google Gemini API key for AI processing Google Sheets for contact management Pre-created Gmail labels for organization Customising this workflow Add new Gmail labels for your workflow (e.g., Invoices, Support Tickets). Connect to a CRM (e.g., HubSpot, Notion, or Airtable) for syncing email data. Enhance AI replies with dynamic templates stored in Google Sheets. Extend chat commands to include batch actions (e.g., “Archive all emails older than 30 days”).

How it works time trigger using the cron format, every weekday at 5pm gets CentralStationCRM people updates of today checks for tag "Outreach" if true, sends message on gmail (predefine in node) waits 7 days, checks for answers alerts user if an answer is there if not, repeats process with second mail How to set up get credentials for CentralStationCRM, Slack and GMail set up the respective nodes with the credentials define text for your automated mails test without wait nodes

Publish a Reel on a Facebook Page 🧠 Good to Know > Set up n8n self-hosted instance using https://tino.vn/vps-n8n?affid=388 > Use the code ==VPSN8N== for up to 39% off. This workflow automatically uploads and publishes Facebook Reels using data from Google Sheets and video files stored in Google Drive. It runs on a schedule (every 30 minutes by default) and can be fully customized for your posting routine. ⚙️ How It Works Google Sheets provides the content data — video file ID, caption, and optional links. Google Drive hosts the actual video file (.mp4 format). The workflow initializes an upload session with the Facebook Graph API, uploads the video, and publishes it as a Reel on your Page. Finally, it updates your Google Sheet and adds a comment under the published Reel with your affiliate or product link. How to Use Open the template Google Sheet or make a copy: 👉 Template Sheet Fill out each row with: File ID → the ID of your video file from Google Drive File name → optional Caption → your post caption Link Share → optional Link post → leave empty (it will be filled after posting) Ensure your video file: .mp4 format shared folder on Google Drive that’s accessible to your connected account Add your Facebook Page ID and Page Access Token to the “info” node. (Learn how to get these here: Facebook Reels Workflow Guide) 📋 Requirements n8n instance (Self-hosted recommended):** Set up a self-hosted instance using https://tino.vn/vps-n8n?affid=388 Use the code VPSN8N for up to 39% off. Facebook Page** with publishing permissions Page Access Token** (with pages_manage_posts, pages_read_engagement) Google Drive* and *Google Sheets** account connected to n8n Video files in .mp4 format, under the 1GB upload limit 🎨 Customizing This Workflow Change schedule:* Adjust the *Schedule Trigger** node (e.g., every 2 hours or only during business hours). Track post links:** Add a node to fetch the permalink_url from the Graph API and update it in your sheet. Auto-comment control:** Modify or remove the “Create comment post” node to suit your campaign style. Improve security:* Replace hardcoded tokens with *n8n credentials, **secrets, or a Data Table lookup. This structure keeps your automation scalable, secure, and easy to adapt for multi-page or multi-brand use.

Automatically Import Research Papers using DOI URL from Telegram to Zotero This workflow allows you to automatically import research papers into your Zotero library by simply sending a DOI link through Telegram. It fetches metadata from reliable sources such as Crossref, DataCite, and Unpaywall, enriches the bibliographic details, attaches the best available full-text PDF when possible, and generates a concise summary of the abstract using an LLM before sending it back to Telegram. ✨ Key Features Telegram Integration** – Send a DOI link via Telegram bot to trigger the workflow. DOI Parsing** – Automatically detects and extracts DOI or arXiv identifiers from user messages. Metadata Fetching* – Retrieves bibliographic information from *Crossref, **DataCite, and Unpaywall. Smart PDF Finder** – Locates the best available PDF (publisher link, open access, or arXiv). Zotero Integration** – Creates a Zotero parent item with complete metadata and attaches the PDF link when available. Abstract Summarization** – Uses a basic LLM chain to generate a short and clear summary of the abstract. Telegram Feedback** – Sends the title, URL, and abstract summary back to the user in Telegram. 🔑 Required Credentials Telegram API** – To connect the workflow with your Telegram bot. Zotero API Key** – To create and update items in your Zotero library. OpenRouter API Key** – To enable the LLM for generating abstract summaries. (Optional) Email for Unpaywall API requests (recommended for stable access). 💡 Benefits Save time by automating manual research paper imports. Ensure high-quality metadata by combining multiple sources (Crossref, DataCite, Unpaywall). Get instant summaries of abstracts directly in Telegram for quick understanding. Keep your Zotero library organized with accurate titles, abstracts, authors, and tags. Quickly attach available full-text PDFs without manual searching. Improve your academic workflow by managing references and summaries directly from Telegram.

