Webhook and LinkedIn integration

Schedule and optimize social media posts to Twitter and LinkedIn using AI This workflow automates the entire lifecycle of social media management—from fetching draft content to AI-driven optimization and multi-platform publishing. Who’s it for Social media managers, marketing teams, and content creators who use Google Sheets to plan their content but want to leverage AI for better engagement and automate the repetitive task of cross-platform posting. How it works The workflow is triggered either hourly or manually via a webhook. It fetches scheduled content from a designated Google Sheet and identifies posts ready for publication. An AI Agent (OpenAI) then analyzes the raw content to generate two optimized versions: a punchy, character-limited post for Twitter and a more professional, detailed version for LinkedIn. After generating relevant hashtags and engagement tips, the workflow publishes the posts simultaneously. Finally, it logs the live URLs back to your spreadsheet and sends a performance summary to a Slack channel for easy tracking. How to set up Google Sheet: Create a sheet with columns for status, content, platforms, scheduled_time, hashtags, and tone. Credentials: Connect your Google Sheets, OpenAI, Twitter (X), LinkedIn, and Slack accounts. Node Configuration: Select your specific spreadsheet and worksheet in both the "Fetch Content" and "Update Content" nodes. Slack: Specify the channel name or ID in the Slack node to receive notifications. Activation: Test with the Manual Webhook, then toggle the workflow to "Active." Requirements Google Sheets OAuth2** OpenAI API Key** (using GPT-4o-mini or higher) Twitter (X) OAuth2** LinkedIn OAuth2** Slack Bot Token** How to customize the workflow AI Tone**: Modify the "System Message" in the AI Content Optimizer node to match your brand's unique voice. Additional Platforms**: Extend the branching logic after the AI Parse node to include platforms like Discord, Facebook, or Mastodon. Advanced Scheduling**: Adjust the Filter node's JavaScript code if you use a different date format or status labels in your spreadsheet.

This workflow automates the post-publish process for YouTube videos, combining advanced SEO optimization, cross-platform promotion, and analytics reporting. It is designed for creators, marketers, and agencies who want to maximize the reach and performance of their YouTube content with minimal manual effort. Features SEO Automation** Fetches video metadata and analyzes competitor and trending data. Uses AI to generate SEO-optimized titles, descriptions, and tags. Calculates an SEO score and applies A/B testing logic to select the best title. Updates the video metadata on YouTube automatically. Cross-Platform Promotion** Generates platform-specific promotional content (LinkedIn, X/Twitter, Instagram, Facebook, etc.) using AI. Publishes posts to each connected social channel. Extracts video clips and analyzes thumbnails for enhanced promotion. Engagement Monitoring & Analytics** Monitors YouTube comments, detects negative sentiment, and drafts AI-powered replies. Logs all key data (videos, comments, analytics) to Google Sheets for tracking and reporting. Runs a weekly analytics job to aggregate performance, calculate engagement/viral indicators, and email a detailed report. Notifications & Alerts** Sends Slack alerts when a new video is published or when viral potential/negative comments are detected. How It Works Trigger The workflow starts automatically when a new YouTube video is published (via webhook) or on a weekly schedule for analytics. Video Intake & SEO Fetches video details (title, description, tags, stats). Gathers competitor and trending topic data. Uses AI to generate improved SEO assets and calculates an SEO score. Selects the best title (A/B test) and updates the video metadata. Clip & Thumbnail Processing If the video is long enough, runs thumbnail analysis and extracts short clips for social media. Cross-Platform Promotion Generates and formats promotional posts for each social platform. Publishes automatically to enabled channels. Engagement & Comment Monitoring Fetches comments, detects negative sentiment, and drafts AI-powered replies. Logs comments and responses to Google Sheets. Analytics & Reporting Aggregates weekly analytics, calculates engagement and viral indicators. Logs insights and sends a weekly report via email. Notifications Sends Slack alerts for new video publications and viral/negative comment detection. Setup Instructions Connect YouTube Set up YouTube API credentials and required IDs in the Workflow Configuration node. Connect OpenAI Add your OpenAI credentials for AI-powered content generation. Connect Slack Configure Slack credentials and specify alert channels. Connect Google Sheets Set up service account credentials for logging video, comment, and analytics data. Configure Social Platforms Add credentials for LinkedIn, Twitter (X), Instagram, and Facebook as needed. Test the Workflow Publish a test video and verify that metadata updates, social posts, logging, and weekly reports are working as expected. Use Cases YouTube Creators:** Automate SEO, promotion, and analytics to grow your channel faster. Marketing Teams:** Streamline multi-channel video campaigns and reporting. Agencies:** Deliver consistent, data-driven YouTube growth for multiple clients. Requirements YouTube API credentials OpenAI API key Slack API token Google Sheets service account (Optional) LinkedIn, Twitter, Instagram, Facebook API credentials Limitations Requires valid API credentials for all connected services. AI-powered features depend on OpenAI API access. Social posting is limited to platforms with available n8n nodes and valid credentials. Tip: You can easily customize prompts, scoring logic, and enabled platforms to fit your channel’s unique needs.

