Workflow Templates

This n8n template demonstrates a “Human-in-the-Loop” workflow where AI automatically drafts replies to inbound emails, which are then reviewed and approved by a human before being sent. This powerful pattern ensures both the efficiency of AI and the quality assurance of human oversight. Use cases are many: Streamline sales inquiry responses, manage first-level customer support, handle initial recruitment communications, or any business process that requires personalized yet consistent email replies. Good to know At the time of writing, the cost per execution depends on your OpenAI API usage. This workflow uses a cost-effective model like gpt-4o-mini. See OpenAI Pricing for updated info. The AI’s knowledge base and persona are fully customizable within the Basic LLM Chain node’s prompt. How it works The Gmail Trigger node starts the workflow whenever a new email arrives in the specified inbox. The Classify Potential Leads node uses AI to determine if the incoming email is a potential lead. If not, the workflow stops. The Basic LLM Chain, powered by an OpenAI Chat Model, generates a draft reply based on a detailed system prompt and your internal knowledge base. A Structured Output Parser is crucially used to force the AI’s output into a reliable JSON format ({"subject": "...", "body": "..."}), preventing errors in subsequent steps. The Send for Review Gmail node sends the AI-generated draft to a human reviewer and pauses the workflow, waiting for a reply. The IF node checks the reviewer’s reply for approval keywords (e.g., “approve”, “承認”). If approved, the ✅ Send to Customer Gmail node sends the final email to the original customer. If not approved, the reviewer’s feedback is treated as a revision request, and the workflow loops back to the Basic LLM Chain to generate a new draft incorporating the feedback. How to use Gmail Trigger** node: Configure with your own Gmail account credentials. Send for Review** node: Replace the placeholder email reviewer@example.com with the actual reviewer's email address. IF** node: You can customize the approval keywords to match your team’s vocabulary. OpenAI Nodes**: Ensure your OpenAI credentials are set up. You can select a different model if needed, but the prompt is optimized for models like GPT-4o mini. Requirements An OpenAI account for the LLM. A Gmail account for receiving customer emails and for the review process. Customising this workflow By modifying the prompt and knowledge base in the Basic LLM Chain, you can adapt this agent for various departments, such as technical support, HR, or public relations. The approval channel is not limited to Gmail. You can easily replace the review nodes with Slack or Microsoft Teams nodes to fit your internal communication tools.

Who's it for Customer support teams, SaaS companies, and service businesses that need to quickly identify and respond to urgent customer issues. Perfect for organizations handling high ticket volumes where manual prioritization creates delays and missed critical issues. How it works This workflow automatically analyzes incoming Zendesk tickets using OpenAI's GPT-4 to determine urgency levels and routes high-priority issues to your team via Slack notifications. The system monitors new Zendesk tickets via webhook, extracts key information (subject, description, customer details), and sends this data to OpenAI for intelligent analysis. The AI considers factors like emotional language, business impact keywords, technical severity indicators, and customer context to assign an urgency score from 1-5. Based on the AI analysis, the workflow automatically updates the ticket priority in Zendesk, adds detailed reasoning as a private note, and sends formatted Slack notifications for high-priority issues (score 4+). The Slack alert includes ticket details, urgency reasoning, key indicators found, and direct links to the ticket for immediate action. How to set up Prerequisites: Zendesk account with API access OpenAI API key (GPT-4 access recommended) Slack workspace with webhook permissions n8n instance (cloud or self-hosted) Setup steps: Configure credentials in n8n: Add OpenAI API credential with your API key Add Zendesk API credential (email + API token) Add Slack API credential (bot token with chat:write permissions) Update Configuration Variables node: Set your Zendesk subdomain (e.g., "yourcompany" for