Workflow Templates

🤖 Instagram Automation Suite: AI Chatbot & Content Powerhouse Workflow Overview This cutting-edge n8n workflow is a comprehensive automation solution designed to streamline various Instagram operations. It combines an intelligent AI chatbot for direct message management, automated user following, and an advanced content generation system, all integrated to enhance your Instagram presence and efficiency. This workflow automatically: Manages Instagram Direct Messages via Telegram Chatbot: Listens for new messages on Telegram. Routes messages from a specific Instagram user (Wolf23000) for processing. Utilizes an AI agent (powered by OpenRouter's cutting-edge models) to determine the intent of the message (e.g., chat back, run an Instagram-related action like getting profile info, posting, or following). Sends AI-generated responses back to the user via Telegram. Automates Instagram User Following: Scheduled to run at regular intervals (hourly). Processes a list of usernames (likely from a Google Sheet, though not explicitly shown in the provided JSON, it's a common pattern for "Auto Follow users from sheet" sticky note). Initiates following actions on Instagram for the specified users. Generates & Schedules Instagram Posts: Scheduled to run monthly. Leverages an AI agent (powered by OpenRouter) to generate 30 or 31 Instagram post ideas for the current month, based on a predefined "Instagram personality profile." Each post idea includes an imagePrompt (for AI image generation), a caption with emojis and hashtags, and a scheduledDate. Refines these post ideas by enhancing the imagePrompt to be more vivid and detailed for AI image generation, and polishing the caption for optimal engagement. Updates a Google Sheet ("posts generation plan") with the generated content, including the enhanced image prompts and the resulting image URLs (presumably from a separate image generation step not fully detailed in the provided JSON, but implied by image_url updates). Key Benefits Intelligent DM Management: Automate responses and actions for Instagram direct messages, ensuring timely and relevant interactions without manual effort. Effortless Audience Growth: Automatically follow target users, expanding your reach and potential engagement on Instagram. AI-Powered Content Creation: Generate a full month's worth of diverse, engaging Instagram post ideas tailored to a specific personality, complete with image prompts and captions. Content Optimization: Automatically enhance image prompts for better AI image generation and refine captions for maximum impact. Time-Saving: Significantly reduce the manual workload associated with Instagram management, from direct messages to content planning and execution. Consistent Brand Voice: Maintain a consistent and engaging presence on Instagram with AI-generated content aligned with your defined personality. Setup Requirements To set up and run this workflow, you'll need the following: n8n Installation: Install n8n (cloud or self-hosted). The latest stable version, as of July 2025, is v1.101.1. Import the workflow configuration. Configure API credentials for all integrated services. Set up scheduling preferences for continuous operation. System Requirements for Self-Hosting: A modern multi-core processor (2 cores minimum, 4 recommended), 2 GB RAM (4 GB or more recommended), and 20 GB of free SSD storage. Node.js version 16 or later (18.x LTS recommended) is required. PostgreSQL is the recommended database for production. Telegram API Access: Create a Telegram bot via BotFather and obtain your API token. Configure the Telegram Trigger node with your bot's API credentials to receive messages. Pricing: Telegram's API is free to use. OpenRouter API Access: Create an OpenRouter account and generate an API key. This key ({{your open router api key }} as seen in the code) is used to access their chat models (e.g., google/gemini-2.5-flash-preview) for AI agent operations. Pricing: OpenRouter offers a variety of models with different pricing structures, including some free models like DeepSeek R1. Most models operate on a pay-per-usage basis, with costs clearly displayed for each model and prompt. Instagram Session ID: You'll need a valid Instagram session ID ({{ your instagram session ID }} as seen in the code) for the workflow to interact with Instagram. This usually involves extracting it from your browser's cookies after logging into Instagram. Caution: Instagram's terms of service generally prohibit automated interactions, and using session IDs for scraping or automation can lead to account suspension. Use with extreme caution and at your own risk. Apify token setup: *You'll need to replace {{ your apify token }} with you apify token in https requests Google Sheets Credentials: A Google Cloud API key with access to Google Sheets. Set up OAuth2 authentication in n8n for read/write access to your "posts generation plan" spreadsheet (Document ID: 1XHNwAXR4USThaAzX1Y6M5PF2P8WqCBU8mi34FBLkV6M). This sheet is used to store and manage generated post ideas. Pricing: The Google Sheets API is generally free for most common use cases, with generous per-minute quotas (300 read and 300 write requests per minute per project, 60 per user per project). No additional charges are incurred for exceeding these limits. https://docs.google.com/spreadsheets/d/1Ze5SC1g6Q5VzMAKYx0zmqlT00Db1HOchUth1jrPyM2Y/edit?usp=sharing