Workflow Templates

🤖 Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round Watch the demo video below: 📌 Who’s it for This workflow is designed for: Recruiters* and *Talent Acquisition Specialists** who want to automate candidate interview prep. Hiring Managers** conducting multiple interviews and needing personalized question sets. Technical Interviewers** who want to save time and be well-prepared with relevant questions. ⚙️ How it works / What it does The Smart Interview Assistant automates the interview preparation process in a few clicks: Accepts: Multiple resumes (PDFs) Selected job role Chosen interview round Extracts structured data from: The candidate’s CV The corresponding Job Description (JD) Uses GPT-4 to analyze: Candidate profile Role requirements Interview round context Generates: Tailored interview questions Expected answers A summarized interview prep report Sends the report directly to the hiring team via email (SMTP) 📁 Google Drive Structure 📂 Root Folder ├── 📁 jd/ # Stores all job descriptions in PDF format │ ├── Backend_Engineer.pdf │ ├── Azure_DevOps_Lead.pdf │ └── ... └── 📄 Positions (Google Sheet) # Maps Job Role ↔ JD File Link 📝 Sample Mapping Sheet: Positions Sheet Columns: Job Role Job Description File URL (pointing to PDF in jd/ folder) 🛠️ How to Set Up Step 1: Configure API Integrations ✅ Connect your OpenAI GPT-4 API Key ✅ Enable Google Cloud APIs: Google Sheets API (to read job roles) Google Drive API (to access CV and JD files) ✅ Set up SMTP credentials (for email delivery) Step 2: Prepare Google Drive & Mapping Sheet Create a root folder on Google Drive Inside the root folder: Create a folder named /jd/ and upload all job descriptions (PDFs) Create a Google Sheet named Positions with the following format: | Job Role | Job Description File URL | |-----------------------------|--------------------------------------------| | Azure DevOps Engineer | https://drive.google.com/xxx/jd1.pdf | | Full-Stack Developer (.NET) | https://drive.google.com/xxx/jd2.pdf | Step 3: Build the Application Form Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects: 📎 Resume file (PDF) 🧾 Job Role (dropdown) 🔄 Interview Round (dropdown) Step 4: Resume & JD Extraction 🔍 Use Extract from PDF to parse the resume content 📄 Retrieve the JD link from the Positions sheet based on the selected Job Role 🔗 Use Download file to pull the PDF for processing Step 5: Analyze with GPT-4 Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output) Merge results Add manual input or mapping for the Interview Round metadata Step 6: Generate Interview Report Use a second GPT-4 agent (e.g., HR Expert Agent) to: Generate 6–8 tailored interview questions Include expected answers and rationale Step 7: Deliver Final Report Format the content as: 📄 PDF (optional) 📨 Email body Send the report to the recruiter, hiring manager, or interviewer via SMTP ✅ Requirements 🔑 OpenAI GPT-4 API Key 📁 Google Drive (for resume and JD storage) 📊 Google Sheet (job role mapping) 📬 SMTP credentials (host, username, password) 🧰 n8n self-hosted or cloud instance with: PDF Parser Google Sheets node HTTP Download node Email node ✏️ How to Customize the Workflow | Part | Customization Options | |----------------------------|-------------------------------------------------------------| | Form UI | Modify the design, dropdown options, or input validations | | Job Description Source | Replace Google Sheet with Notion, Airtable, or database | | Interview Metadata | Add job level, region, or language preference | | AI Prompt Tuning | Adjust prompt phrasing or temperature in GPT nodes | | Report Format | Generate PDF instead of email body using PDF node | | Delivery Method | Add internal HR portal webhook or generate downloadable link |