yourcompany.zendesk.com) Configure Slack channel for urgent alerts (e.g., "#support-urgent") Adjust urgency threshold (1-5, default is 4) Set default assignee email for fallback scenarios Set up Zendesk webhook: Copy the webhook URL from the trigger node In Zendesk Admin, go to Settings > Extensions > Add target Create HTTP target with the copied URL and POST method Create a trigger for "Ticket is created" that sends to this target Test the workflow: Create a test ticket with urgent language ("system is down", "critical issue") Verify the AI analysis runs and priority is updated Check that Slack notifications appear for high-priority tickets Confirm ticket updates include AI reasoning in private notes Requirements Zendesk** account with API access and admin permissions for webhook setup OpenAI API key** with GPT-4 access (estimated cost: $0.01-0.05 per ticket analysis) Slack workspace** with bot creation permissions and access to notification channels n8n instance** (cloud subscription or self-hosted installation) How to customize the workflow Adjust AI analysis parameters: Modify the system prompt in the OpenAI node to focus on industry-specific urgency indicators Add custom keywords or phrases relevant to your business in the prompt Adjust the temperature setting (0.1-0.5) for more consistent vs creative analysis Configure priority mapping: Edit the Code node to change how urgency scores map to Zendesk priorities Add custom business logic based on customer tiers or product types Implement time-based urgency (e.g., higher priority during business hours) Enhance Slack notifications: Customize the Slack message blocks with additional fields (product, customer tier, SLA deadline) Add action buttons for common responses ("Acknowledge", "Escalate", "Assign to me") Route different urgency levels to different Slack channels Extend integrations: Add email notifications using the Email node for critical issues Integrate with PagerDuty or Opsgenie for after-hours escalation Connect to your CRM to enrich customer context before AI analysis Add Teams or Discord notifications as alternatives to Slack Advanced customizations: Implement machine learning feedback loops by tracking resolution times vs AI scores Add sentiment analysis as a separate factor in priority calculation Create daily/weekly summary reports of AI analysis accuracy Build approval workflows for certain priority changes before auto-updating

This workflow automatically sends timely medication reminders to patients after a prescription is marked as sent in the system. It reads the medication schedule from prescription data, schedules reminders for each dosage time, and delivers notifications via WhatsApp, SMS, or email. All reminders are tracked and logged, ensuring patients stay on track with their treatment while providing healthcare providers with acknowledgment records. 📋 Simple Google Sheets Structure "Prescriptions" Sheet - Required columns: prescription_id patient_name patient_phone patient_email medication dosage times_per_day (1, 2, 3, or 4) duration_days (7, 14, 30, etc.) start_date (YYYY-MM-DD) prescription_status (set to "sent") reminders_created (auto-updated to "yes") "Reminders" Sheet (auto-created): Simple tracking of all scheduled reminders 🔧 Workflow Components (Only 10 Nodes!) Part 1: Schedule Creation Watch Sheet → Monitors for "sent" prescriptions Filter New → Only processes unscheduled prescriptions Create Schedule → Generates reminder times automatically Save Reminders → Stores schedule in sheet Mark Processed → Prevents duplicate scheduling Part 2: Send Reminders Cron Timer → Checks every 10 minutes Get Reminders → Retrieves all scheduled reminders Find Due → Identifies reminders due now Send Messages → WhatsApp + Email simultaneously Mark Sent → Updates status to prevent duplicates ⚙️ Simple Setup Replace these values: YOUR_GOOGLE_SHEET_ID YOUR_WHATSAPP_PHONE_NUMBER_ID Email sender address Add credentials: Google Sheets API WhatsApp API SMTP for email Sample data: prescription_id: RX001 patient_name: John Doe patient_phone: +1234567890 patient_email: john@email.com medication: Amoxicillin 500mg dosage: 1 tablet times_per_day: 3 duration_days: 7 start_date: 2025-01-15 prescription_status: sent reminders_created: no 📱 Default Schedule 1x daily:** 9:00 AM 2x daily:** 9:00 AM, 9:00 PM 3x daily:** 8:00 AM, 2:00 PM, 8:00 PM 4x daily:** 8:00 AM, 12:00 PM, 4:00 PM, 8:00 PM