https://docs.google.com/spreadsheets/d/1XHNwAXR4USThaAzX1Y6M5PF2P8WqCBU8mi34FBLkV6M/edit?usp=sharing Predefined Instagram Personality JSON: The workflow relies on a detailed JSON object defining an "Instagram personality" (e.g., user_id, username, full_name, bio, content_preferences, personality_traits, unfulancer_attributes). This JSON needs to be correctly set within the Code nodes (Variables, Variables1, Variables2) to guide the AI content generation. Workflow Architecture [Telegram New Message Trigger] ⬇️ [Variables (Set OpenRouter API Key, Instagram Personality, Session ID)] ⬇️ [Switch (Filter messages from 'Wolf23000' and ensure message text exists)] ⬇️ [Edit Fields (Extract message text)] ⬇️ [AI Agent (Determine action based on message intent)] ⬇️ [Structured Output Parser (Parse AI agent's JSON output)] ⬇️ [Switch1 (Route based on AI agent's determined action: chat_back, run_agent, get_instagram_profile)] ⬇️ ┌─────────────┬─────────────┬─────────────┐ │ │ │ │ ▼ ▼ ▼ ▼ [Send a text message1 (Chat back)] [Send a text message (Run agent confirmation)] [Send a text message2 (Get profile confirmation)] ▲ │ [Schedule Trigger (Hourly for Instagram follow)] ⬇️ [Variables (Set OpenRouter API Key, Instagram Personality, Session ID)] ⬇️ [Code (Prepare usernames for following)] ⬇️ [Code1 (Process followed usernames)] ⬇️ [Schedule Trigger2 (Monthly for Instagram post generation)] ⬇️ [AI Agent1 (Generate monthly Instagram post ideas)] ⬇️ [OpenRouter Chat Model (AI Model for content generation)] ⬇️ [Code2 (Parse AI agent's JSON output)] ⬇️ [Schedule Trigger3 (Daily for post generation refinement and auto-posting)] ⬇️ [AI Agent2 (Enhance image prompts and captions)] ⬇️ [OpenRouter Chat Model2 (AI Model for prompt refinement)] ⬇️ [Update row in sheet1 (Update Google Sheet with enhanced content)] ⬇️ [Get row(s) in sheet2 (Retrieve data from Google Sheet)] Connect With Me Exploring AI-Powered Social Media Automation? 📧 Email: mohamedgb00714@gmail.com 💼 LinkedIn: Mohamed el Hadi Msaid Supercharge your Instagram presence with intelligent automation and AI-driven content\! 🚀

This automated n8n workflow transforms uploaded radiology images into professional, patient-friendly PDF reports. It uses AI-powered image analysis to interpret medical scans, simplify technical terms, and produce clear explanations. The reports are formatted, converted to PDF, stored in a database, and sent directly to patients via email, ensuring both accuracy and accessibility. 🏥 Workflow Overview: Simple Process Flow: Upload Image → 2. AI Analysis → 3. Generate Report → 4. Send to Patient 🔧 How It Works: Webhook Trigger - Receives image uploads via POST request Extract Image Data - Processes patient info and image data AI Image Analysis - Uses GPT-4 Vision to analyze the radiology image Process Analysis - Structures the AI response into readable sections Generate PDF Report - Creates a beautiful HTML report Convert to PDF - Converts HTML to downloadable PDF Save to Database - Logs all reports in Google Sheets Email Patient - Sends the report via email Return Response - Confirms successful processing 📊 Key Features: AI-Powered Analysis** using GPT-4 Vision Patient-Friendly Language** (no medical jargon) Professional PDF Reports** with clear sections Email Delivery** with report attachment Database Logging** for record keeping Simple Webhook Interface** for easy integration 🚀 Usage Example: Send POST request to webhook with: { "patient_name": "John Smith", "patient_id": "P12345", "scan_type": "X-Ray", "body_part": "Chest", "image_url": "https://example.com/xray.jpg", "doctor_name": "Dr. Johnson", "patient_email": "john@email.com" } ⚙️ Required Setup: OpenAI API - For GPT-4 Vision image analysis PDF Conversion Service - HTML to PDF converter Gmail Account - For sending reports Google Sheets - For logging reports Replace YOUR_REPORTS_SHEET_ID with your actual sheet ID Want a tailored workflow for your business? Our experts can craft it quickly Contact our team

📌 Title (SEO-Friendly) Automate Facebook Messenger orders to Google Sheets and Google Calendar Introduction This workflow automates Facebook Messenger order management by connecting your Facebook Page with Google Sheets and Google Calendar. It’s designed to help small businesses save time, reduce errors, and streamline order-taking. Every time a customer messages your page, they receive a structured order form, their responses are parsed, and the details are saved directly to Google Sheets. The same workflow also creates a Google Calendar event, ensuring you never miss a delivery or pickup schedule. Who’s It For Small businesses** selling products through Facebook Messenger. Entrepreneurs** who want to eliminate manual order-taking. Teams** that need a centralized order tracker (Google Sheets) and automatic reminders (Google Calendar). How It Works Listen to incoming messages on Facebook Messenger. Send an automated greeting and order form to the customer. Parse their responses (items, quantity, payment method, etc.). Save order details into Google Sheets for easy tracking. Create a matching Google Calendar event for the order date/time. Send a confirmation message and an optional upsell suggestion. Requirements Facebook Page** with Messenger enabled. Meta for Developers account** to create a Facebook App and generate a Page Access Token. Google Sheets** account with a spreadsheet containing the following columns: Date, Customer Name, Order Details, Payment Method, Order Status, Notes Google Calendar** account for order scheduling. n8n instance** (cloud or self-hosted). 