Workflow Templates

Who's this for? If you own a website and need to analyze your Google analytics data If you need to create an SEO report on which pages are getting most traffic or how your google search terms are performing If you want to grow your site based on suggestions from data Use case Instead of hiring an SEO expert, I run this report weekly. It checks compares the data from this week to the week before: Views based on countries The top performing pages Google search console performance Watch youtube tutorial here Get my SEO A.I. agent system here Read my detailed case study here How it works The workflow gathers google analytics for the past 7 days then it gathers the data for the week before for comparison. It does this 3 times to get: views per country, engagement per page and google search console results for organic search results. The google analytics nodes has already chosen the correct dimensions and metrics. At the end, it passes the data to openrouter.ai for A.I. analyse. Finally it saves to baserow. How to use this Input your Google analytics credentials Input your property ID Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Name, Country Views, Page Views, Search Report, Blog (name of your blog). Created by Rumjahn

Time Logging on Clockify Using Slack How it works This workflow simplifies time tracking for teams and agencies by integrating Slack with Clockify. It enables users to log, update, or delete time entries directly within Slack, leveraging an AI-powered assistant for seamless and conversational interactions. Key features include: Effortless Time Logging**: Create and manage time entries in Clockify without leaving Slack. AI-Powered Assistant**: Get step-by-step guidance to ensure accurate and efficient time logging. Project and Client Management**: Retrieve project and client information from Clockify effortlessly. Overlap Prevention**: Avoid overlapping entries with built-in time validation. Automated Descriptions**: Generate ethical, grammatically correct descriptions for time logs. Set up steps 1. Prepare your integrations Ensure you have active accounts for both Slack and Clockify. Generate your Clockify API credentials for integration. 2. Import the workflow Download and import the workflow template into your n8n instance. Configure the workflow to connect with your Slack and Clockify accounts. 3. Configure the workflow Add your Clockify API credentials in the workflow settings. Set up the Slack Trigger to listen for app mentions or specific commands. 4. Test the workflow Use Slack to create a time entry and verify it in Clockify. Test updating and deleting existing entries to ensure smooth functionality. Check for any overlapping time logs or incorrect data entries. Why use this workflow? Efficiency**: Eliminate the need to switch between tools for time tracking. Accuracy**: AI-driven validation ensures error-free entries. Automation**: Simplify repetitive tasks like updating or deleting time logs. Proactive Guidance**: Conversational assistant ensures smooth operations.

Linear Project/Issue Status and End Date to Productboard feature Sync Sync project and issue data between Linear and Productboard to keep teams aligned. This workflow updates Productboard features with the status and end date from Linear projects or due date from Linear issues. It ensures consistent data and sends a Slack notification whenever changes are made. Features Listens for updates in Linear projects/issues. Maps Linear statuses to Productboard feature statuses. Updates Productboard feature details including timeframe. Sends a Slack notification summarizing the updates. Setup Linear Credentials: Add your Linear API credentials in n8n. Productboard Credentials: Configure the Productboard API credentials in n8n. Linear Projects or Issues: Select the Linear project(s) or Issue(s) you want to monitor for updates. Productboard Custom Field: Create a custom field in Productboard named "Linear". This field should store the URL of the Linear project or issue you want to sync. Retrieve the UUID of the custom field in Productboard and set it up in the "Get Productboard Feature ID" node. Slack Notification: Update the Slack node with the desired Slack channel ID. Activate the Workflow: Enable the workflow to automatically sync data when triggered by updates in Linear.