How it works This workflow automatically generates a weekly sales performance report from Google Sheets data. It runs on a schedule, cleans and filters the dataset, and calculates week-over-week performance metrics. An AI model generates a concise business summary, while a chart visualizes category performance. Finally, the report is formatted into a professional HTML email and sent via Gmail. Step-by-step Trigger & fetch data** Schedule Trigger1 – Runs the workflow weekly at a defined time. Get row(s) in sheet1 – Fetches raw sales data from Google Sheets. Clean & prepare data** Removing Empty Rows1 – Cleans dataset by removing empty rows and formatting numbers. Filter Latest Week1 – Filters data to include only the relevant weekly range. Sales Analytics Engine – Calculates totals, growth %, category performance, and prepares structured output. Generate insights & visuals** Message a model – Uses AI to generate a short performance summary and recommendations. HTTP Request1 – Generates a bar chart comparing category performance using QuickChart. Format & send report** Format Email1 – Builds a styled HTML email with KPIs, insights, and tables. Send Email1 – Sends the final report via Gmail to the configured recipient. Why use this? Automates weekly reporting with zero manual effort Provides AI-driven insights for better decision-making Visualizes performance trends clearly with charts Improves communication with clean, professional email reports Saves time on data cleaning, analysis, and formatting

Track your daily mood in one tap and receive automated AI summaries of your emotional trends every week and month. Perfect for self-reflection, wellness tracking, or personal analytics. This workflow logs moods sent through a webhook (/mood) into Data Tables, analyzes them weekly and monthly with OpenAI (GPT-4o), and emails you clear summaries and actionable recommendations via Gmail. ⚙️ How It Works Webhook – Mood → Collects new entries (🙂, 😐, or 😩) plus an optional note. Set Mood Data → Adds date, hour, and note fields automatically. Insert Mood Row → Stores each record in a Data Table. Weekly Schedule (Sunday 20:00) → Aggregates the last 7 days and sends a summarized report. Monthly Schedule (Day 1 at 08:00) → Aggregates the last 30 days for a deeper AI analysis. OpenAI Analysis → Generates insights, patterns, and 3 actionable recommendations. Gmail → Sends the full report (chart + AI text) to your inbox. 📊 Example Auto-Email Weekly Mood Summary (last 7 days) 🙂 5 ██████████ 😐 2 ████ 😩 0 Average: 1.7 (Positive 🙂) AI Insights: You’re trending upward this week — notes show that exercise days improved mood. Try keeping short walks mid-week to stabilize energy. 🧩 Requirements n8n Data Tables enabled OpenAI credential (GPT-4o or GPT-4 Turbo) Gmail OAuth2 credential to send summaries 🔧 Setup Instructions Connect your credentials: Add your own OpenAI and Gmail OAuth2 credentials. Set your Data Table ID: Open the Insert Mood Row node and enter your own Data Table ID. Without this, new moods won’t be stored. Replace the email placeholder: In the Gmail nodes, replace your.email@example.com with your actual address. Deploy and run: Send a test POST request to /mood (e.g. { "mood": "🙂", "note": "productive day" }) to log your first entry. ⚠️ Before activating the workflow, ensure you have configured the Data Table ID in the “Insert Mood Row” node. 🧠 AI Analysis Interprets mood patterns using GPT-4o. Highlights trends, potential triggers, and suggests 3 specific actions. Runs automatically every week and month. 🔒 Security No personal data is exposed outside your n8n instance. Always remove or anonymize credential references before sharing publicly. 💡 Ideal For Personal mood journaling and AI feedback Therapists tracking client progress Productivity or self-quantification projects 🗒️ Sticky Notes Guide 🟡 Mood Logging Webhook POST /mood receives mood + optional note. ⚠️ Configure your own Data Table ID in the “Insert Mood Row” node before running. 🟢 Weekly Summary Runs every Sunday 20:00 → aggregates last 7 days → generates AI insights + emails report. 🔵 Monthly Summary Runs on Day 1 at 08:00 → aggregates last 30 days → creates monthly reflection. 🟣 AI Analysis Uses OpenAI GPT-4o to interpret trends and recommend actions. 🟠 Email Delivery Sends formatted summaries to your inbox automatically.