The problem Ever attend a networking event and find yourself taking screenshots of people's LinkedIn? Sounds counter-intuitive because you are connecting on LinkedIn. But you find it hard to keep track of everyone you've met. You also don't want to miss diligently updating your CRM with details and insights. *The solution * There's no need for yet another app. Continue taking screenshots. Just share them on a 2-field only Google Form: screenshot + your quick notes about the person. Create a shortcut to the Google Form link on your phone homescreen. Voila! You have app-like access without the need for an app. Once you submit with just these 2 pieces of info, AI parses the image AND crafts a follow-up message. Within minutes! Just open your spreadsheet to have all that information consolidated - automatically - for your review. Promote yourself from do-er to manager. Who should use it? Anyone really. If you find yourself meeting people but want to be more meticulous or efficient staying on top, use this. How to set it up Time: ~10 minutes end-to-end. Import the provided workflow JSON in n8n. Connect credentials: Google Drive (read), Google Sheets (write), OpenAI. Configure key information: Google Sheets and relevant columns Configure Open AI models based on your cost/ efficiency requirements Confirm column headers in your Sheet match the variables (or update the variables). Test with one screenshot. Pro-tip: Add that Google Form link as a shortcut on your phone's home screen. Get app-like convenience without downloading yet another app.

Try It Out! This workflow builds a Telegram-based Solana (SOL/USDT) Multi-Timeframe AI Market Analyzer that automatically pulls live candlestick data for SOL/USDT, runs structured multi-timeframe technical analysis (1-minute, 5-minute, 1-hour) through an AI Agent, and posts a professional, JSON-structured analysis + trading recommendation straight to your Telegram chat. It combines on-chain / market data aggregation, LLM-driven interpretation, and instant Telegram reporting — giving you concise, actionable market intelligence every hour. How It Works Hourly Trigger – The workflow runs once per hour to pull fresh market data. Market Data Fetch – Three HTTP requests gather candlesticks from CryptoCompare: 1-minute (last 60 candles) 5-minute aggregate (last 60 aggregated candles) 1-hour (last 60 candles) Merge & Transcribe – The three feeds are merged and a lightweight code node extracts: symbol, current price, arrays for data_1m, data_5m, data_1h. AI Agent Analysis – The LLM (configured via your model node) receives the merged payload and runs a structured multi-timeframe technical analysis, returning a strict JSON report containing: Per-timeframe analysis (momentum, volume, S/R,MA, volatility) Market structure / confluence findings Trading recommendation (action, entry, stop, TPs, position sizing) A final disclaimer Parse AI Output – Extracts the JSON block from the agent’s reply and validates/parses it for downstream formatting. Telegram Reporting – Sends two nicely formatted Telegram messages: Multi-timeframe breakdown (1m / 5m / 1h) Market structure + Trading Recommendation (TPs, SL, position size, disclaimer) How to Use Import the workflow into your n8n workspace (or replicate the nodes shown in the JSON). Add credentials: CryptoCompare API Key — for reliable candlestick data. LLM model credentials — e.g., Google Gemini / OpenAI, configured in the LangChain/LM node. Telegram Bot Token & Chat ID — to send messages. (Optional) AFK Crypto API key if you want to enrich data with wallet info later. Node mapping & endpoints: Fetch_1m → GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60 Fetch_5m → GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60&aggregate=5 Fetch_1h → GET https://min-api.cryptocompare.com/data/v2/histohour?fsym=SOL&tsym=USDT&limit=60 Merge → combine the three responses into a single payload. Transcribe (code) → extract last close as current price and attach the arrays. AI Agent → pass the structured prompt (system message instructs exact JSON structure). Parse