💡 Security Best Practice: Store your Page Access Token and Google credentials in n8n Credentials (not hardcoded in nodes). Setup Instructions 1. Facebook Messenger Connection Go to Meta for Developers. Create a Messenger App and generate a Page Access Token. Copy the Webhook URL from your n8n Webhook Trigger node. Add the webhook URL and verify it in your Facebook Page settings. 2. Google Sheets Setup Create a new spreadsheet named Messenger Orders. Add columns: Date, Customer Name, Order Details, Payment Method, Order Status, Notes. Share the sheet with the Google account connected in n8n. 3. Google Calendar Setup Connect your Google Calendar credentials in n8n. Select the calendar where orders should be added. 4. Import & Configure Workflow Download this workflow template. Replace placeholders ({{YOUR_PAGE_ACCESS_TOKEN}}, {{YOUR_GOOGLE_SHEET_ID}}, etc.). Test by sending a message to your Facebook Page. Customization Personalize messages** in the Messenger node (greeting, upsell suggestions). Add extra fields such as delivery address or contact number to both the form and the Google Sheet. Extend the workflow by adding Telegram, Email, or SMS notifications for customers or staff. Use Filter nodes to route VIP orders or high-value purchases to a separate workflow. ⚡ Final Flow: Facebook Messenger → Order Form → Google Sheets → Google Calendar → Customer Confirmation 💬 Call to Action: Clone this workflow, connect your accounts, and start automating your Messenger orders in minutes!

How it works This workflow automates the handling of new lead responses received in Gmail. It captures emails with a specific label, analyzes the message using AI to determine sentiment, intent, urgency, next action, and priority, and then decides whether follow-up is needed. If required, it creates tasks in HubSpot, notifies the sales team via Slack, and logs all details into Google Sheets for tracking. Step-by-step Trigger on New Lead Email Workflow starts whenever a new email with a defined Gmail label arrives. Captures the sender’s email, subject, message snippet, and timestamp. Normalize Email Data Standardizes Gmail fields into structured values: leadEmail (sender’s address) subject (email subject) message (email content snippet) source (Gmail) receivedAt (timestamp) AI-Powered Lead Analysis Uses OpenAI to analyze the lead’s message. Extracts: Sentiment (Positive / Neutral / Negative) Intent (Interested, Not Interested, Needs Info, Ready to Buy, Objection) Urgency (High / Medium / Low) Next Action (Call, Email, Demo, Quote, No Action) Summary (1–2 sentence description) Priority (Hot / Warm / Cold) Parsed results are merged with the original email data. Flags are added: needsFollowUp (true/false) isHighPriority (true/false) Decision: Needs Follow-Up? If AI suggests a follow-up action, the workflow continues. Otherwise, the process stops here. Create HubSpot Task Automatically creates a HubSpot CRM task for the sales team. Task includes email subject, body, and lead details. Notify Sales Team on Slack Sends a formatted message to Slack with key lead insights: Summary Lead email Priority Urgency Date of analysis Log Lead Data to Google Sheets Appends structured data to Google Sheets for record-keeping. Stores all fields: Email, Date, Subject, Message, Sentiment, Intent, Urgency, Next Action, Summary, and Priority. Why use this? Automates lead triage directly from Gmail. Saves time by using AI-powered analysis instead of manual review. Ensures no potential lead is missed by logging into Google Sheets. Provides instant sales team alerts on high-priority leads. Integrates seamlessly with HubSpot CRM for structured follow-up. Keeps your sales pipeline efficient, organized, and proactive.

Who’s it for Women creators, homemakers-turned-entrepreneurs, and feminine lifestyle brands who want a graceful, low-lift way to keep an eye on competitor content and spark weekly ideas. What it does On a weekly schedule, this workflow crawls your competitor URLs with Firecrawl (HTTP Request), summarizes each page with OpenAI, brainstorms carousel/pin ideas with Gemini, appends results to Google Sheets (Date, URL, Title, Summary, Ideas), and sends you a single email digest (optional Telegram alert). It includes basic error notifications and a setup-friendly config node. Requirements HTTP credentials** for Firecrawl, OpenAI, and Gemini (no keys in nodes) Google Sheets** OAuth credential A Sheets document with a target sheet/range (e.g., Digest!A:F) (Optional) Telegram bot + chat ID How to set up Open Set: Configuration (edit me) and fill: competitorUrls (one per line), sheetsSpreadsheetId, sheetsRange, ownerEmail, emailTo, geminiModel, openaiModel Attach credentials to the HTTP and Sheets nodes. Test by switching Cron to Every minute, then revert to weekly. How it works Cron → Firecrawl (per URL) → Normalize → OpenAI (summary) + Gemini (ideas) → Merge → Compile Row → Google Sheets append → Build one digest → Email (+ optional Telegram). How to customize Add/remove competitors or change the weekly send time. Tweak the OpenAI/Gemini prompts for your brand voice. Expand columns in Sheets (e.g., category, tone, CTA). Swap email/Telegram for Slack/Notion, or add persistent logs.