This n8n workflow template creates an intelligent data analysis chatbot that can answer questions about data stored in Google Sheets using OpenAI's GPT-5 Mini model. The system automatically analyzes your spreadsheet data and provides insights through natural language conversations. What This Workflow Does Chat Interface**: Provides a conversational interface for asking questions about your data Smart Data Analysis**: Uses AI to understand column structures and data relationships Google Sheets Integration**: Connects directly to your Google Sheets data Memory Buffer**: Maintains conversation context for follow-up questions Automated Column Detection**: Automatically identifies and describes your data columns 🚀 Try It Out! 1. Set Up OpenAI Connection Get Your API Key Visit the OpenAI API Keys page. Go to OpenAI Billing. Add funds to your billing account. Copy your API key into your OpenAI credentials in n8n (or your chosen platform). 2. Prepare Your Google Sheet Connect Your Data in Google Sheets Data must follow this format: Sample Marketing Data First row** contains column names. Data should be in rows 2–100. Log in using OAuth, then select your workbook and sheet. 3. Ask Questions of Your Data You can ask natural language questions to analyze your marketing data, such as: Total spend** across all campaigns. Spend for Paid Search only**. Month-over-month changes** in ad spend. Top-performing campaigns** by conversion rate. Cost per lead** for each channel. 📬 Need Help or Want to Customize This? 📧 rbreen@ynteractive.com 🔗 LinkedIn 🔗 n8n Automation Experts

Who’s it for This template is perfect for SEO writers, niche bloggers, and content marketers who want to generate high-quality blog posts from a single keyword without spending hours on research and writing. If you often find yourself stuck at the research stage or manually drafting blog content, this workflow automates the entire process from topic discovery to publication. What it does The workflow takes a keyword, performs a Google search using Dumpling AI, analyzes the top-ranking pages and People Also Ask (PAA) questions, and then uses GPT-4 to generate a detailed blog post based on the most valuable question. The blog draft is sent for approval via email, and once approved, it’s automatically published to WordPress. Here’s what happens step by step: Receives a keyword through a simple form Uses Dumpling AI to perform a Google search and extract: Top 2 organic search results People Also Ask (PAA) questions and answers Top related searches Filters for insightful PAA questions Sends the data to GPT-4 to generate a blog post in JSON format Emails the draft blog post for manual review and approval If approved, publishes the post automatically to WordPress How it works Form Trigger: Captures the keyword input Dumpling AI: Searches Google and extracts SEO data including top results, PAA, and related searches Code Node: Processes the raw search data into a structured format for GPT-4 Filter Node: Checks if PAA questions are available GPT-4: Chooses a strong PAA question and writes the blog post Gmail: Sends the draft blog post to your inbox for review Approval Node: Waits for manual approval WordPress: Publishes the approved post automatically Requirements ✅ Dumpling AI API key stored securely as credentials ✅ OpenAI GPT-4 credentials ✅ Gmail account with OAuth2 connected to n8n ✅ WordPress account with API credentials configured How to customize Edit the GPT-4 prompt to control the blog structure, tone, or style Add extra filters to select specific types of PAA questions (e.g., how-to, guides) Change the review recipient email in the Gmail node Add additional formatting or SEO optimization steps before publishing Integrate with Notion, Airtable, or Slack to log or notify team members after publication > This workflow turns a single keyword into a fully researched, GPT-4 generated, and auto-published blog post — helping you scale content creation efficiently while maintaining quality.