✨ Summary Efficiently monitor Kubernetes environments by sending only unique error logs from Grafana Loki to Slack. Reduces alert fatigue while keeping your team informed about critical log events. 🧑‍💻 Who’s it for DevOps or SRE engineers running EKS/GKE/AKS Anyone using Grafana Loki and Promtail for centralized logging Teams that want Slack alerts but hate alert spam 🔍 What it does This n8n workflow queries your Loki logs every 5 minutes, filters only the critical ones (error, timeout, exception, etc.), removes duplicate alerts within the batch, and sends clean alerts to a Slack channel with full metadata (pod, namespace, node, container, log, timestamp). 🧠 How it works 🕒 Schedule Trigger Every 5 minutes (customizable) 🌐 Loki HTTP Query Pulls logs from the last 10 minutes Keyword match: error, failed, oom, etc. 🧹 Log Parsing Extracts log fields (pod, container, etc.) Skips empty/malformed results 🧠 Deduplication Removes repeated error messages (within query window) 📤 Slack Notification Sends nicely formatted message to Slack ⚙️ Requirements Tool Notes Loki- Exposed internally or externally Slack App- With chat:write OAuth n8n- Cloud or self-hosted 🔧 How to Set It Up Import the JSON file into n8n Update: Loki API URL (e.g., http://loki-gateway.monitoring.svc.cluster.local) Slack Bearer Token (via credentials) Target Slack channel (e.g., #k8s-alerts) (Optional) Change keywords in the query regex Activate the workflow Ensure n8n pod/container is having access to your kubernetes cluster/pods/namespaces 🛠 How to Customize Want more or fewer keywords? Adjust the regex in the Query Loki for Error Logs node. Need to increase deduplication logic? Enhance the Remove Duplicate Alerts node. Want 5-log summaries every 5 min? Fork this and add a Batch + Slack group sender. Grafana Loki logs to Slack Output

Automatically fetch existing domains from Notion's Database and verify the validity of SSL certificates through SSL-Checker. If the validity period is less than 14 days, send a Telegram message notification and trigger SSH remote automatic refresh. Successful refresh notification will be sent through Telegram. This can prevent problems with the server-side automatic refresh program, which may cause unexpected service interruptions. Main use cases: Notion store domain. Telegram receives warning messages. Remotely trigger Certbot to refresh SSL. How it works: Record who triggered this workflow, because if there is a credential that is about to expire, this workflow will be triggered repeatedly. After getting all the domains from Notion, send an http request to SSL-Checker. After getting all the SSL-Checker results, add the validity label. And use the IF node to check if there are any certificates that are about to expire. Then there are two workflows: If there is a certificate that is about to expire: send an SSH command to the remote control server to refresh the certificate, notify through Telegram, and call this workflow again to re-verify the validity of the SSL certificate. If the validity period of SSL is normal: then refresh the data on Notion, and if a re-called workflow is detected, Telegram will be used to notify that the SSL has been updated.

Who is this for? This workflow is ideal for individuals focused on nutrition tracking, meal planning, or diet optimization—whether you’re a health-conscious individual, fitness coach, or developer working on a healthtech app. It also fits well for anyone who wants to capture their meal data via voice or text, without manually entering everything into a spreadsheet. What problem is this workflow solving? Manually logging meals and breaking down their nutritional content is time-consuming and often skipped. This workflow automates that process using Telegram for input, OpenAI for natural language understanding, and Google Sheets for structured tracking. It enables users to record meals by typing or sending voice messages, which are transcribed, analyzed for nutrients, and automatically stored for tracking and review. What this workflow does This n8n automation lets users send either a text or voice message to a Telegram bot describing their meal. The workflow then: Receives the Telegram message Checks if it’s a voice message • If yes: Downloads the audio file and transcribes it using OpenAI • If no: Uses the text input directly Sends the meal description to OpenAI to extract a structured list of ingredients and nutritional details Parses and stores the results in Google Sheets Responds via Telegram with a personalized confirmation message A testing interface also allows you to simulate prompts and view structured outputs for development or debugging. Setup Create a Telegram bot via BotFather and note the API token. Create an empty Google Sheet and store the sheet