This workflow leverages n8n to automate LinkedIn content creation from start to finish. Upload an image and quote through a web form, and get a professionally designed post with AI-generated captions, ready to publish in seconds. Features Randomly selects from 6 professional design templates for visual variety Converts HTML designs to high-quality images (90-95% JPEG quality) Generates engaging captions using OpenAI's GPT models Built-in caption editor for customization before posting Direct publishing to LinkedIn profiles or company pages Auto-compresses images for optimal LinkedIn upload Prerequisites N8N Instance: A running n8n instance (cloud or self-hosted) OpenAI API: Active account with API access for caption generation LinkedIn Account: Profile or company page with API access Image Conversion API: HTML CSS to Image account Web Hosting: Platform to host the web form (Netlify, Vercel, or custom server) Setup Instructions Deploy Web Form Download the provided web form template Host on your preferred platform Copy both webhook URLs from your n8n workflow Update form's webhook endpoints with your n8n URLs Configure Image Conversion Sign up at htmlcsstoimage.com Get your API credentials (User ID + API Key) Add to HTTP Request node as Basic Auth credentials Connect OpenAI API Create API key at OpenAI Platform In the ChatGPT HTTP Request node, add Header parameter: Key: Authorization Value: Bearer YOUR_API_KEY Recommended model: gpt-4 or gpt-3.5-turbo Authenticate LinkedIn Create LinkedIn OAuth2 credential in n8n Follow the authentication flow and grant required permissions Select the credential in the "Create a post" LinkedIn node Choose post destination (personal profile or company page) Test the Workflow Submit test data through the web form Monitor n8n execution panel for successful completion Verify image generation, caption quality, and LinkedIn posting Adjust settings as needed based on results Notes Processing time averages 10-20 seconds from upload to preview All 6 design templates are fully responsive and LinkedIn-optimized Caption editor allows full customization before publishing to LinkedIn For questions or issues, please contact me for consulting and support : Linkedin. 🔗 Test with sample data first. Access Web Form Template

Overview: Automated LinkedIn Job Posting with AI This workflow automates the publication of new job vacancies on LinkedIn immediately after they are created in the Recrutei ATS (Applicant Tracking System). It leverages a Code node to pre-process the job data and a powerful AI model (GPT-4o-mini, configured via the OpenAI node) to generate compelling, marketing-ready content. This template is designed for Recruitment and Marketing teams aiming to ensure consistent, timely, and high-quality job postings while saving significant operational time. Workflow Logic & Steps Recrutei Webhook Trigger: The workflow is instantly triggered when a new job vacancy is published in the Recrutei ATS, sending all relevant job data via a webhook. Data Cleaning (Code Node 1): The first Code node standardizes boolean fields (like remote, fixed_remuneration) from 0/1 to descriptive text ('yes'/'no'). Prompt Transformation (Code Node 2): The second, crucial Code node receives the clean job data and: Maps the original data keys (e.g., title, description) to user-friendly labels (e.g., Job Title, Detailed Description). Cleans and sanitizes the HTML description into readable Markdown format. Generates a single, highly structured prompt containing all job details, ready for the AI model. AI Content Generation (OpenAI): The AI Model receives the structured prompt and acts as a 'Marketing Copywriter' to create a compelling, engaging post specifically optimized for the LinkedIn platform. LinkedIn Post: The generated text is automatically posted to the configured LinkedIn profile or Company Page. Internal Logging (Google Sheets): The workflow concludes by logging the event (Job Title, Confirmation Status) into a Google Sheet for internal tracking and auditing. Setup Instructions To implement this workflow successfully, you must configure the following: Credentials: Configure OpenAI (for the Content Generator). Configure LinkedIn (for the Post action). Configure Google Sheets (for the logging). Node Configuration: Set up the Webhook URL in your Recrutei ATS settings. Replace YOUR_SHEET_ID_HERE in the Google Sheets Logging node with your sheet's ID. Select the correct LinkedIn profile/company page in the Create a post node.