Scan URLs with urlscan.io and Send Results via Gmail

by Calistus Christian

Overview Receive a URL via Webhook, submit it to urlscan.io, wait ~30 seconds for artifacts (e.g., screenshot), then email a clean summary with links to the result page, screenshot, and API JSON. What this template does Ingests a URL from a POST request. Submits the URL to urlscan.io and captures the scan UUID. Waits 30s** to give urlscan time to generate the screenshot and result artifacts. Sends a formatted HTML email via Gmail with all relevant links. Nodes used Webhook** (POST /urlscan) urlscan.io → Perform a scan** Wait** (30 seconds; configurable) Gmail → Send a message** Input { "url": "https://example.com" }

beginner

2 nodes1 views

Creating a AI Slack Bot with Google Gemini

by Zacharia Kimotho

This is an example of how we can build a slack bot in a few easy steps Before you can start, you need to o a few things Create a copy of this workflow Create a slack bot Create a slash command on slack and paste the webhook url to the slack command Note Make sure to configure this webhook using a https:// wrapper and don't use the default http://localhost:5678 as that will not be recognized by your slack webhook. Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent. To have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history. The final message is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create a new message with reference to the input we passed. We can advance this using the tools or data sources for it to be more custom tailored for your company. Usage To use the slackbot, go to slack and click on your set slash command eg /Bob and send your desired message. This will send the message to your endpoint and get return the processed results as the message. If you would like help setting this up, feel free to reach out to zacharia@effibotics.com

Line Message API : Push Message & Reply

by darrell_tw

Workflow Description This workflow demonstrates how to use the LINE Messaging API to handle two scenarios: Replying to a user's message using a reply token. Sending a push message to a specific LINE user using their user ID. Key Features Webhook Integration: Receives and processes incoming messages from LINE using a webhook. Conditional Logic: Checks if the received event type is a message and handles it accordingly. Reply Message: Automatically responds to the user's message using the LINE reply token. Push Message: Sends a test message to a specific LINE user using their unique user ID. Pre-Configuration To simplify the setup process, create a Header Auth credential in n8n: Name**: Authorization Value**: Bearer {line token} This will authenticate all API requests to the LINE Messaging API. Node Configurations 1.1. Webhook from LINE Message Purpose**: Captures incoming events from the LINE Messaging API. Configuration**: HTTP Method: POST Path: {n8n-webhook-page} 1.2. If Condition Purpose**: Checks if the received event type is message. Configuration**: Condition: {{ $json.body.events[0].type }} equals "message" 1.3. Line: Reply with Token Purpose**: Replies to the user's message using the LINE reply token. Configuration**: Method: POST URL: https://api.line.me/v2/bot/message/reply JSON Body: { "replyToken": "{{ $('Webhook from Line Message').item.json.body.events[0].replyToken }}", "messages": [ { "type": "text", "text": "收到您的訊息 : {{ $('Webhook from Line Message').item.json.body.events[0].message.text }}" } ] } 2.1. Manual Trigger: Test Workflow Purpose**: Triggers the workflow for testing the push message functionality. Configuration**: No additional setup required. 2.2. Edit Fields Purpose**: Prepares the unique LINE user ID for the push message. Configuration**: Field: line_uid: Uxxxxxxxxxxxx 2.3. Line: Push Message Purpose**: Sends a test message to a specific LINE user. Configuration**: Method: POST URL: https://api.line.me/v2/bot/message/push JSON Body: { "to": "{{ $json.line_uid }}", "messages": [ { "type": "text", "text": "推播測試" } ] } 工作流程描述此工作流程展示如何使用 LINE Messaging API 處理兩種情境：使用 reply token 回應使用者的訊息。使用使用者的 user ID 發送推播訊息。主要功能 Webhook 整合：透過 Webhook 接收並處理來自 LINE 的訊息。條件邏輯：檢查接收到的事件類型是否為訊息並進行處理。回應訊息：使用 LINE 的 reply token 自動回覆使用者的訊息。推播訊息：使用 LINE User ID 向指定用戶發送測試訊息。預先設定為簡化設定流程，請在 n8n 中建立 Header Auth 憑證：名稱**：Authorization 值**：Bearer {line token} 此設定將用於認證所有 LINE Messaging API 的請求。節點設定 1.1. Webhook from LINE Message 用途**：接收來自 LINE Messaging API 的事件。設定**： HTTP 方法：POST 路徑：{n8n-webhook-page} 1.2. If 條件判斷用途**：檢查接收到的事件類型是否為 message。設定**：條件： {{ $json.body.events[0].type }} 等於 "message" 1.3. Line: Reply with Token 用途**：使用 LINE reply token 回應使用者訊息。設定**：方法：POST URL：https://api.line.me/v2/bot/message/reply JSON 主體： { "replyToken": "{{ $('Webhook from Line Message').item.json.body.events[0].replyToken }}", "messages": [ { "type": "text", "text": "收到您的訊息 : {{ $('Webhook from Line Message').item.json.body.events[0].message.text }}" } ] } 2.1. 手動觸發：測試工作流程用途**：測試推播訊息功能。設定**：無需額外設定。 2.2. Edit Fields 用途**：準備推播訊息所需的 LINE 使用者 ID。設定**：欄位： line_uid：Uxxxxxxxxxxxx 2.3. Line: 推播訊息用途**：向特定 LINE 使用者發送測試訊息。設定**：方法：POST URL：https://api.line.me/v2/bot/message/push JSON 主體： { "to": "{{ $json.line_uid }}", "messages": [ { "type": "text", "text": "推播測試" } ] } 完成示意圖 (Storyboard Example):