ID in the environment. Set up your OpenAI credentials in the n8n credential manager. Customize the “List of Ingredients and Nutrients” node with your prompt if needed. (Optional) Use the “Testing” section to simulate messages and refine outputs before going live. How to customize this workflow to your needs • Enhance prompts in the OpenAI node to improve the structure and accuracy of responses. • Add new fields in the Google Sheet and corresponding logic in the parser if you want more detail. • Adjust the Telegram response to provide motivational feedback, dietary tips, or summaries. • Upgrade to the “Pro” version mentioned in the contact section for USDA database integration and complete nutrient breakdowns. This is a lightweight, AI-powered meal logging automation that transforms voice or text into actionable nutrition data—perfect for making healthy eating easier and more data-driven. See my other workflows here

This workflow is a comprehensive solution for digital marketers, performance agencies, and e-commerce brands looking to scale their creative testing process on Meta Ads efficiently. It eliminates the tedious manual work of uploading assets, creating campaigns, and setting up ads one by one. Use Case Manually launching weekly creative tests is time-consuming and prone to errors. This workflow solves that problem by creating a fully automated pipeline: from a creative asset in a folder to a complete, ready-to-launch (but paused) ad structure in your Meta Ads account. It's perfect for teams that want to: Save hours of manual work every week. Systematically test a high volume of creatives. Maintain a structured and consistent campaign naming convention. Keep a detailed log of all created assets for data-driven performance analysis. How it Works The workflow is structured into four logical blocks: 1. Configuration & Scheduling: The workflow runs on a weekly schedule. A central "Configuration" Set node at the beginning holds all key variables (Ad Account ID, Page ID, Pixel ID, making it incredibly easy to adapt the template for different projects. 2. Creative Ingestion & Processing: It scans a specific Google Drive folder for new image and video files. Using an IF node, it branches the logic based on the file type. Each file is uploaded to the Meta Ads library, and a corresponding Ad Creative is built with a pre-defined destination URL. 3. Campaign & Ad Set Assembly: The workflow creates a single new Campaign with an OUTCOME_SALES objective. It then creates a single Ad Set optimized for OFFSITE_CONVERSIONS (e.g., "Add to Cart"), using the Pixel ID from the configuration. A Merge node intelligently combines the single Ad Set ID with every creative processed in the previous block, preparing the data for the final step. 4. Ad Creation & Data Logging: The workflow iterates through the prepared data, creating a unique Ad for each creative. Upon the successful creation of each ad, a new row is appended to a Google Sheet, logging all relevant IDs (CampaignID, AdSetID, AdID, CreativeID) and metadata for a complete audit trail. Setup Instructions To use this template, you need to configure a few key nodes. 1. Credentials: Connect your Meta Ads account. Connect your Google account (for both Drive and Sheets). 2. The ⚙️ Configuration Node (Set node): This is the most important step. Open the first Set node and fill in your specific values: adAccountId: Your Meta Ad Account ID. pageId: The ID of the Facebook Page you're advertising for. pixelId: Your Meta Pixel ID for conversion tracking. 3. Google Sheets Node (Save Full Report to Sheet): Select your spreadsheet and the specific sheet where you want to save the reports. Make sure your sheet has columns with the following headers: CampaignID, AdSetID, AdID, CreativeID, FileName, MimeType, Timestamp. 4. Check URLs and IDs in HTTP Request Nodes: The template is configured to use the variables from the ⚙️ Configuration node. Double-check that the URLs in the Create Campaign, Create Ad Set, and Create ... Creative nodes correctly reference these variables (e.g., .../act_{{ $('⚙️ Configuration Meta Ads').item.json.adAccountId }}/campaigns). Verify the link in the Create Video Creative and Create Image Creative nodes points to your desired landing page. 5. Activate the Workflow: Set your desired schedule in the Schedule Trigger node. Save and activate the workflow. Further Ideas & Customization This workflow is a powerful foundation. You can easily extend it to: Create a second workflow** that runs a week later, reads the Google Sheet, and pulls performance data for all the ads created. A/B test ad copy** by adding different text variations from a spreadsheet. Add a Slack or Email notification** at the end to confirm that the weekly campaign launch was successful.