Research meeting attendees and prepare daily agenda in Slack This workflow automatically researches your meeting attendees every morning and sends you a comprehensive brief in Slack with context about who you're meeting, their company, and key talking points. Who's it for Sales professionals who need quick context before meetings Executives with packed calendars who need meeting preparation Customer success teams managing multiple client relationships Account managers preparing for client calls Business development teams researching prospects Anyone who wants to be better prepared for their daily meetings How it works Daily Trigger: Runs every weekday morning at 6 AM (customizable) to analyze your Google Calendar Calendar Analysis: Fetches all meetings scheduled for today and filters for external meetings (those with attendees other than yourself) AI-Powered Research: For each external meeting, an AI agent researches attendees using multiple sources: Searches your CRM (Attio) for existing contact information Queries Gmail history for past email interactions Searches past calendar events for previous meetings with attendees Performs web searches for recent news about attendees and their companies Retrieves company data from Apollo.io including industry, size, and technologies CRM Updates: Automatically creates new contact records in Attio for unknown attendees and adds meeting preparation notes to existing contacts Brief Generation: Compiles all research into a scannable, actionable meeting brief with key talking points Slack Delivery: Sends the formatted brief to your designated Slack channel for easy mobile access Setup requirements Google Calendar** OAuth2 connection (for fetching meetings) Slack** workspace with bot permissions (for receiving briefs) Gmail** OAuth2 connection (for email history search) OpenRouter** API key (for AI processing) Attio CRM** account and API token (optional - for contact management) Apollo.io** API key (optional - for company research) Anthropic** API key (optional - for advanced web search) How to customize Adjust Schedule: Modify the Schedule Trigger node to run at your preferred time - change from 6 AM to whenever works best for your schedule Customize Research Sources: Remove CRM integration if you don't use Attio Remove Apollo.io if you don't need company research Add additional research tools as needed Modify Output Format: Edit the prompt in "Format Daily Meeting Brief" node to change how the information is structured and presented Change Delivery Method: Replace Slack with Microsoft Teams, email, or Discord Add multiple delivery channels if needed Send to different channels based on meeting type Filter Meetings: Adjust the filtering logic to include/exclude certain types of meetings based on keywords, attendees, or calendar properties Advanced customization Add VIP alerts**: Create special handling for meetings with executives or key clients Include preparation documents**: Automatically attach relevant files from Google Drive Time zone handling**: Adjust for meetings across different time zones Language support**: Modify prompts to generate briefs in different languages

Zoho CRM → AI‑Generated Competitive Battle Card This workflow automatically analyzes competitor websites, which inseted in description field and generates a clean, structured AI‑powered Battle Card for every new Zoho CRM deal. It reads the competitor URL from the deal Description, scrapes the site, runs an AI analysis pipeline and updates the deal with pricing, differentiators, pros/cons and a concise sales battle summary — all fully automated. Quick Implementation Steps Add Zoho CRM + Gmail OAuth2 + AI API credentials. Import workflow into n8n. create a new deal in zoho CRM. While creating Deal,Add a competitor URL inside the Zoho deal Description. Activate the workflow. Wait 5 minutes → Deal updates with AI‑generated Battle Card. What It Does This workflow removes the manual effort of researching competitors during a sales cycle. Every time a new deal is created, it checks the Description field for a competitor name and website. After validating both, it automatically fetches the competitor webpage and feeds the content into an AI analysis pipeline powered by LangChain. The AI transforms the messy, unstructured webpage HTML into a readable, structured and ready‑to‑use Battle Card — including pricing overview, differentiating features, advantages, disadvantages and a compact sales battle summary. This data is pushed directly into the Deal Description and emailed to the sales team. No web research, no copy‑pasting, no manual formatting — the AI does everything. Who’s It For Sales teams wanting fast competitor intelligence. SDR/BDR teams prepping before first calls. Pre‑sales engineers making pitch notes. Founders/Product teams monitoring competitor positioning. Agencies building automation for CRM users. Requirements n8n instance Zoho CRM OAuth2 credentials Gmail OAuth2 credentials AI model provider API key (Gemini / OpenAI / Claude — interchangeable) Deals containing a competitor name + competitor URL [Must Have] How It Works & Setup Step 1 — Cron Trigger Runs every 5 minutes → pulls newly created deals and last run time. Step 2 — Fetch Deals Retrieves deals sorted by Created_Time. Step 3 — Identify New Deals Filters deals created after the last workflow run. Step 4 — Validate Deal Description Ensures the