Generate Conversational Twitter/X Threads with GPT-4o AI

by joseph

🧵 Generate Conversational Twitter/X Threads with GPT-4o AI (n8n Workflow) This workflow uses OpenAI (GPT-4o) and Twitter/X to automatically generate and publish engaging, conversational threads in response to a trigger (e.g., from a chatbot or form). 🚀 What Does It Do? Listens for an incoming message (e.g., via webhook or another n8n input). Uses GPT-4o to craft a narrative-style Twitter thread in a personal, friendly tone. Publishes the first tweet, then automatically posts each following tweet as a reply—building a full thread. 🛠️ What Do You Need to Configure? Before using this template, make sure to set up the following credentials: OpenAI Add your OpenAI API key in the OpenAI Chat Model node. This is used to generate the thread content. Twitter/X Add your Twitter OAuth2 credentials to the First Tweet and Thread Reply nodes. This allows the workflow to publish tweets on your behalf. ✨ Who Is This For? This template is perfect for: Content creators who want to share ideas regularly Personal brands looking to grow their presence Social media managers automating thread creation 🔧 How to Customize It You can easily adjust the tone, structure, or length of the threads by modifying the system prompt in the OpenAI node. For example: To create threads with humor, change the prompt to “Write in a witty and humorous tone.” To tailor it for marketing, prompt it with “Write a persuasive product-focused Twitter thread.” You can also integrate this workflow with: Telegram bots Web forms (e.g., Typeform, Tally) CRM tools or newsletter platforms 📋 Sample Output Prompt sent to the workflow: “Tips for growing on Twitter in 2025” Generated thread: ++Tweet 1:++ Thinking of growing your presence on Twitter/X in 2024? Here's a thread with the most effective strategies that actually work 🧵 ++Reply 1:++ Engage, don’t broadcast Twitter is a conversation platform. Reply to others, quote-tweet, and start discussions instead of just posting links. ++Reply 2:++ Consistency beats virality Tweeting regularly builds trust and visibility. You don't need to go viral — just show up.

🤖AI & Machine Learning

beginner

3 nodes700 views

fetch the public IP addresses of your n8n instance

by Ger Longstacks

Why If you need to use n8n to connect to service providers of yours, some of which happen to rely on firewall white-listing as part of their access control, you'll need to determine or verify the public IP addresses of your n8n instance(s). How does it work The webhook, upon invocation, will use Http Request node to request public IP address information from ++api.ipify.org++ in json format, for 10 times, then aggregate results to an array. The reason to repeat, is to get all the potential public IP addresses of your n8n instance. Often than not, enterprises or network providers deploy at least a pair of gateway devices at the border for redundancy. built-in array functions in a javascript expression are used to pluck all the values under 'ip' key, and to dedup to an array as response body. How to set it up import the workflow set up your own header-auth credential update the workflow to use the new credential test or activate workflow as usual. example invocation $ curl -H "api-key: super-long-api-token" http://localhost:5678/webhook-test/4879bc79-d6f8-48df-bfe4-613366c7f399 ["88.88.88.66", "88.88.88.88"]