How it works Regulatory monitoring**: Continuously tracks changes in laws, regulations, and compliance requirements across multiple jurisdictions Contract analysis**: AI-powered review of existing contracts to identify compliance gaps and risks Automated alerts**: Real-time notifications when regulatory changes affect your contracts or business operations Compliance reporting**: Generates audit-ready reports and documentation for regulatory compliance Set up steps Legal databases**: Connect to legal research platforms (Westlaw, LexisNexis, EUR-Lex) Contract repository**: Integrate with your contract management system or document storage Regulatory feeds**: Configure government and regulatory body RSS feeds and APIs AI legal analysis**: Set up OpenAI or specialized legal AI for contract analysis Compliance calendar**: Integrate with calendar systems for deadline tracking Audit trail**: Configure logging and documentation systems for compliance records Key Features 🔍 Multi-jurisdiction monitoring**: Tracks regulatory changes across different countries and regions 📊 Risk assessment**: Automatically scores compliance risks and potential impact ⚡ Real-time alerts**: Instant notifications when regulations affecting your business change 📋 Gap analysis**: Identifies discrepancies between current contracts and new requirements 🤖 AI-powered analysis**: Uses natural language processing to understand legal text 📈 Compliance dashboard**: Visual overview of compliance status across all contracts 🔄 Automated remediation**: Suggests contract amendments and compliance actions 📱 Mobile notifications**: Critical compliance alerts on mobile devices Compliance areas monitored Data protection**: GDPR, CCPA, and other privacy regulations Financial services**: Banking regulations, securities law, anti-money laundering Healthcare**: HIPAA, medical device regulations, pharmaceutical compliance Employment law**: Labor regulations, workplace safety, discrimination laws Environmental**: ESG requirements, environmental protection regulations Industry-specific**: Sector-specific regulations and standards Contract types supported Vendor agreements**: Supplier contracts and service agreements Employment contracts**: Employee agreements and contractor terms Data processing agreements**: Privacy and data handling contracts Customer agreements**: Terms of service and customer contracts Partnership agreements**: Joint ventures and strategic partnerships Licensing agreements**: Software licenses and intellectual property Automated responses Low risk (0-30)**: Routine monitoring and documentation Medium risk (31-60)**: Enhanced review and stakeholder notification High risk (61-80)**: Immediate legal review and action planning Critical risk (81-100)**: Emergency legal intervention and compliance measures Integration capabilities Legal research**: Westlaw, LexisNexis, Bloomberg Law Document management**: SharePoint, Google Drive, Dropbox Contract systems**: DocuSign, PandaDoc, ContractWorks Communication tools**: Slack, Teams, email for legal team alerts Calendar systems**: Outlook, Google Calendar for compliance deadlines This workflow ensures continuous legal compliance by monitoring regulatory changes and automatically assessing their impact on your contracts and business operations.

Quick overview This workflow monitors Gmail and a Google Drive folder for new invoice/receipt files, uses Google Gemini to extract structured invoice data and classify expense categories, logs results to Google Sheets, and routes higher-value invoices to Slack for approve/reject decisions with automatic ledger updates. How it works Triggers every minute for unread Gmail messages with invoice/receipt attachments and for new files created in a specified Google Drive folder. Filters incoming files to PDFs or images, marking unsupported Gmail messages as read and notifying a Slack channel when a file type is skipped. Sends each supported document to Google Gemini to extract invoice fields as JSON, then parses and validates the output and posts to Slack when extraction is incomplete or totals don’t reconcile. Checks Google Sheets for an existing row with the same invoice number and, if found, skips logging and notifies Slack about the duplicate. Uses Google Gemini to assign an expense category, then determines whether the invoice requires approval based on a total amount threshold. Appends the invoice to a Google Sheets ledger as Approved for under-threshold totals, or as Pending Review and sends a Slack message with Approve/Reject buttons for over-threshold totals. Waits up to three days for the Slack decision and then updates the matching Google Sheets row to Approved, Rejected, or No Response, while posting a Slack alert if the workflow errors. Setup Add credentials for Gmail, Google Drive, Google Sheets, Google Gemini (PaLM API), and Slack. Create/select a Google Sheets document with an invoices sheet and columns matching the fields this workflow writes (for example: vendor_name, invoice_number, invoice_date, due_date, subtotal, tax, total, currency, category, source, needsApproval, status) and set the document in all Google Sheets nodes. Choose the Google Drive folder to watch and set the target Slack channel in each Slack node. For Slack approvals, configure a Slack app with interactivity enabled, set the Request URL to your n8n waiting webhook endpoint, and provide the bot token and signing secret in the Slack credential. In n8n workflow settings, set this workflow as the error workflow (or ensure the Error Trigger is enabled) so failures post to Slack, then activate the workflow.