Monthly Energy Generation Report (PostgreSQL → PDF → Email) This workflow automatically collects monthly energy generation data from a PostgreSQL database, converts it into a structured PDF report and emails it to stakeholders. It eliminates manual report creation and ensures timely delivery of performance summaries. Who’s it for Energy companies monitoring solar, wind or hydro generation Operations & maintenance (O\&M) teams needing monthly summaries Managers and executives who require periodic performance reports Data analysts who want automated reporting instead of manual exports How it works Monthly Trigger → Schedules the workflow to run once a month. Postgres Node → Fetches energy data from the energy_data table. Code Node (Transform Data) → Structures the raw records into JSON with metadata (date_range, records, note). HTTP Request (PDF.co API) → Converts structured data into a formatted PDF report. Gmail Node (Send Report) → Sends the PDF report (or link) via email to the configured recipient. How to set up Import the workflow JSON into n8n. Configure credentials: PostgreSQL connection (DB host, user, password, database, schema). Gmail OAuth2 credentials. PDF.co API key (for HTML → PDF conversion). Update: Database table (energy_data). Email recipients in the Gmail node. PDF template (if custom formatting is required). Activate workflow. Requirements n8n (self-hosted or cloud) PostgreSQL database with energy generation data PDF.co API account with valid API key Gmail account with OAuth2 access Internet access for API calls How to customize Change the SQL query in the Postgres node to filter specific plants or date ranges. Update the Code node to add extra fields (e.g., average power, anomalies). Modify the PDF.co request body to use a custom HTML template for branding. Replace Gmail with Outlook, SMTP, or Slack for distribution. Add-ons Add Slack/Teams node to notify teams when reports are sent. Store PDFs in Google Drive or S3 for archival. Add a dashboard (e.g., Grafana or Superset) that references the same DB for real-time view. Integrate with Jira to auto-create tasks for underperformance alerts. Use Case Examples Solar company emailing monthly reports to plant owners. Wind farm operator generating regulatory compliance reports. O&M teams automating KPI summaries for executives. Consulting firms monitoring multiple clients’ energy production. Common Troubleshooting | Issue | Possible Cause | Solution | | ------------------------------ | -------------------------------------- | ------------------------------------------------------- | | Workflow does not trigger | Cron not set correctly | Verify Schedule Trigger node interval is monthly | | No data returned from Postgres | Wrong schema/table or DB creds | Check DB connection and table name | | PDF not generated | Invalid/missing PDF.co API key | Generate a new key in PDF.co dashboard | | Email not sent | Gmail OAuth expired or wrong recipient | Reconnect Gmail credentials and confirm recipient email | | PDF output malformed | Incorrect JSON → HTML conversion | Check Code node formatting and PDF.co request body | Need Help? Our n8n workflow automation experts at WeblineIndia can help you: Set up the PostgreSQL connection securely, Customize the PDF layout with your company branding, Add more delivery channels (Slack, Teams, S3), Extend reporting logic (KPIs, charts, anomaly detection), And so much more.

