by Soumya Sahu
This workflow acts as an automated engagement bot. It sends a Direct Message (DM) with a link or resource to any follower who replies to your post with a specific target keyword. Who is this for Ideal for creators and community managers who want to distribute resources (PDFs, links, invites) to their audience automatically without manually messaging each person. What it does It scans your notifications for new replies and applies a strict filter to ensure only the right people get messaged: Targeted:** It only monitors replies on the specific post you choose. Keyword Match:** Checks if the user's reply contains your specific trigger word (e.g., "Send"). Follower Check:** Verifies if the user is following you (if not, it skips them). Delivery:** Opens a chat conversation and sends your pre-set message. Engagement:** Automatically "Likes" the user's reply to confirm receipt. Anti-Spam:** Remembers processed replies so it never messages the same user twice for the same interaction. How to set up Configuration: Open the first node ("Configuration") and enter: BlueSky Credentials: Your Handle and App Password. Target Post URL: The full link to the specific BlueSky post you want to monitor. Trigger Keyword: The word users must type (e.g., "Template"). DM Message: The actual text/link to send them. Activate: Turn the workflow on. It runs every 30 minutes to batch-process new replies. 🚀 The BlueSky Growth Suite This workflow is part of a 3-part automation suite designed to help you grow on BlueSky: Part 1: Post Scheduler** (Manage content from Google Sheets) Part 2: Analytics Tracker** (Track likes/reposts back to Sheets) Part 3: Auto-DM Bot** (This template)
by MUHAMMAD SHAHEER
Who's It For AI developers, automation engineers, and teams building chatbots, AI agents, or workflows that process user input. Perfect for those concerned about security, compliance, and content safety. What It Does This workflow demonstrates all 9 guardrail types available in n8n's Guardrails node through real-world test cases. It provides a comprehensive safety testing suite that validates: Keyword blocking for profanity and banned terms Jailbreak detection to prevent prompt injection attacks NSFW content filtering for inappropriate material PII detection and sanitization for emails, phone numbers, and credit cards Secret key detection to catch leaked API keys and tokens Topical alignment to keep conversations on-topic URL whitelisting to block malicious domains Credential URL blocking to prevent URLs with embedded passwords Custom regex patterns for organization-specific rules (employee IDs, order numbers) Each test case flows through its corresponding guardrail node, with results formatted into clear pass/fail reports showing violations and sanitized text. How to Set Up Add your Groq API credentials (free tier works fine) Import the workflow Click "Test workflow" to run all 9 cases Review the formatted results to understand each guardrail's behavior Requirements n8n version 1.119.1 or later (for Guardrails node) Groq API account (free tier sufficient) Self-hosted instance (some guardrails use LLM-based detection) How to Customize Modify test cases in the "Test Cases Data" node to match your specific scenarios Adjust threshold values (0.0-1.0) for AI-based guardrails to fine-tune sensitivity Add or remove guardrails based on your security requirements Integrate individual guardrail nodes into your production workflows Use the sticky notes as reference documentation for implementation This is a plug-and-play educational template that serves as both a testing suite and implementation reference for building production-ready AI safety layers.
by Simone
Overview This workflow automates the process of merging multiple .xlsx files from a designated folder into a single, well-organized Excel workbook. Each input file is converted into its own sheet within the output file. Additionally, a summary sheet is generated at the beginning, providing a convenient overview of all merged files, including their original names and the number of records in each. This is particularly useful for consolidating reports, combining data from different sources, or archiving multiple spreadsheets into one manageable file. How It Works The workflow follows these key steps: Trigger: The process begins when you manually execute the workflow. Read Files: It reads all files ending with the .xlsx extension from the /n8n_files/ directory (ensure your volume is mapped correctly). Process Each File: The workflow iterates through each file one by one. For each file, it extracts the data from the first sheet. Collect and Clean Data: A custom code node gathers the data from all files. It cleans the data by removing any completely empty rows and prepares it for the final Excel generation. The original filename is used to name the new sheet. Generate Multi-Sheet Excel: The core logic resides in a code node that uses the xlsx library. It creates a new Excel workbook in memory, adds a sheet for each processed file, and populates it with the corresponding data. It also creates a "Summary" sheet that lists all the source files and their record counts. Save the Result: The final workbook is saved as a new .xlsx file in the /n8n_files/output/ directory with a timestamped filename (e.g., 合并文件_20250908T123000.xlsx). Setup & Prerequisites To use this workflow, you need to configure your n8n instance to allow and use the external xlsx npm module. Place Your Files: Put all the Excel files you want to merge into the folder that is mapped to /n8n_files/ in your n8n container. Enable External Module: Set the following environment variable for your n8n service in your docker-compose.yml file: environment: NODE_FUNCTION_ALLOW_EXTERNAL=xlsx Install the Module: You must build a custom Docker image for n8n that includes the xlsx library. In the same directory as your docker-compose.yml, create a file named Dockerfile. Add the following content to the Dockerfile: FROM n8nio/n8n:latest USER root RUN npm install xlsx USER node In your docker-compose.yml, replace the image: n8nio/n8n... line with build: . for the n8n service. Rebuild and restart your n8n container using docker-compose up --build -d. Nodes Used Manual Trigger: To start the workflow. Read Write File: To read source files and save the final output file. Split In Batches: To process files one by one. Extract From File: To read the data from each .xlsx file. Code: For custom JavaScript logic to process data and generate the final multi-sheet Excel file using the xlsx library.