AWS News Analysis and LinkedIn Automation Pipeline Transform AWS industry news into engaging LinkedIn content with AI-powered analysis and automated approval workflows. Who's it for This template is perfect for: Cloud architects and DevOps engineers** who want to stay current with AWS developments Content creators** looking to automate their AWS news coverage Marketing teams** needing consistent, professional AWS content Technical leaders** who want to share industry insights on LinkedIn AWS consultants** building thought leadership through automated content How it works This workflow creates a comprehensive AWS news analysis and content generation pipeline with two main flows: Flow 1: News Collection and Analysis Scheduled RSS Monitoring: Automatically fetches latest AWS news from the official AWS RSS feed daily at 8 PM AI-Powered Analysis: Uses AWS Bedrock (Claude 3 Sonnet) to analyze each news item, extracting: Professional summary Key themes and keywords Importance rating (Low/Medium/High) Business impact assessment Structured Data Storage: Saves analyzed news to Feishu Bitable with approval status tracking Flow 2: LinkedIn Content Generation Manual Approval Trigger: Feishu automation sends approved news items to the webhook AI Content Creation: AWS Bedrock generates professional LinkedIn posts with: Attention-grabbing headlines Technical insights from a Solutions Architect perspective Business impact analysis Call-to-action engagement Automated Publishing: Posts directly to LinkedIn with relevant hashtags How to set up Prerequisites AWS Bedrock access** with Claude 3 Sonnet model enabled Feishu account** with Bitable access LinkedIn company account** with posting permissions n8n instance** (self-hosted or cloud) Detailed Configuration Steps AWS Bedrock Setup Step 1: Enable Claude 3 Sonnet Model Log into your AWS Console Navigate to AWS Bedrock Go to Model access in the left sidebar Find Anthropic Claude 3 Sonnet and click Request model access Fill out the access request form (usually approved within minutes) Once approved, verify the model appears in your Model access list Step 2: Create IAM User and Credentials Go to IAM Console Click Users → Create user Name: n8n-bedrock-user Attach policy: AmazonBedrockFullAccess (or create custom policy with minimal permissions) Go to Security credentials tab → Create access key Choose Application running outside AWS Download the credentials CSV file Step 3: Configure in n8n In n8n, go to Credentials → Add credential Select AWS credential type Enter your Access Key ID and Secret Access Key Set Region to your preferred AWS region (e.g., us-east-1) Test the connection Useful Links: AWS Bedrock Documentation Claude 3 Sonnet Model Access AWS Bedrock Pricing Feishu Bitable Configuration Step 1: Create Feishu Account and App Sign up at Feishu International Create a new Bitable (multi-dimensional table) Go to Developer Console → Create App Enable Bitable permissions in your app Generate App Token and App Secret Step 2: Create Bitable Structure Create a new Bitable with these columns: title (Text) pubDate (Date) summary (Long Text) keywords (Multi-select) rating (Single Select: Low, Medium, High) link (URL) approval_status (Single Select: Pending, Approved, Rejected) Get your App Token and Table ID: App Token: Found in app settings Table ID: Found in the Bitable URL (tbl...) Step 3: Set Up Automation In your Bitable, go to Automation → Create automation Trigger: When field value changes → Select approval_status field Condition: approval_status equals "Approved" Action: Send HTTP request Method: POST URL: Your n8n webhook URL (from Flow 2) Headers: Content-Type: application/json Body: {{record}} Step 4: Configure Feishu Credentials in n8n Install Feishu Lite community node (self-hosted only) Add Feishu credential with your App Token and App Secret Test the connection Useful Links: Feishu Developer Documentation Bitable API Reference Feishu Automation Guide LinkedIn Company Account Setup Step 1: Create LinkedIn App Go to LinkedIn Developer Portal Click Create App Fill in app details: App name: AWS News Automation LinkedIn Page: Select your company page App logo: Upload your logo Legal agreement: Accept terms Step 2: Configure OAuth2 Settings In your app, go to Auth tab Add redirect URL: https://your-n8n-instance.com/rest/oauth2-credential/callback Request these scopes: w_member_social (Post on behalf of members) r_liteprofile (Read basic profile) r_emailaddress (Read email address) Step 3: Get Company Page Access Go to your LinkedIn Company Page Navigate to Admin tools → Manage admins Ensure you have Content admin or Super admin role Note your Company Page ID (found in page URL) Step 4: Configure LinkedIn Credentials in n8n Add LinkedIn OAuth2 credential Enter your Client ID and Client Secret Complete OAuth2 flow by clicking Connect my account Select your company page for posting Useful Links: LinkedIn Developer Portal LinkedIn API Documentation LinkedIn OAuth2 Guide Workflow Activation Final Setup Steps: Import the workflow JSON into n8n Configure all credential connections: AWS Bedrock credentials Feishu credentials LinkedIn OAuth2 credentials Update webhook URL in Feishu automation