🎯 Accounting Alerts Automation Purpose: Automatically track Companies House filing deadlines for UK accounting firms and prevent costly penalties (£150-£1,500 per missed deadline). How it works: Daily automated checks pull live deadline data from Companies House API Color-coded email alerts (Red/Orange/Yellow/Green) prioritize urgent deadlines Interactive "Yes/No" buttons let recipients confirm completion status All data syncs back to Google Sheets for complete audit trail Value: Saves 2-3 hours/week per firm while eliminating manual tracking errors. ⚙️ Daily Deadline Check & Alert System Runs: Every weekday at 5 PM (Mon-Fri) What happens: Read Company Database - Fetches all tracked companies from Google Sheets Get Company Data - Pulls live filing deadlines from Companies House API for each company Update Due Dates - Syncs latest deadline data back to the tracking sheet Build Interactive Email - Creates HTML email with: Color-coded urgency indicators (days remaining) Sortable table by due date Clickable Yes/No confirmation buttons for each company Send via Gmail - Delivers consolidated report to accounting team Why automated: Manual deadline checking across 10-50+ companies is time-consuming and error-prone. This ensures nothing falls through the cracks. ✅ Email Response Handler (Webhook Flow) Triggered when: Recipient clicks "Yes" or "No" button in the alert email What happens: Webhook - Receives confirmation status (company_number, company_name, yes/no) Process Data - Extracts response details from the webhook payload Update Sheet - Records confirmation status in Google Sheets with timestamp Confirmation Page - Displays success message to user Why this matters: Provides instant feedback to the user and creates an audit trail of who confirmed what and when. No separate tracking system needed—everything updates automatically in the same spreadsheet. Result: Accountability without administrative burden. 📋 Setup Requirements Google Sheets Database Structure: Create a sheet with these columns: company_number (manually entered) company_name (manually entered) accounts_due (auto-updated) confirmation_due (auto-updated) confirmation_submitted (updated via email clicks) last_updated (auto-timestamp) Required Credentials: Google Sheets OAuth (for reading/writing data) Companies House API key (free from api.company-information.service.gov.uk) Gmail OAuth (for sending alerts) Webhook Configuration: Update webhook URL in "Build Interactive Email" node to match your n8n instance. Time to Setup: ~15 minutes once credentials are configured.

📊 Description Most career advice is generic. This workflow builds a fully personalized AI coaching system that remembers every user, adapts to their career stage and goals, detects what kind of help they need, and gets more contextual with every conversation. It is not a simple chatbot — it is a structured coaching engine with user profiling, conversation memory, intent routing, and proactive weekly outreach. Built for women's communities, coaching platforms, HR teams, and edtech creators who want to deliver real personalized career support at scale without hiring a team of coaches. What This Workflow Does 💬 Opens a chat interface where users can start talking immediately — no signup required 🧮 Detects if the user is new or returning on every message using Google Sheets as a user database 📋 Walks new users through a 4-step onboarding — name, career stage, biggest challenge, and monthly goal 🗂️ Stores and updates every user profile in Google Sheets with full onboarding state tracking 🔍 Detects intent from every coaching message across 6 categories — salary negotiation, interview prep, career change, leadership, confidence building, and work-life balance 🤖 Routes each message to a topic-specific GPT-4o system prompt tailored to that coaching category 💬 Loads the last 5 conversations from history to give GPT-4o full context before generating a response ✅ Responds with personalized advice, one actionable step for today, and a follow-up question to keep momentum 📝 Logs every conversation to Google Sheets with timestamp, message, intent, and AI response 📧 Sends every fully onboarded user a personalized weekly check-in email every Sunday with a weekly challenge, progress acknowledgment, and motivational quote from a woman leader Key Benefits ✅ Full conversation memory — every session builds on the last ✅ Intent detection across 6 coaching categories — not one generic prompt ✅ User profiling — advice is always tailored to their stage, challenge, and goal ✅ Proactive weekly outreach — not just reactive coaching ✅ Complete audit trail — every conversation logged to Google Sheets ✅ Works for any number of users simultaneously via session-based identification ✅ No login or signup needed — just open the chat URL and start How It Works SW1 — Onboarding Every message hits the Chat Trigger and gets routed through the onboarding engine. The workflow reads all users from Google Sheets and matches