Monitor website performance with PageSpeed Insights and send alerts

by Dahiana

Monitor website performance with PageSpeed Insights and save to Google Sheets with alerts This n8n template automatically monitors website performance using Google's PageSpeed Insights API, compiles detailed reports, and tracks performance trends over time in Google Sheets. Use cases: Agency client monitoring, competitor analysis, performance regression detection, SEO reporting, site migration monitoring, A/B testing performance impact, and maintaining performance SLAs. Who's it for Digital agencies monitoring client websites SEO professionals tracking site performance DevOps teams maintaining performance SLAs Business owners wanting automated site monitoring How it works Automated Testing:** Scheduled audits of multiple websites using PageSpeed Insights API Core Web Vitals:** Tracks LCP, FID, CLS, and overall performance scores Historical Tracking:** Maintains performance history for trend analysis Alert System:** Sends notifications when performance drops below thresholds Detailed Reporting:** Captures specific recommendations and optimization opportunities Two Workflow Paths Scheduled Audit: Automatically tests all URLs from Google Sheet on schedule On-Demand Testing: Webhook endpoint for immediate single-URL testing How to set up Get a free PageSpeed Insights API key from Google Cloud Console Create Google Sheet with columns: URL, Site Name, Category, Alert Threshold, Last_Processed_Date and Device. Set up Google Sheets API credentials Configure notification preferences (Slack, email, etc.) Set audit schedule (daily, weekly, or custom) Define performance thresholds for alerts Requirements Google PageSpeed Insights API key (free) Google Sheets API access n8n instance (cloud or self-hosted) Optional: Slack/email for notifications Google Sheet Structure Input Sheet ("sites"): URL, Site_Name, Category, Alert_Threshold, Last_Processed_Date and Device. Results Sheet ("audit_results"): Date, URL, Site_Name, Device, Performance_Score, LCP, FID, CLS, Recommendations, Full_Report_URL API Usage (On-Demand) POST to webhook: { "url": "https://example.com", "site_name": "Example Site", "alert_threshold": 75 } How to customize Add custom performance thresholds per site Include additional metrics (accessibility, SEO, best practices) Connect to other dashboards (Data Studio, Grafana) Add competitor benchmarking Integrate with project management tools for issue tracking Set up different notification channels based on severity Sample Google Sheet Included

beginner

4 nodes517 views

Rewrite viral LinkedIn posts in your voice with Google Gemini and Telegram approval