AI Output → extract the json ... block and JSON.parse it. Telegram nodes → format and send two messages (timeframes and recommendation). Adjust analysis frequency: default is hourly — change the Schedule Trigger node as desired. Deploy and activate: the workflow will post an AI-driven SOL/USDT market analysis to your Telegram hourly. (Optional) Extend This Workflow Add price / orderbook enrichment (e.g., AFK price endpoints or exchange orderbook) to improve context. Add wallet exposure checks (AFK wallet balances) to tailor position sizing suggestions. Store AI reports in Notion / Google Sheets for historical auditing and backtesting. Add alert filtering to only post when the LLM flags high-confidence signals or confluence across timeframes. Expose Telegram commands to request on-demand analysis (e.g., /analyze now 5m). Add risk management logic to convert LLM recommendation into automated orders (careful — requires manual review and stronger safety controls). Safety Mechanisms Explicit system prompt — forces AI to output only the exact JSON structure to avoid free-form text parsing errors. JSON parser node — validates the agent response and throws if malformed before any downstream action. Read-only market analysis — the workflow only reports by default (no auto-trading), reducing operational risk. Credentials gated — ensure LLM and Telegram credentials are stored securely in n8n. Disclaimer — every report includes a legal/financial disclaimer from the agent. Requirements CryptoCompare API Key (for minute/hour candlesticks) LLM model credentials (Google Gemini / OpenAI / other supported model in your LangChain node) Telegram Bot Token + Chat ID (where analysis messages are posted) Optional: AFK Crypto API key if you plan to add wallet/position context n8n instance with: HTTP Request, Code, Merge, LangChain/Agent, and Telegram nodes enabled AFK / External APIs Used CryptoCompare Candles: GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60 (1m) GET https://min-api.cryptocompare.com/data/v2/histominute?fsym=SOL&tsym=USDT&limit=60&aggregate=5 (5m) GET https://min-api.cryptocompare.com/data/v2/histohour?fsym=SOL&tsym=USDT&limit=60 (1h) Telegram Bot API – via n8n Telegram node. LLM / LangChain – your chosen LLM provider (configured in the workflow). Summary The Solana (SOL/USDT) Multi-Timeframe AI Market Analyzer (Telegram) gives you hourly, professional multi-timeframe technical analysis generated by an LLM agent using real candlestick data from CryptoCompare. It combines the speed of automated data collection with the structure and reasoning of an AI analyst, delivering clear trading recommendations and a timestamped analysis to your Telegram chat — ideal for traders who want reliable, concise market intelligence without manual charting. Our Website: https://afkcrypto.com/ Check our blogs: https://www.afkcrypto.com/blog

This workflow automates image processing using VLM Run, extracting signed URLs, downloading results, and distributing them via multiple channels (Google Drive & Telegram). ✅ Key Features Upload image files through a Form Trigger. Process images through two VLM Run agents simultaneously: Segmentation Agent → extracts objects. Detection Agent → generates bounding boxes. Webhooks capture completed results asynchronously. Code Node** extracts the full signed URL for secure downloading. Downloaded images are automatically: Uploaded to Google Drive Sent to a Telegram chat ⚙️ Workflow Flow User Uploads File → Form Trigger node VLM Run Agents → Segmentation & Detection agents Webhook Nodes → Receive processed results Code Node → Extract signed URLs Download Node → Retrieve processed images Distribution Nodes → Upload to Google Drive & Telegram 📌 Notes Ensure Google Drive OAuth2 credentials have upload permissions. Telegram Bot token and chat ID must be configured correctly. Regex in the Code Node is critical for capturing full signed URLs including query parameters. Workflow allows multi-channel sharing of images automatically. ⚠️ Community Node Disclaimer > This workflow uses VLM Run node