Introduction **Manual LinkedIn data collection is time-consuming, error-prone, and results in inconsistent data quality across CRM/database records.** This workflow is great for organizations that struggle with: Incomplete contact records with only LinkedIn URLs but missing profile details Hours spent manually copying LinkedIn information into databases Inconsistent data formats due to copy-paste from LinkedIn (emojis, styled text, special characters) Outdated profile information that doesn't reflect current roles/companies No systematic way to enrich contacts at scale Primary Users Sales & Marketing Teams Event Organizers & Conference Managers for event materials Recruitment & HR Professionals CRM Administrators Specific Problems Addressed Data Completeness: Automatically fills missing profile fields (headline, bio, skills, experience) Data Quality: Sanitizes problematic characters that break databases/exports Time Efficiency: Reduces hours of manual data entry to automated monthly updates Error Handling: Gracefully manages invalid/deleted LinkedIn profiles Scalability: Processes multiple profiles in batch without manual intervention Standardization: Ensures consistent data format across all records Cost Each URL scraped by Apify costs $0.01 to get all the data above. Apify charges per scrape, regardless of how much dta or fields you extract/use. Setup Instructions Prerequisites n8n Instance: Access to a running n8n instance (self-hosted or cloud) NocoDB Account: Database with a table containing LinkedIn URLs Apify Account: Free or paid account for LinkedIn scraping Required fields in NocoDB table Input: single LinkedIn URL NocoDB Field name LinkedIn Output: first/last/full name e-mail bio headline profile pic URL current role country skills current employer employer URL experiences (all previous jobs) personal website publications (articles) NocoDB Field names linkedin_full_name linkedin_first_name: linkedin_headline: linkedin_email: linkedin_bio: linkedin_profile_pic linkedin_current_role linkedin_current_company linkedin_country linkedin_skills linkedin_company_website linkedin_experiences linkedin_personal_website linkedin_publications linkedin_scrape_error_reason linkedin_scrape_last_attempt linkedin_scrape_status linkedin_last_modified Technically you also need an Id field, but that is always there so no need to add it :) n8n Setup 1. Import the Workflow Copy the workflow JSON from the template In n8n, click "Add workflow" → "Import from JSON" Paste the workflow and click "Import" 2. Configure NocoDB Connection Click on any NocoDB node in the workflow Add new credentials → "NocoDB Token account" Enter your NocoDB API token (found in NocoDB → User Settings → API Tokens) Update the projectId and table parameters in all NocoDB nodes 3. Set Up Apify Integration Create an Apify account at apify.com Generate an API token (Settings → Integrations → API) In the workflow, update the Apify token in the "Get Scraper Results" node Configure HTTP Query Auth credentials with your token 4. Map Your Database Fields Review the "Transform & Sanitize Data" node Update field mappings to match your NocoDB table structure Ensure these fields exist in your table: LinkedIn (URL field) linkedin_headline, linkedin_full_name, linkedin_bio, etc. linkedin_scrape_status, linkedin_last_modified 5. Configure the Filter In "Get Guests with LinkedIn" node Adjust the filter to match your requirements Default: (LinkedIn,isnot,null)~and(linkedin_headline,is,null) 6. Test the Workflow Click "Execute Workflow" with Manual Trigger Monitor execution for any errors Verify data is properly updated in NocoDB 7. Activate Automated Schedule Configure the Schedule Trigger node (default: monthly) Toggle the workflow to "Active" Monitor executions in n8n dashboard Customization Options 1. Data Source Modifications Different Database: Replace NocoDB nodes with Airtable, Google Sheets, or PostgreSQL Multiple Tables: Add parallel branches to process different contact tables Custom Filters: Modify the WHERE clause to target specific record subsets 2. Enrichment Fields Add Fields: Include additional LinkedIn data like education, certifications, or