by ConnectSafely

Rewrite viral LinkedIn posts in your voice with AI and Telegram approval using Google Gemini Who's it for This workflow is designed for LinkedIn creators, personal brand builders, thought leaders, and content marketers who want to consistently create engaging content without starting from scratch. Perfect for professionals who admire viral posts from others but want to adapt those ideas to their own unique voice and style. If you're struggling to maintain a consistent posting schedule, looking for content inspiration, or want to repurpose trending ideas while keeping your authentic voice, this automation handles the creative heavy lifting while giving you full control over what gets published. How it works The workflow transforms viral LinkedIn posts into personalized content that matches your writing style, complete with AI-generated images, all controlled through Telegram. The process flow: Send any LinkedIn post URL to your Telegram bot Security check validates your Telegram user ID ConnectSafely.ai scrapes the original post content and engagement metrics Your custom persona profile is loaded (tone, phrases, formatting preferences) Google Gemini AI rewrites the post to match YOUR voice Gemini generates a professional, on-brand image for the post Preview is sent to Telegram for your review Approve or reject with a simple reply On approval, the post goes live on LinkedIn automatically Setup steps Step 1: Create a Telegram Bot Open Telegram and search for @BotFather Send /newbot and follow the prompts to create your bot Save the API token provided by BotFather Get your Telegram User ID by messaging @userinfobot Step 2: Configure Telegram Credentials in n8n Go to Credentials → Add Credential → Telegram API Paste your bot token from BotFather Save the credential Update all Telegram nodes to use this credential Step 3: Set Up Security Check Open the 🔒 Security Check node Replace YOUR_TELEGRAM_USER_ID with your actual Telegram user ID This ensures only YOU can trigger the workflow Step 4: Configure ConnectSafely.ai API Sign up at ConnectSafely.ai Navigate to Settings → API Keys in your dashboard Generate a new API key In n8n, go to Credentials → Add Credential → ConnectSafely API Paste your API key and save Connect this credential to the 🔍 Scrape LinkedIn Post node Step 5: Configure Google Gemini API Go to Google AI Studio Create or select a project Generate an API key In n8n, go to Credentials → Add Credential → Google Gemini (PaLM) API Paste your API key and save Connect this credential to both: Google Gemini Chat Model node Generate an image node Step 6: Connect Your LinkedIn Account In n8n, go to Credentials → Add Credential → LinkedIn OAuth2 API Follow the OAuth flow to connect your LinkedIn account Connect this credential to the Create LinkedIn Post node Update the person parameter with your LinkedIn Person ID (URN) Step 7: Customize Your Persona Open the 👤 Load Your Persona node Edit the PERSONA object to match YOUR writing style: Update name with your name Modify expertiseAreas with your topics Adjust commonPhrases with phrases you actually use Set preferredEmojis to your favorites Customize styleNotes to capture your unique voice Step 8: Activate the Workflow Save your workflow Toggle the workflow to Active Your Telegram bot is now ready to receive LinkedIn URLs Customization Persona Customization The 👤 Load Your Persona node is where you define your unique voice. Key areas to customize: | Field | Description | Example | |-------|-------------|---------| | tone | Overall communication style | "Professional yet approachable, data-driven" | | voice | Perspective and personality | "First-person, authentic, vulnerable" | | formatting | Structure preferences | "Short paragraphs, emoji bullets, line breaks" | | hooks | Opening style | "Start with contrarian takes or personal stories" | | expertiseAreas | Your niche topics | ["SaaS growth", "Leadership", "Remote work"] | | commonPhrases | Signature expressions | ["Here's the truth:", "I learned this the hard way:"] | Image Generation The 📝 Create Image Prompt node generates the image prompt. Modify the style parameters to match your brand: Current style**: Modern, clean, corporate, vector art Customize**: Change to photography, illustrations, or abstract visuals Post Length In the persona configuration, adjust postLength: "short" - Quick insights (under 500 characters) "medium" - Standard posts (500-1500 characters) "long" - Deep dives (1500-3000 characters) AI Model Selection The workflow uses gemini-2.5-pro for text. You can switch to other models in the Google Gemini Chat Model node based on your needs. Requirements | Requirement | Details | |-------------|---------| | n8n Version | 1.0+ recommended | | Telegram Bot | Created via @BotFather | | ConnectSafely.ai Account | API key required | | Google AI Studio Account | Gemini API key required | | LinkedIn Account | OAuth2 connected in n8n | | Community Node | n8n-nodes-connectsafely-ai (self-hosted only) | ⚠️ Note: This workflow uses the ConnectSafely community node, which requires a self-hosted n8n instance. Use cases Content Repurposing**: Transform competitor or industry leader posts into your own perspective Consistent Posting**: Maintain a regular posting schedule without content creation burnout Style Consistency**: Ensure every post matches your established personal brand Trend Riding**: Quickly create content around viral topics while they're still relevant A/B Testing**: Test different approaches by approving or rejecting variations Troubleshooting Common Issues & Solutions Issue: Bot not responding to messages Solution**: Verify the Telegram webhook is active; check the Telegram Trigger node is properly configured Issue: "Profile not found" from ConnectSafely.ai Solution**: Ensure the LinkedIn URL is complete and public. Some posts on private profiles can't be scraped Issue: Image generation fails Solution**: Verify your Gemini API key has access to image generation models. Check quota limits in Google AI Studio Issue: LinkedIn post fails to publish Solution**: Confirm your LinkedIn OAuth2 credentials are valid and haven't expired. Re-authorize if needed Issue: AI generates posts that don't match your style Solution**: Be more specific in your persona configuration. Add more example phrases and detailed style notes Issue: Security check blocks your messages Solution**: Double-check your Telegram User ID is correctly entered (must be a number, not username) Documentation & Resources Official Documentation ConnectSafely.ai Docs**: https://connectsafely.ai/docs Google Gemini API**: https://ai.google.dev/docs Telegram Bot API**: https://core.telegram.org/bots/api LinkedIn API**: https://docs.microsoft.com/linkedin/ Support ConnectSafely Support**: support@connectsafely.ai n8n Community**: https://community.n8n.io Connect With Us Stay updated with the latest automation tips, LinkedIn strategies, and platform updates: LinkedIn**: linkedin.com/company/connectsafelyai YouTube**: youtube.com/@ConnectSafelyAI-v2x Instagram**: instagram.com/connectsafely.ai Facebook**: facebook.com/connectsafelyai X (Twitter)**: x.com/AiConnectsafely Bluesky**: connectsafelyai.bsky.social Mastodon**: mastodon.social/@connectsafely Need Custom Workflows? Looking to build sophisticated LinkedIn automation workflows tailored to your business needs? Contact our team for custom automation development, strategy consulting, and enterprise solutions. We specialize in: Multi-channel engagement workflows AI-powered personalization at scale Lead scoring and qualification automation CRM integration and data synchronization Custom reporting and analytics pipelines