by AI/ML API | D1m7asis
This n8n workflow turns Telegram into a personal language tutor. Users can choose between different learning modes — vocabulary, grammar, quiz, or mixed lessons — simply by adding a hashtag to their message. The bot processes requests with AI/ML API and sends back structured, interactive lessons in Telegram. 🚀 Features 📩 Telegram-based input with hashtag commands 🧠 Adaptive AI responses (vocabulary, grammar, quiz) 🔤 Pronunciation support in Latin transcription 📒 Grammar explanations with examples ❓ Custom quizzes with auto-feedback 💬 Supportive learning experience with motivational messages ⏳ Typing indicator for smoother UX 🛠 Setup Guide 📲 Create Telegram Bot Go to @BotFather Use /newbot → choose a name and username Save the bot token 🔐 Set Up Credentials in n8n Telegram API: Use your bot token AI/ML API: Add your API key under AI/ML account ⚙️ Configure the Workflow Import the JSON into n8n Update credentials (Telegram + AI/ML API) Activate the workflow 💬 Start Learning In Telegram, send a message with one of the supported hashtags: #vocabulary — learn new words #grammar — study rules with examples #quiz — get exercises Or just send plain text for a free-form AI response 🔍 Node Overview Telegram Trigger** → Listens for incoming messages Show Typing Indicator** → Displays “typing…” while processing Switch Node** → Routes message by hashtag (#vocabulary, #grammar, #quiz) Prompt Builder Nodes** → Create JSON payload for AI/ML API AI/ML API Node** → Generates the structured lesson Telegram Send** → Sends the formatted response back to the user 💡 Example Flow User Input: #vocabulary кукуруза Bot Output: Кукуруза (Kukurúza) — Corn Pronunciation: koo-koo-ROO-zah Sentence: Я люблю есть кукурузу на гриле. I love eating grilled corn. 👉 Try to write your own sentence with “кукуруза”!
by Robert Breen
Capture new Jotform submissions and instantly create items on a Monday.com board with mapped columns (email, date, dropdowns, instructions, etc.). 🛠️ Setup — Jotform (simple) Add your Jotform API key (Jotform Account → Settings → API → Create Key). Create your form template in Jotform (use fields like Name, Email, Start Date, Engagement Type, Campaign Type, Instructions). In n8n, open the Jotform Trigger node and choose your Jotform template/form from the dropdown. That’s it. 🛠️ Setup — Monday.com In Monday.com, generate an API token (Admin/Developers → API). In n8n → Credentials → New → Monday.com, paste your API token. Identify and set: Board ID (from your board URL or via node “List” operations) Group ID (e.g., topics) Column IDs that match your board (examples used by this workflow): text_mkvdj8v3 → Email (Text) date_mkvdg4aa → Start Date (Date) dropdown_mkvdjwra → Engagement Type (Dropdown) dropdown_mkvdd9v3 → Campaign Type (Dropdown) text_mkvd2md9 → Campaign Type (as Text label) text_mkvd1bj2 → Instructions (Text) text_mkvd5w3y → Domain (Text) Update the label → ID mappings inside the Monday.com node if your dropdown IDs differ (e.g., Engagement A → 1, Engagement B → 2). ✅ Notes (best practices) No secrets in nodes: store tokens in n8n Credentials. Use the included Sticky Notes for quick reference inside the workflow. Test once in Jotform to see the payload flow into Monday. 📬 Contact Need help customizing this (e.g., extra fields, file uploads, or routing by campaign)? 📧 rbreen@ynteractive.com 🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/ 🌐 ynteractive.com — https://ynteractive.com
by System Admin
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by System Admin
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by System Admin
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by System Admin
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