Description has: Competitor name Competitor website URL Step 5 — Extract Competitor Info Regex identifies and extracts the name + first valid URL in the Description. Step 6 — Scrape Competitor Website HTTP Request downloads the competitor webpage’s HTML. Step 7 — AI‑Generated Battle Card Creation The AI pipeline (LangChain + your chosen LLM) transforms HTML into a structured JSON output containing: Pricing Summary Key Features Pros Cons Battle Summary Competitor Name Step 8 — Update Zoho Deal The script saves the formatted AI Battle Card directly into the Deal Description. Step 9 — Notify Sales Gmail node sends a summary email to the sales team. How to Customize Nodes Change the AI Output Edit LangChain prompt to: Add SWOT Include pricing tiers Include objections Add competitor positioning Add risk scoring Change Where Battle Card Is Stored Modify the Zoho Update node to store data in: Notes Custom fields Attachments Tags Tasks Email Customization Update subject, body, recipients, etc. Filtering Logic Modify filters to: Only process specific deal stages Only process certain pipelines Ignore internal test deals Add‑Ons (Optional Enhancements) Auto‑generate a PDF Battle Card and attach it to the deal. Send Battle Cards to Slack, Teams, or a WhatsApp bot. Store all Battle Cards in Notion, Airtable, or Google Sheets. Add a competitor scoring system (price, features, risk level). Build a weekly digest of all competitors analyzed. Use Case Examples Instant competitor breakdown when a new lead or deal is created. Rapid sales call preparation with AI summarizing the competition. Automated enrichment of CRM records with meaningful intelligence. Internal competitive intelligence dashboards fed by AI outputs. Pitch deck automation where Battle Cards update slides automatically. There are many more possible use cases depending on your CRM setup and AI strategy. Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | No Battle Card generated | No URL found in Description | Add valid http/https competitor URL | | Deal skipped | Time filtering excluded it | Adjust lookback window in code | | AI output incomplete | HTML unreadable or blocked | Try different competitor URL | | Zoho update fails | OAuth scope missing | Reconnect Zoho with full CRM access | | Email not sent | Gmail OAuth expired | Reconnect Gmail | | AI output wrong format | Prompt mismatched | Update output schema and prompt | Need Help? If you need help customizing prompts, enhancing automations or building full‑scale AI workflows, then our n8n automation developers at WeblineIndia can support: AI automations LangChain pipelines CRM integrations n8n workflow development Competitive intelligence tooling And so much more.

Classify YouTube Trends and Generate Email Summaries with GPT-4 and Gmail Monitor YouTube channels, fetch stats, classify videos as viral (≥ 1000 likes) or normal, and auto‑generate LinkedIn/email summaries with GPT‑4. Deliver via Gmail or SMTP. Clear node names, examples, and auditable fields. 🎯 Overview This template monitors YouTube channels via RSS or the YouTube Data API, retrieves video stats, classifies each video as viral (≥ 1000 likes) or normal, and produces concise LinkedIn/email summaries with OpenAI (GPT‑4 family). It can send a compact weekly briefing via Gmail (OAuth2) or SMTP. Built for creators, marketing teams, and agencies who want automated trend alerts and ready‑to‑use content. This screenshot shows the Gmail-ready weekly briefing generated by the Generate Weekly Briefing (HTML) node in my YouTube Trend Detector workflow, confirming the end-to-end pipeline: RSS/API → stats → like-based classification (≥ 1000 = viral) → LLM summaries → HTML email. 🧭 How It Works (Node Map) Manual Run – ad‑hoc execution Set Channel IDs – provide one or more YouTube channelId values Split Channels – process channels one by one Fetch Latest Videos (RSS) – pull recent uploads via channel RSS Filter: Published in Last 72h – only recent items are kept Get Video Stats (YouTube API) – request snippet,statistics for likes and details Classify by Likes (Code) – sets classification to viral or normal Branch: Normal / Branch: Viral – separate LLM prompts per relevance Write Post (Normal / Viral) – generate LinkedIn‑style notes via OpenAI Aggregate Posts for Briefing – merge all texts into one block Generate Weekly Briefing (HTML) – produce a Gmail‑robust HTML email via GPT Send Weekly Briefing (Gmail/SMTP) – deliver briefing (you set recipients) ⚙️ Quick Start (≈ 3 minutes) Import the sanitized JSON into n8n (Menu → Import). Create credentials (use exact names): YouTube_API_Key — Generic credential (field: apiKey) OpenAi account — OpenAI API Key Gmail account (OAuth2) or SMTP_Default (SMTP) Configure channels: In Set Channel IDs, list your YouTube channelId values (e.g., UC…). Set recipients: In Send Weekly Briefing, add your target email(s). Test: Run Execute Workflow and review outputs from the LLM and send nodes. 🔑 Required Credentials YouTube_API_Key** — YouTube Data API v3 key (field apiKey) OpenAi account** — OpenAI API key for LLM nodes Gmail account* (OAuth2, recommended) *or* *SMTP_Default** (server/port/TLS + app password if 2FA) 🧩 Key Parameters & Adjustments Viral threshold:** In Classify by Likes (Code) → const THRESHOLD = 1000; YouTube API parts:** Use part=snippet,statistics to obtain likeCount Time window:* The filter keeps videos from the *last 72 hours** 🧪 Troubleshooting Missing likeCount / classification = "unknown"** → ensure part=statistics and a valid API key credential. Gmail OAuth redirect_mismatch / access_denied** → redirect must be https://<your-n8n-host>/rest/oauth2-credential/callback and test users added if restricted. SMTP auth issues** → set correct server/port/TLS and use an app password when 2FA is enabled. Empty LLM output** → verify OpenAI key/quota and inspect node logs. 