intermediate

7 nodes

Automated Email Replies with GPT-4o, Outlook, and GoToHuman Approval

by Robert Breen

8.9

This n8n workflow reads emails from your Outlook inbox, drafts AI-powered replies using OpenAI, and routes them through the gotoHuman node for human approval before replying automatically. ✅ Key Features Reads Outlook emails** from today only (excluding those from your own address). AI-generated replies** crafted using OpenAI based on the subject and body of the email. Community node integration**: Uses the gotoHuman node for human review and approval of replies before sending. Safe sending**: Only approved responses are automatically sent back via Outlook. Expandable**: Can be easily modified to: Send drafts instead of full replies Include additional email filters Trigger at intervals or via webhook 🧠 Nodes Used Microsoft Outlook – Fetch and reply to emails OpenAI – Generates smart reply text gotoHuman – Human-in-the-loop approval system Loop Over Items, IF, Code, and Set nodes for processing logic Manual Trigger – For testing 🔧 Setup Instructions 1. Connect APIs Outlook OAuth2**: Go to Azure Portal Register an app Add Mail.Read, Mail.Send scopes Set redirect URI: https://api.n8n.cloud/oauth2-credential/callback Paste credentials in n8n credential manager OpenAI API**: Create account at OpenAI Create an API Key Add it to n8n credentials gotoHuman API**: Go to https://gotoHuman.ai and sign in Create a review template (e.g., “Email Responses”) Copy the Template ID and API key into n8n credentials 🪜 Workflow Steps Overview 1. Trigger Use the Manual Trigger to test or schedule execution with a cron node. 2. Filter Emails from Today A Code node outputs today's date in the proper yyyy-mm-dd format. const today = new Date(); today.setHours(0, 0, 0, 0); return [{ json: { searchQuery: received:${today.toISOString().split('T')[0]} } }]; 3. Search and Filter Outlook Messages Uses the Outlook node with a search query like: received:2025-08-06 -from:rbreen@ynteractive.com (Update to your email) 4. Generate AI Response Text prompt to OpenAI: subject: {{ $json.subject }} body: {{ $json.body.content }} System prompt: > You are a personal assistant helping respond to emails. I am an AI automation expert specializing in helping small and medium-size businesses automate processes. Create a short response to the email. Sign the email as Robert Breen. 5. Review with gotoHuman Submit AI output for human approval using the gotoHuman node. The output schema should match the Review Template fields (e.g., "email", "OriginalEmail"). 6. IF Node Decision If status is approved, send reply If not, return to loop for revision or skip ✏️ Customization Ideas ✉️ Send only drafts by skipping the "reply" step and storing results. 🕒 Schedule the workflow with a Cron trigger for automation. 🔎 Add label filters or subject keywords for advanced targeting. 🔗 External Links gotoHuman Community Node OpenAI Microsoft Outlook API Setup 💬 Need More Help? If you'd like help customizing this or building similar automations, reach out: Robert Breen AI & Automation Consultant 🌐 https://ynteractive.com 📧 robert.j.breen@gmail.com 🔗 LinkedIn

intermediate