the current session ID. If the user is new they go through 4 onboarding steps one message at a time — name, career stage with a numbered menu, biggest challenge with a numbered menu, and their monthly goal in their own words. Numbered responses are automatically mapped to their full label so 2 becomes Early Career (1-3 years) and 5 becomes Work-life balance. Every step is saved and the onboarding state is tracked so users can return to the same conversation and pick up exactly where they left off. SW2 — Coaching Engine Once onboarding is complete every subsequent message goes straight to the coaching engine. The workflow reads the user's last 5 conversations from the Conversation Log sheet for context. It then scans the message for intent keywords across 6 categories and selects the matching system prompt. GPT-4o receives the full user profile, conversation history, and topic-specific coaching instructions before generating a response. Every response includes a main coaching answer, one specific action the user can take today, and a follow-up question to continue the conversation. The full exchange is logged to the Conversation Log sheet. SW3 — Weekly Check-in Every Sunday at 10AM the workflow reads all fully onboarded users, pulls their recent conversation topics from the log, and generates a personalized weekly check-in email for each one via GPT-4o. The email includes a warm personalized greeting, acknowledgment of their progress, a concrete weekly challenge tied to their goal, and a motivational quote from a real woman leader relevant to their situation. Emails are sent via Gmail and every send is logged to the Weekly Checkins sheet. Features n8n Chat Trigger with public URL — shareable with any user Session-based user identification — no login required 4-step guided onboarding with numbered menu options Numbered response to label mapping for clean data storage New vs returning user detection on every message Google Sheets as full user database and conversation memory 6-category intent detection engine with keyword matching Topic-specific GPT-4o system prompts per coaching category Last 5 message context window passed to every GPT call Structured JSON responses — advice, action step, follow-up question Weekly Sunday proactive check-in via Gmail Personalized HTML email with challenge box and quote section Full logging across 3 sheets — User Profiles, Conversation Log, Weekly Checkins Requirements OpenAI API key (GPT-4o access) Google Sheets OAuth2 connection Gmail OAuth2 connection A configured Google Sheet with 3 sheets as above Setup Steps Create a Google Sheet called "AI Confidence Coach" with 3 sheets — User Profiles, Conversation Log, Weekly Checkins Paste your Sheet ID into all Google Sheets nodes Add your Google Sheets OAuth2 credentials Add your OpenAI API key Add your Gmail OAuth2 credentials Add your email as fallback in the Send Weekly Checkin Email node Activate the workflow and copy the Chat Trigger URL Open the chat URL and test the full onboarding flow with 5 messages Send a coaching question and confirm GPT-4o responds with personalized advice Add your email to the User Profiles sheet and run SW3 manually to test the weekly check-in email Share the chat URL with your users — the workflow runs itself from here Target Audience 🤖 Women's communities and career platforms who want to offer AI coaching at scale 💼 HR teams building internal confidence and career development tools 🎓 Edtech creators running women's upskilling and mentorship programs 🔧 Automation agencies building AI coaching products for clients

Here is the template specification based on the provided workflow and guidelines. Audit Instagram Influencer Safety and Engagement to Slack Description Protect your brand reputation and optimize your marketing budget by automatically vetting potential influencer partners. Manually analyzing engagement rates and reading through hundreds of comments to detect brand safety risks is time-consuming and prone to error. This workflow streamlines the due diligence process. By simply entering an Instagram username into a form, the system scrapes recent data, calculates engagement metrics to detect potential fake followers or bot activity, and uses AI to scan content for offensive language or competitor mentions. The final detailed audit report is delivered instantly to your Slack channel and logged in Google Sheets for record-keeping. Who is this for Influencer Marketing Managers:** To quickly vet creators before sending collaboration offers. Digital Agencies:** To perform scalable due diligence for client campaigns. Brand Managers:** To ensure potential partners align with brand safety guidelines and do not promote direct competitors. How it works Input: The workflow starts with an n8n Form where you enter the influencer’s Instagram handle and optional competitor names. Data Extraction: It triggers Apify (using the Instagram Scraper) to fetch the profile’s statistics and their most recent 