🧾 Example Outputs 1) Classification (single video) { "videoId": "abc123XYZ", "title": "How to Ship an n8n Workflow with OpenAI", "likeCount": 1587, "classification": "viral", "needsStatsFetch": false } 2) LinkedIn draft (viral) Did you know how much faster prompt workflows get with structured inputs? • Setup: n8n + YouTube API + OpenAI for auto-briefs • Tip: include part=statistics for reliable like counts Useful for teams tracking trending how-to content. What’s your best “viral” signal besides likes? #n8n #YouTubeAPI #OpenAI #Automation #Growth 3) Plain‑text email preview Subject: Weekly AI Briefing — YouTube Trend Highlights Hi team, Highlights from our tracked channels: • Viral: “How to Ship an n8n Workflow with OpenAI” (1.6k likes) • Normal: “RSS vs API: What’s Best for Monitoring?” Generated via n8n + GPT‑4. ✅ Submission Checklist (meets the guidelines) Title clarity:* Mentions *GPT‑4* and *Gmail** Language:* Entire document in *English** Node naming:** Descriptive, non‑generic labels HTML → Markdown:* No HTML in this description; badges are *Markdown images** Examples:** Included (JSON, LinkedIn draft, email) Security:** No secrets in JSON; uses credentials by name 📸 Suggested Screenshots (optional) Full canvas overview (entire workflow) LLM output (expanded) showing generated summary Send‑node result with messageId/status Optional: aggregated briefing preview 📜 License & Support License: MIT Support/Contact: kaihoelters@yahoo.de

Introduction Automates Singapore COE price tracking with AI forecasts and buy/wait recommendations. Weekly scraping collects LTA data, enriches with economic indicators, predicts 6-month trends, and alerts users via Telegram/email—helping car buyers and fleet managers make data-driven purchase decisions while avoiding manual tracking. How it Works Weekly trigger scrapes LTA COE → validates → stores in Google Sheets → calculates indicators → AI forecasts trends → multi-scenario analysis → generates buy/wait signals → sends actionable alerts. Setup Steps Add OpenAI/NVIDIA API credentials in n8n Authenticate Google Sheets and create spreadsheet Configure Telegram bot or Gmail SMTP Set weekly trigger (Thursday 9AM SGT post-bidding) Adjust alert thresholds in conditional nodes Workflow Schedule Trigger → Scrape COE → Validate → Store Sheets → Fetch Historical → Calculate Indicators → AI Prediction → Merge Economics → Multi-Scenario Analysis → Compare Conditions → Generate Dashboard → Send Alerts Workflow Steps Scraping: Fetch LTA COE results with retry logic Validation: Check completeness, flag anomalies Storage: Append timestamped records to Sheets Enrichment: Calculate moving averages, volatility, seasonality AI Analysis: Forecast next 6 months with confidence intervals Decision Engine: Output buy/wait/monitor recommendation Reporting: Create dashboard and send alerts via Telegram/email Prerequisites OpenAI/NVIDIA API key, Google Sheets access, Telegram bot token or Gmail, basic COE category understanding Use Cases First-time buyers timing purchases, fleet operators coordinating bulk acquisitions Customization Add SMS alerts via Twilio, integrate loan calculators for total cost analysis Benefits Saves 5+ hours monthly, captures 10–18% price dips, provides predictive insights (potential $10K–$25K savings)

LinkedIn URL → Scrape → Match → Screen → Decide, all automated This workflow automatically processes candidate LinkedIn profiles shared via Telegram, intelligently matches them to job descriptions, performs AI-powered screening analysis, and sends actionable summaries to your team in Telegram. Good to know Handles LinkedIn profile scraping via Apify API (extracts full profile data including experience, education, skills) Built-in spam prevention: limits users to 3 LinkedIn profile submissions Two-stage JD matching: prioritizes role mentioned in candidate's Telegram message, falls back to LinkedIn profile analysis if needed Uses Google Gemini API for AI screening (generous free tier and rate limits, typically enough to avoid paying for API requests - check latest pricing at Google AI Pricing and rate limits documentation) Automatic polling mechanism checks Apify extraction status up to 10 times (15-second intervals) Complete audit trail logged in Google Sheets with unique submission IDs Who's it for Hiring teams and recruiters who want to streamline first-round screening for candidates who share LinkedIn profiles directly. Perfect for companies accepting applications via messaging platforms (Telegram, WhatsApp, etc.), especially useful fortech-savvy audiences and remote/global hiring. How it works Telegram bot receives message containing LinkedIn profile URL from candidate Validates URL format and checks spam prevention (max 3 submissions per Telegram username) Sends confirmation message to candidate and notifies internal talent team via Telegram group Extracts clean LinkedIn URL and initiates Apify scraping job Polls Apify API up to 10 times (15-second intervals) until profile extraction completes AI agent matches candidate to best-fit job description by analyzing Telegram message context first (if candidate mentioned a role), or LinkedIn profile content as fallback (selects up to 3 potential JD matches) If multiple JDs matched, second AI agent selects the single best fit based on detailed profile analysis AI recruiter agent analyzes LinkedIn profile against selected JD and generates structured screening report (strengths, weaknesses, risk/reward factors, overall fit score 0-10 with justification) Logs complete analysis to Google Sheets tracker with unique submission ID Sends formatted summary to Telegram group with candidate details, matched JD, and overall fit score Requirements Telegram Bot Token (Create bot via @BotFather) Apify account with API token (Sign up for free tier) Google Drive account (OAuth2) Google Sheets account (OAuth2) Google Gemini API key (Get free key here) Google Drive folder for Job Descriptions (as PDFs or Google Docs) Telegram group for internal talent team notifications How to set up Create Telegram bot and internal Telegram chat group with new bot: Message @BotFather on Telegram Send /newbot and follow instructions to create your bot Save the API token provided Create Telegram group chat and invite your new bot + invite the @GetIDs bot Note down the group chat ID (How to get group chat ID) Setup Apify: Sign up at Apify Get your API token from Settings Note: Free tier includes sufficient scraping credits for testing and production ($0.01 per successful LinkedIn profile enriched, a free monthly limit of $5.00) - LinkedIn profile scraper "actor" details Create Google Sheet: Create new sheet named "LinkedIn Profile AI Candidate Screening" Add columns: Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, Email (if known), Telegram Username, Strengths, Weaknesses, Risk Factor, Reward Factor, JD Match, Overall Fit, Justification Copy the spreadsheet ID from URL Setup Google Drive folder: Create folder named "Job Descriptions" Upload your JD files (PDFs or Google Docs) with clear, descriptive filenames Copy the folder ID from URL Configure workflow nodes: In "Receive Telegram Msg to Recruiter Bot" node: Add Telegram API credentials In "Extract LinkedIn Profile Information" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Check LinkedIn Profile Extraction Status" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Get Fully Extracted LinkedIn Profile Data" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Access JD Files" node: Update folder ID to your "Job Descriptions" folder In "Get All Rows Matching Telegram Username" node: Select your Google Sheet In "Add Candidate Analysis in GSheet" node: Select your Google Sheet and verify column mappings In "Send Msg to Internal Talent Group" node: Update chat ID to your Telegram group chat ID In "Send Review Completed Msg to Talent Group" node: Update chat ID and Google Sheet URL Add your company description: In "JD Matching Agent" system message: Replace company description with your details In "Detailed JD Matching Agent" system message: Replace company description with your details In "Recruiter Scoring Agent" system message: Update company description Test the workflow: Send a LinkedIn profile URL to your bot from Telegram Monitor execution to ensure all nodes run successfully Check Google Sheets for logged results Activate workflow Customizing this workflow Change spam limits: Edit "Spam Check: Sent <4 LinkedIn Profiles?" node to adjust maximum submissions (currently 3) Adjust polling attempts: Edit "Checked 10x for LinkedIn Profile Data?" node to change maximum polling attempts (currently 10) or modify wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Change JD matching logic: Edit "JD Matching Agent" node prompt to adjust how LinkedIn profiles are matched to roles (e.g., weight current role vs. overall experience) Modify screening criteria: Edit "Recruiter Scoring Agent" node system message to focus on specific qualities (culture fit, leadership potential, technical depth, industry experience, etc.) Add more messaging platforms: Add nodes to support WhatsApp, Discord, or other messaging platforms using similar URL-based triggers Customize Telegram messages: Edit notification nodes to change formatting, add emojis, or include additional candidate data Auto-proceed logic: Add IF node after screening to auto-proceed candidates with fit score above threshold (e.g., 8+/10) and trigger different notification paths Add candidate responses: Connect nodes to automatically message candidates back via Telegram (confirmation, rejection, interview invite) Add interview scheduling: For approved candidates, send Telegram message with Cal.com or Calendly link so they can book their interview Enrich with additional data: Add nodes to cross-reference candidate data with other sources (GitHub, Twitter/X, company websites) Multi-language support: Add translation nodes to support candidates submitting profiles in different languages Add human approval step: Create buttons in Telegram group messages for instant Approve/Reject decisions that update Google Sheets Pro tip: Add your Telegram bot to your company's careers page with instructions like: "Want fast-track screening? Share your LinkedIn profile with our AI recruiter: @YourBotName" Troubleshooting Telegram bot not responding: Ensure bot