to match your n8n instance Activate the scheduled trigger (daily at 8 PM) Test with manual webhook trigger using sample data Verify Feishu Bitable receives data Test approval workflow and LinkedIn posting Requirements Service Requirements AWS Bedrock** with Claude 3 Sonnet model access AWS account with Bedrock service enabled IAM user with Bedrock permissions Model access approval for Claude 3 Sonnet Feishu Bitable** for news storage and approval workflow Feishu account (International or Lark) Developer app with Bitable permissions Automation capabilities for webhook triggers LinkedIn Company Account** for automated posting LinkedIn company page with admin access LinkedIn Developer app with posting permissions OAuth2 authentication setup n8n community nodes**: Feishu Lite node (self-hosted only) Technical Requirements n8n instance** (self-hosted recommended for community nodes) Webhook endpoint** accessible from Feishu automation Internet connectivity** for API calls and RSS feeds Storage space** for workflow execution logs Cost Considerations AWS Bedrock**: ~$0.01-0.05 per news analysis Feishu**: Free tier available, paid plans for advanced features LinkedIn**: Free API access with rate limits n8n**: Self-hosted (free) or cloud subscription How to customize the workflow Content Customization Modify AI prompts** in the AI Agent nodes to change tone, focus, or target audience Adjust hashtags** in the LinkedIn posting node for different industries Change scheduling** frequency by modifying the Schedule Trigger settings Integration Options Replace LinkedIn** with Twitter/X, Facebook, or other social platforms Add Slack notifications** for approved content before posting Integrate with CRM** systems to track content performance Add content calendar** integration for better planning Advanced Features Multi-language support** by modifying AI prompts for different regions Content categorization** by adding tags for different AWS services Performance tracking** by integrating analytics platforms Team collaboration** by adding approval workflows with multiple reviewers Technical Modifications Change RSS sources** to monitor other AWS blogs or competitor news Adjust AI models** to use different Bedrock models or external APIs Add data validation** nodes for better error handling Implement retry logic** for failed API calls Important Notes Service Limitations This template uses community nodes (Feishu Lite) and requires self-hosted n8n Geo-restrictions** may apply to AWS Bedrock models in certain regions Rate limits** may affect high-frequency posting - adjust scheduling accordingly Content moderation** is recommended before automated posting Cost considerations**: Each AI analysis costs approximately $0.01-0.05 USD per news item Troubleshooting Common Issues AWS Bedrock Issues: Model not found**: Ensure Claude 3 Sonnet access is approved in your region Access denied**: Verify IAM permissions include Bedrock service access Rate limiting**: Implement retry logic or reduce analysis frequency Feishu Integration Issues: Authentication failed**: Check App Token and App Secret are correct Table not found**: Verify Table ID matches your Bitable URL Automation not triggering**: Ensure webhook URL is accessible and returns 200 status LinkedIn Posting Issues: OAuth2 errors**: Re-authenticate LinkedIn credentials Posting failed**: Verify company page admin permissions Rate limits**: LinkedIn has daily posting limits for company pages Security Best Practices Never hardcode credentials** in workflow nodes Use environment variables** for sensitive configuration Regularly rotate API keys** and access tokens Monitor API usage** to prevent unexpected charges Implement error handling** for failed API calls

Generate social posts from GitHub pushes to Twitter and LinkedIn On each GitHub push, this workflow checks if the commit set includes README.md and CHANGELOG.md, fetches both files, lets an LLM generate a Twitter and LinkedIn post, then publishes to Twitter and LinkedIn (Person). Apps & Nodes Trigger:** Webhook Logic:** IF, Merge, Aggregate GitHub:** Get Repository File (×2) Files:** Extract from File (text) (×2) AI:** OpenAI Chat Model → LLM Chain (+ Structured Output Parser) Publish:** Twitter, LinkedIn (Person) Prerequisites GitHub:** OAuth2 or PAT with repo read. OpenAI:** API key. Twitter:* OAuth2 app with *Read and Write; scopes tweet.read tweet.write users.read offline.access. LinkedIn (Person):* OAuth2 credentials; required scope:* w_member_social, openid. Setup GitHub Webhook: Repo → Settings → Webhooks Payload URL: https://<your-n8n-domain>/webhook/github/push Content type: application/json • Event: Push • Secret (optional) • Branches as needed. Credentials: Connect GitHub, OpenAI, Twitter, and LinkedIn (Person). How it Works Webhook receives GitHub push payload. IF checks that README and CHANGELOG appear in added/modified. GitHub (Get Repository File) pulls README.md and CHANGELOG.md. Extract from File (text) converts both binaries to text. Merge & Aggregate combines into one item with both contents. LLM (OpenAI + Parser) returns a JSON with twitter and linkedin. Twitter posts the tweet. LinkedIn (Person) posts the LinkedIn text.