Task-based Assignee billing via Time Tracking This workflow automates billing by scanning a target Dartboard on schedule, aggregating time logs from completed tasks, cross‑referencing assignee rates in Google Sheets, calculating total pay, and updating the sheet with final billable hours and amounts. Who's it for Individuals, agencies, companies, and project managers automating payroll or client invoicing from task data. How to setup Link your Dart and Google accounts. Replace the dummy ID in the List tasks node with your actual target Dartboard ID. Set your preferred run frequency (e.g., Weekly). Create a Google Sheet with these exact headers: Name, HourlyRate, TotalHours, TotalPay, DateCalculated. Connect the Sheet nodes to your file. Pre-fill Name (matching Dart Assignees exactly) and HourlyRate in your Google Spreadsheet. Optional: Add a last header column in the sheet as a Status header to track if the bill is paid or pending. Customizing the workflow Choose your AI model for your AI time tracking and assignee scanner Use your own google sheet account and target spreadsheet document

Overview This n8n workflow automatically fetches the Forex Factory calendar for yesterday using Rapid API, then saves the data to a connected Google Sheet and sends Telegram alerts for high and medium impact events. It runs daily on schedule, collecting key fields such as currency, time, impact, and market indicators, and organizes them for easy tracking and analysis. Perfect for forex traders and analysts who need quick access to reliable market data from the previous day’s events. ✅ Tasks ⏰ Runs automatically every day 🌐 Fetches yesterday’s Forex Factory calendar via Rapid API 🧾 Collects key data fields: year, date, time, currency, impact, actual, forecast, previous 📊 Saves all records to Google Sheets for tracking and analysis 🚨 Sends Telegram alerts for high and medium impact events ⚙️ Keeps your market data updated and organized with no manual work required 🛠 How to Use 📄 Create a Google Spreadsheet Create a new spreadsheet in Google Sheets and add two sheets: High Impact and Low Impact. Connect it to your Google Sheets nodes in n8n. 🌐 Find the API on Rapid API Go to Rapid API and search for Forex Factory Scraper. Subscribe to the API to get your access key. 🔑 Connect Rapid API to n8n In your HTTP Request node, add the header below to authenticate your request: 💬 Add Your Telegram Chat ID In the Telegram node, paste your Chat ID to receive daily alerts for high-impact news. 🕒 Activate the Workflow Enable the Schedule Trigger to run daily. The workflow will automatically fetch yesterday’s Forex Factory calendar, save it to Google Sheets, and send Telegram notifications.

This automated n8n workflow streamlines invoice creation and payment reminders. It generates invoices on a monthly schedule and sends reminders for overdue payments, updating records in Google Sheets. Good to Know Supports monthly invoice generation and daily overdue checks Integrates with Google Sheets for data management Uses email notifications for invoice delivery and reminders Includes logging for tracking and auditing Features multiple reminder types based on overdue duration How It Works Invoice Creation Flow: Monthly Invoice Trigger** - Initiates workflow on a set monthly schedule Get Clients for Invoicing** - Reads client data from Google Sheet Filter Active Clients** - Filters out inactive clients Generate Invoice Data** - Creates invoice details in required format Save Invoice to Google Sheets** - Appends or updates invoice record in the sheet Send Invoice Email** - Sends the invoice to the client via email Log Invoice Creation** - Logs invoice creation for records/auditing Reminder Flow: Daily Payment Reminder Check** - Triggers workflow daily to check overdue invoices Get Overdue Invoices** - Reads overdue invoices from Google Sheet Filter Overdue Invoices** - Filters invoices still unpaid Calculate Reminder Type** - Calculates how many days overdue Switch Reminder Type** - Decides which type of reminder to send Send Gentle / Follow-up / Urgent / Final Notice** - Sends respective reminder email Update Reminder Log** - Updates reminder status in the sheet How to Use Import workflow into n8n Configure Google Sheets API for data access Set up email service for notifications Define monthly schedule for invoice trigger Test with sample client data and monitor reminders Adjust reminder thresholds as needed Requirements Access to Google Sheets API Email service configuration Scheduled trigger setup in n8n Sheet Columns: Client Name** Invoice ID** Amount** Due Date** Status** Reminder Type** Last Updated** Customizing This Workflow Modify invoice generation schedule Adjust reminder email templates Configure custom Google Sheet columns Set custom overdue thresholds Integrate additional notification methods