token is correct in "Receive Telegram Msg to Recruiter Bot" node, and users have sent /start to your bot at least once "LinkedIn profile URL invalid" error: Check that candidates are sending full URLs in format https://www.linkedin.com/in/username (not shortened links or text without URL) Apify extraction failing: Verify Apify API token is correctly set in all three HTTP Request nodes ("Extract LinkedIn Profile Information", "Check LinkedIn Profile Extraction Status", "Get Fully Extracted LinkedIn Profile Data") LinkedIn extraction timeout: Increase polling attempts in "Checked 10x for LinkedIn Profile Data?" node (currently 10) or increase wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Spam check blocking valid users: Check "Get All Rows Matching Telegram Username" node is pointing to correct Google Sheet, and adjust limit in "Spam Check: Sent <4 LinkedIn Profiles?" node if needed JD matching returns no results: Check "Access JD Files" node folder ID points to your Job Descriptions folder, and JD files are named clearly (e.g., "Marketing Director JD.pdf") JD matching is not relevant for my company: Update the "Company Description" in the System Messages in all three AI agent nodes ("JD Matching Agent", "Detailed JD Matching Agent", "Recruiter Scoring Agent") "Can't find matching JD": Ensure candidate's Telegram message mentions role name OR their LinkedIn profile clearly indicates relevant experience for available JDs Google Sheets errors: Verify sheet name is "LinkedIn Profile AI Candidate Screening" and column headers exactly match workflow expectations (Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, etc.) Telegram group notifications not appearing: Verify chat ID is correct in "Send Msg to Internal Talent Group" and "Send Review Completed Msg to Talent Group" nodes (use negative number for group chats, e.g., -4954246611) Missing candidate data in Google Sheets: LinkedIn profile may be incomplete - verify Apify successfully extracted data by checking "Get Fully Extracted LinkedIn Profile Data" node output Loop counter not working: Check "Restore Loop Counter" code node references correct node names ("Checked 10x for LinkedIn Profile Data?" and "Initialize Loop Counter to Poll for Completion") 401/403 API errors: Re-authorize all OAuth2 credentials (Google Drive, Google Sheets) and verify Apify and Telegram API tokens are valid AI analysis quality issues: Edit system prompts in "JD Matching Agent", "Detailed JD Matching Agent", and "Recruiter Scoring Agent" nodes to refine screening criteria and provide more context about your hiring needs Gemini API rate limit errors: Check your usage at Google AI Studio and consider upgrading to paid tier if exceeding free tier limits (see rate limits documentation) Sample Outputs Google Sheets - LinkedIn AI Candidate Screening - sample Telegram messages between AI recruiter bot and job applicant Telegram messages from AI recruiter bot in internal group chat

UX & SEO Website Analyst (Airtop + OpenAI + Gmail) This workflow automatically analyzes a website for UX and SEO quality. It uses Airtop for realistic web scraping, OpenAI for structured evaluation of metadata (title, description, and overall SEO signals), and Gmail to send professional reports. What it does Scrapes website content and metadata through an Airtop session. Evaluates SEO and UX factors (strengths, weaknesses, recommendations) with OpenAI. Generates a clear, structured report. Sends the report automatically via Gmail. Use cases Marketing agencies auditing client websites. Freelancers offering SEO/UX review services. Businesses monitoring their own website performance. Requirements Airtop account** with API access. OpenAI API key**. Gmail credentials** connected in n8n. How it works Start the flow with a target website URL. Airtop opens a session and scrapes metadata naturally. OpenAI analyzes and scores the title, description, and overall quality. Gmail sends a formatted report to your chosen recipient. Set up steps Connect Airtop, OpenAI, and Gmail credentials in n8n. Provide the target URL to analyze. Run the workflow and review the email report. Keep detailed instructions inside sticky notes in the workflow.

How it works This workflow is your personal CEO Brain. Every Saturday night, it automatically collects the past week’s activity across: 📩 Gmail: filters out spam, promos, receipts, etc. 📅 Google Calendar: grabs past week and upcoming month 🗒️ Notion Weekly Plan: pulls and analyzes a photo of your weekly plan (e.g., taken from a paper planner/notebook) using GPT-4o 🎯 Notion OKRs: fetches quarterly OKRs and formats them for summary It sends all the data to GPT-4.1, which generates a smart weekly report — including progress check, misalignments, overdue follow-ups, and next steps — then emails it to you as a Weekly OKR Report. Set up steps 🧠 Add your Gmail, Google Calendar, Notion, and OpenAI credentials 📅 The Notion Weekly Plan should have a date property and an image field that holds a photo of your planner/notebook page 🎯 The Notion OKR database should include objective, key result, and status fields 🔁 Schedule is preset to every Saturday at 20:30 HK time (cron 0 30 20 * * 6). Also set the workflow timezone in n8n and, if self-hosting, the server/container TZ (e.g., TZ=Asia/Hong_Kong) to ensure correct triggering 💬 You can modify the AI prompts inside the LLM nodes for more customized outputs