How It Works ⚙️ This workflow is a comprehensive, AI-powered system that acts as a virtual content manager for creators and marketing teams. It automates the entire content lifecycle, from ingestion and analysis to multi-channel distribution and performance logging. Multi-Source Ingestion: The workflow starts by ingesting new content from a trigger, such as a WordPress blog post or an RSS Feed from a YouTube channel. AI-Powered Analysis: The new content is sent to an OpenAI (GPT-4) node, which performs a series of high-value tasks. It instantly creates a summary, extracts keywords, analyzes the sentiment, and generates tailored post drafts for different social media platforms. Smart Distribution: A Buffer node then takes these AI-generated, platform-specific posts and schedules them for optimal times across your social media channels like Twitter, LinkedIn, and Facebook. Centralized Archiving: All of the content data, including the AI-generated summaries and insights, are automatically logged into a Google Sheets database. This creates a powerful, searchable archive and an analytics dashboard for tracking content performance. How to Set Up 🛠️ Import the Workflow: Copy the provided workflow JSON and import it into your n8n instance. Configure Credentials: OpenAI: Add your API Key. WordPress: Add your API credentials. Buffer: Add your API credentials. Google Sheets: Add your OAuth2 credentials. Customize Workflow Nodes: Node 1 (WordPress Trigger): Select your WordPress credential. You can also add other trigger nodes like RSS Feed Read Trigger if needed. Node 2 (OpenAI): You can customize the prompt to get different kinds of output or translate into more languages. Node 4 (Buffer): Select the social media profiles you want to post to. Node 5 (Google Sheets): Replace the placeholder [YOUR SPREADSHEET ID] and [YOUR CONTENT LOG SHEET NAME] with your own details and map the data columns. Save & Activate: Once all settings and credentials are configured, save the workflow and click the "Inactive" toggle in the top-right corner to make it live.

Who is this template for? This workflow template is designed for teams involved in training management and feedback analysis. It is particularly useful for: HR Departments**: Automating the collection and response to training feedback. Training Managers**: Streamlining the process of handling feedback and ensuring timely follow-up. Corporate Trainers**: Receiving direct feedback and taking actions to improve training sessions. This workflow offers a comprehensive solution for automating feedback management, ensuring timely responses, and improving the quality of training programs. How it works This workflow operates with an Airtable trigger but can be easily adapted to work with other triggers like webhooks from external applications. Once feedback data is captured, the workflow evaluates the feedback and directs it to the appropriate channel for action. Tasks are created in Usertask based on the feedback rating, and notifications are sent to relevant parties. Here’s a brief overview of this n8n workflow template: Airtable Trigger**: Captures new or updated feedback entries from Airtable. Switch Node**: Evaluates the feedback rating and directs the workflow based on the rating. Webhook**: Retrieves the result of a Usertask task. Task Creation**: Creates tasks in Usertask for poor feedback. Creates follow-up tasks for fair to good feedback. Documents positive feedback and posts recognition on LinkedIn for very good to excellent ratings. Notifications**: Sends email notifications to responsible parties for urgent actions. Sends congratulatory emails and posts on LinkedIn for positive feedback. To summarize Flexible Integration**: This workflow can be triggered by various methods like Airtable updates or webhooks from other applications. Automated Task Management**: It creates tasks in Usertask based on feedback ratings to ensure timely follow-up. Multichannel Notifications**: Sends notifications via email and LinkedIn to keep stakeholders informed and recognize successes. Comprehensive Feedback Handling**: Automates the evaluation and response to training feedback, improving efficiency and response time. Instructions: Set Up Airtable: Create a table in Airtable to capture training feedback. Configure n8n: Set up the Airtable trigger in n8n to capture new or updated feedback entries. Set Up Usertask: Configure the Usertask nodes in n8n to create and manage tasks based on feedback ratings. Configure Email and LinkedIn Nodes: Set up the email and LinkedIn nodes to send notifications and post updates. Test the Workflow: Run tests to ensure the workflow captures feedback, creates tasks, and sends notifications correctly. Video : https://youtu.be/U14MhTcpqeY Remember, this template was created in n8n v1.38.2.