recommendations Remove Fields: Simplify by removing unnecessary fields (publications, skills) Custom Transformations: Add business logic for field calculations or formatting 3. Scheduling Options Frequency: Change from monthly to daily, weekly, or hourly Time-based: Set specific times for different timezones Event-triggered: Replace with webhook trigger for on-demand processing 4. Error Handling Enhancement Notifications: Add email/Slack nodes to alert on failures Retry Logic: Implement wait and retry for temporary failures Logging: Add database logging for audit trails 5. Data Quality Rules Validation: Add IF nodes to validate data before updates Duplicate Detection: Check for existing records before creating new ones Data Standardization: Add custom sanitization rules for industry-specific needs 6. Integration Extensions CRM Sync: Add nodes to push data to Salesforce, HubSpot, or Pipedrive AI Enhancement: Use OpenAI to summarize bios or extract key skills Image Processing: Download and store profile pictures locally 7. Performance Optimization Batch Size: Adjust the number of profiles processed per run Rate Limiting: Add delays between API calls to avoid limits Parallel Processing: Split large datasets across multiple workflow executions 8. Compliance Additions GDPR Compliance: Add consent checking before processing Data Retention: Implement automatic cleanup of old records Audit Logging: Track who accessed what data and when These customizations allow the workflow to adapt from simple contact enrichment to complex data pipeline scenarios across various industries and use cases.

💼 LinkedIn Job Finder Automation using Bright Data API & Google Sheets A comprehensive n8n automation that searches LinkedIn job postings using Bright Data’s API and automatically organizes results in Google Sheets for efficient job hunting and recruitment workflows. 📋 Overview This workflow provides an automated LinkedIn job search solution that collects job postings based on your search criteria and organizes them in Google Sheets. Perfect for job seekers, recruiters, HR professionals, and talent acquisition teams. ✨ Key Features 🔍 Smart Job Search:** Form-based input for city, job title, country, and job type 🛍 LinkedIn Integration:** Uses Bright Data’s LinkedIn dataset for accurate job posting data 📊 Automated Organization:** Populates Google Sheets with structured job data 📧 Real-time Processing:** Processes job search requests in real-time 📈 Data Storage:** Stores job details including company info, locations, and apply links 🔄 Batch Processing:** Handles multiple job postings efficiently ⚡ Fast & Reliable:** Built-in error handling for scraping 🎯 Customizable Filters:** Advanced job filtering based on criteria 🎯 What This Workflow Does Input Job Search Criteria:** City, job title, country, and optional job type Search Parameters:** Configurable filters and limits Output Preferences:** Google Sheets destination Processing Steps Form Submission Data Request to Bright Data API Status Monitoring Data Extraction Data Filtering Sheet Update Error Handling Output Data Points Field Description Example Job Title Position title from posting Senior Software Engineer Company Name Employer company name Tech Solutions Inc. Job Detail Job summary/description Remote position requiring 5+ years… Location Job location San Francisco, CA Company URL Company profile link View Profile Apply Link Direct application link Apply Now 🚀 Setup Instructions Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access Bright Data account with LinkedIn dataset access Steps Import the Workflow: Use JSON import in n8n Configure Bright Data: Add API credentials and dataset ID Configure Google Sheets: Create sheet, set credentials, map columns Update Workflow Settings: Replace placeholders with your actual data Test & Activate: Submit test form and verify data in Google Sheets 📖 Usage Guide Submitting Job Searches Go to your webhook URL and fill in the form with: City:** e.g., New York Job Title:** e.g., Software Engineer Country:** e.g., US Job Type:** Optional (Full-Time, Remote, etc.) Understanding Results Comprehensive job data Company info and profile links Direct