30 posts. Engagement Analysis: A Code Node calculates the average engagement rate. It logic flags the account as "Suspicious" if the rate is unnaturally low (indicating fake followers) or suspiciously high (indicating bot farms). AI Safety Check: Recent post captions are aggregated and sent to OpenAI. The AI analyzes the text for risk flags (controversy, profanity), competitor mentions, and assigns a safety score. Reporting: The workflow saves the raw request and results to Google Sheets and sends a formatted summary report to a specific Slack channel. Requirements Apify Account:** You will need an API token and access to the Instagram Scraper actor. OpenAI Account:** An API key to perform the content safety analysis. Google Cloud Platform:** Credential with access to the Google Sheets API. Slack Workspace:** A configured Slack app/bot to post messages. How to set up Configure Credentials: Connect your Apify, Google Sheets, OpenAI, and Slack accounts in the respective nodes. Setup Google Sheet: Create a Google Sheet with two tabs: Audit Requests (Columns: username, timestamp) Audit Results (Columns: username, followers, engagementRate, status, safetyScore, riskFlags, recommendation) Configure Variables: Open the Workflow Configuration node (Set node) to input: Your apifyApiToken. engagementThresholdLow (default is 1%). engagementThresholdHigh (default is 10%). Update IDs: In the Store Audit Request and Store Audit Results nodes, select your created Google Sheet. In the Send Audit Report to Slack node, select the channel where you want reports to appear. How to customize the workflow Adjust Thresholds:* Change the engagementThresholdLow or engagementThresholdHigh values in the *Workflow Configuration** node to fit your specific industry benchmarks. Modify AI Criteria:* Edit the system prompt in the *AI Content Safety Audit** node to check for specific brand values, specific keywords, or tone of voice requirements. Change Output:* Replace the Slack node with an *Email* node (Gmail/Outlook) or a *Notion** node if you prefer to store reports in a project management database.

Create Airtable records from new ClickUp Doc pages This workflow automates the process of turning content from ClickUp Docs into structured data in Airtable. When a new task is created in ClickUp with a link to a ClickUp Doc in its name, this workflow triggers, fetches the entire content of that Doc, parses it into individual records, and then creates a new record for each item in a specified Airtable base and table. Who's it for This template is perfect for content creators, project managers, and operations teams who use ClickUp Docs for drafting or knowledge management and Airtable for tracking and organizing data. It helps bridge the gap between unstructured text and a structured database. How it works Trigger: The workflow starts when a new task is created in a specific ClickUp Team. Fetch & Parse URL: It gets the new task's details and extracts the ClickUp Doc URL from the task name. Get Doc Content: It uses the URL to fetch the main Doc and all its sub-pages from the ClickUp API. Process Content: A Code node parses the text from each page. It's designed to split content by * * * and separate notes by looking for the "notes:" keyword. Find Airtable Destination: The workflow finds the correct Airtable Base and Table IDs by matching the names you provide. Create Records: It loops through each parsed content piece and creates a new record in your specified Airtable table. How to set up Configure the Set Node: Open the "Configure Variables" node and set the following values: clickupTeamId: Your ClickUp Team ID. Find it in your ClickUp URL (e.g., app.clickup.com/9014329600/...). airtableBaseName: The exact name of your target Airtable Base. airtableTableName: The exact name of your target Airtable Table. airtableVerticalsTableName: The name of the table in your base that holds "Vertical" records, which are linked in the main table. Set Up Credentials: Add your ClickUp (OAuth2) and Airtable (Personal Access Token) credentials to the respective nodes. Airtable Fields: Ensure your Airtable table has fields corresponding to the ones in the Create New Record in Airtable node (e.g., Text, Status, Vertical, Notes). You can customize the mapping in this node. Activate Workflow: Save and activate the workflow. Test: Create a new task in your designated ClickUp team. In the task name, include the full URL of the ClickUp Doc you want to process. How to customize the workflow Parsing Logic:* You can change how the content is parsed by modifying the JavaScript in the Parse Content from Doc Pages Code node. For example, you could change the delimiter from * * to something else. Field Mapping:** Adjust the Create New Record in Airtable node to map data to different fields or add more fields from the source data. Trigger Events:** Modify the Trigger on New ClickUp Task node to respond to different events, such as taskUpdated or taskCommentPosted.