Automated Multi-Bank Balance Sync to BigQuery This workflow automatically fetches balances from multiple financial institutions (RBC, Amex, Wise, PayPal) using Plaid, maps them to QuickBooks account names, and loads structured records into Google BigQuery for analytics. Who’s it for? Finance teams, accountants, and data engineers managing consolidated bank reporting in Google BigQuery. How it works The Schedule Trigger runs weekly. Four Plaid API calls fetch balances from RBC, Amex, Wise, and PayPal. Each response splits out individual accounts and maps them to QuickBooks names. All accounts are merged into one dataset. The workflow structures the account data, generates UUIDs, and formats SQL inserts. BigQuery node uploads the finalized records. How to set up Add Plaid and Google BigQuery credentials, replace client IDs and secrets with variables, test each connection, and schedule the trigger for your reporting cadence.

Description Keep your internal knowledge base fresh and reliable with this automated FAQ freshness monitoring system. 🧠📅 This workflow tracks FAQ update dates in Notion, calculates SLA compliance, logs results in Google Sheets, and sends Slack alerts for outdated items. Perfect for documentation teams ensuring content accuracy and operational visibility across platforms. 🚀💬 What This Template Does 1️⃣ Triggers every Monday at 10:00 AM to start freshness checks. ⏰ 2️⃣ Fetches FAQ entries from your Notion database. 📚 3️⃣ Computes SLA status based on the last edited date (30-day threshold). 📆 4️⃣ Updates a Google Sheet with current FAQ details and freshness status. 📊 5️⃣ Filters out overdue FAQs that need review. 🔍 6️⃣ Aggregates all overdue items into one report. 🧾 7️⃣ Sends a consolidated Slack alert with direct Notion links and priority tags. 💬 Key Benefits ✅ Maintains documentation freshness across systems. ✅ Reduces support friction from outdated FAQs. ✅ Centralizes visibility with Google Sheets reporting. ✅ Notifies your team in real time via Slack. ✅ Enables SLA-based documentation governance. Features Weekly automated schedule (every Monday at 10 AM). Notion database integration for FAQ retrieval. SLA computation and overdue filtering logic. Google Sheets sync for audit logging. Slack notification for overdue FAQ alerts. Fully configurable thresholds and alerting logic. Requirements Notion API credentials with database read access. Google Sheets OAuth2 credentials with edit access. Slack Bot Token with chat:write permission. Environment variables : NOTION_FAQ_DATABASE_ID GOOGLE_SHEET_FAQ_ID SLACK_FAQ_ALERT_CHANNEL_ID Target Audience Knowledge management and documentation teams 🧾 SaaS product teams maintaining FAQ accuracy 💡 Support operations and customer success teams 💬 QA and compliance teams monitoring SLA adherence 📅 Step-by-Step Setup Instructions 1️⃣ Connect Notion credentials and set your FAQ database ID. 2️⃣ Create a Google Sheet with required headers (Title, lastEdited, slaStatus, etc.). 3️⃣ Add your Slack credentials and specify the alert channel ID. 4️⃣ Configure the cron schedule (0 10 * * 1) for Monday 10:00 AM checks. 5️⃣ Run once manually to verify credentials and mappings. 6️⃣ Activate for ongoing weekly freshness monitoring. ✅