application links Location and job descriptions Customizing Search Parameters Edit the Create Snapshot ID node to change: Time range (e.g., “Past month”) Result limits Company filters 🔧 Customization Options More Data Points:** Add salary, seniority, applicants, etc. Custom Form Fields:** Add filters for salary, experience, industry Multiple Sheets:** Route results by job type or location 🚨 Troubleshooting Bright Data connection failed:** Check API credentials and dataset access No job data extracted:** Verify search parameters and API limits Google Sheets permission denied:** Re-authenticate and check sharing Form not working:** Check webhook URL and field mappings Filter issues:** Review logic and data types Execution failed:** Check logs, retry logic, and network status 📊 Use Cases & Examples Job Seeker Dashboard:** Automate job search and track applications Recruitment Pipeline:** Source candidates and monitor hiring trends Market Research:** Analyze job trends and salary benchmarks HR Analytics:** Support workforce planning and competitive insights ⚙️ Advanced Configuration Batch Processing:** Queue multiple searches with delays Search History:** Track and analyze past searches Tool Integration:** Connect to CRM, Slack, databases, BI tools 📈 Performance & Limits Processing Time:** 30–60 seconds per search Concurrent Requests:** 2–3 (depends on Bright Data plan) Data Accuracy:** 95%+ Success Rate:** 90%+ Daily Capacity:** 50–200 searches Memory:** ~50MB per execution API Calls:** 3–4 Bright Data + 1 Google Sheets per search 🤝 Support & Community n8n Community:** community.n8n.io Documentation:** docs.n8n.io Bright Data Support:** Via your Bright Data dashboard GitHub Issues:** Report bugs and request features 🎯 Ready to Use! Your workflow is ready for automated LinkedIn job searching. Customize it to your recruiting or job search needs. Webhook URL: https://your-n8n-instance.com/webhook/linkedin-job-finder What Gets Extracted: * ✅ Job Title * ✅ Company Information * ✅ Location Data * ✅ Job Details * ✅ Application Links * ✅ Processing Timestamps ### Use Cases: * 🔍 Job Search Automation * 📊 Recruitment Intelligence * 📝 Market Research * 🎯 HR Analytics

This n8n template monitors active support issues in Linear.app to track the mood of their ongoing conversation between reporter and assignee using Sentiment Analysis. When sentiment dips into the negative, a notification is sent via Slack to alert the team. How it works A scheduled trigger is used to fetch recently updated issues in Linear using the GraphQL node. Each issue's comments thread is passed into a simple Information Extractor node to identify the overall sentiment. The resulting sentiment analysis combined with the some issue details are uploaded to Airtable for review. When the template is re-run at a later date, each issue is re-analysed for sentiment Each issue's new sentiment state is saved to the airtable whilst its previous state is moved to the "previous sentiment" column. An Airtable trigger is used to watch for recently updated rows Each matching Airtable row is filtered to check if it has a previous non-negative state but now has a negative state in its current sentiment. The results are sent via notification to a team slack channel for priority. Check out the sample Airtable here: https://airtable.com/appViDaeaFw4qv9La/shrq6HgeYzpW6uwXL How to use Modify the GraphQL filter to fetch issues to a relevant issue type, team or person. Update the Slack channel to ensure messages are sent to the correct location or persons. The Airtable also serves to give a snapshot of Sentiment across support tickets for a given period. It's possible to use this to assess the daily operations. Requirements Linear for issue tracking (but feel free to use another system if preferred) Airtable for Database OpenAI for LLM and Sentiment Analysis Customising the workflow Add more granular levels of sentiment to reduce the number of alerts. Explore different types of sentiment based on issue types and customer types. This may help prioritise alerts and response. Run across teams or categories of issues to get an overview of sentiment across the support organisation.