Workflow Templates

This n8n template from Intuz provides a complete and automated solution for powerful cold outreach campaigns. It connects a Google Sheet of prospect data with Google Gemini to automatically generate highly personalized emails. By analyzing specific keywords and data points like company name, industry, or job title from your sheet, this automated workflow crafts unique, relevant messages that feel one-to-one, creating a complete system to dramatically improve your engagement and response rates. How it Works Manually writing personalized emails for a long list of leads is a significant bottleneck. This workflow eliminates that friction by creating an automated system that reads your lead list, understands the context, and writes compelling drafts for you. Scheduled Lead Processing:** On a schedule you define (e.g., daily), the workflow automatically activates to process your lead list. Fetches Your Lead List:** It connects to your designated Google Sheet and reads all the lead data you've prepared, such as names, companies, roles, and any custom notes or pain points. Intelligent Filtering:** The workflow is smart enough to know which leads have already been processed. Using an "If" node, it filters out any rows that already contain a generated email, ensuring it only works on new, untouched leads. AI-Driven Personalization (Google Gemini):** This is the core of the engine. For each new lead, it sends the relevant data to the Google Gemini Chat Model. The AI follows a custom prompt you define to draft a completely unique email, including a compelling subject line and a personalized body. Structured Data Output:** The workflow uses a Structured Output Parser to ensure the AI's response is always in a clean, predictable JSON format (e.g., {"subject": "...", "body": "..."}), making the data easy to handle in the next steps. Seamlessly Updates Your Spreadsheet:** Finally, the generated subject line and email body are written back into the correct row for that lead in your Google Sheet, ready for your team to copy, paste, and send. How to Use: Quick Start Guide 1. Import Workflow Template: Download the template’s JSON file and import it into your n8n instance via “File” > “Import from JSON.” 2. Configure Credentials: Google Gemini: Create and apply your API key credentials to the “Google Gemini Chat Model” node. Google Sheets: Set up and apply OAuth credentials for the Google account that owns your lead spreadsheet. Apply this credential to both the "Read Leads from Sheet" and "Update Sheet with Email" nodes. 3. Customize Nodes & Spreadsheet: Prepare Your Google Sheet:** Ensure your sheet has columns for lead data (e.g., FirstName, Company, Role) and empty columns to receive the output (e.g., GeneratedSubject, GeneratedEmail). Read Leads from Sheet:** Double-click this node and select your spreadsheet and sheet name from the list. If Node:** Update the condition to check your specific output column. For example, if your output column is named GeneratedEmail, the condition should check if {{$json.GeneratedEmail }} is empty. Basic LLM Chain Node:** This is the most important step. Edit the Template prompt to match your product, service, and desired tone. In the Template Variables section, make sure the values (e.g., {{ $('Read Leads from Sheet').item.json.FirstName }}) match the exact column names from your Google Sheet. Update Sheet with Email Node:** Select your spreadsheet and sheet name. Set the Lookup Column to a unique identifier for each lead (like their Email address). Then, map the output from the Prepare Data for Sheet node to the correct destination columns in your sheet. 4. Test & Activate: Test Run:** Click “Execute Workflow” to perform a test run. Check your Google Sheet to see if the first unprocessed lead was updated correctly with a new subject and body. Activate:** Once satisfied, toggle the workflow “Active” switch to enable it to run on your defined schedule. Requirements To use this workflow template, you will need: 1. n8n Instance: A running n8n instance (cloud or self-hosted). 2. Google Gemini Account: For generating the email content (requires a Google Gemini API Key from Google AI Studio). 3. Google Sheets Account: With a prepared spreadsheet containing your lead list and columns for the generated output. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

This workflow enriches your WordPress articles by automatically adding an AI-generated heading and a short concluding paragraph. It ensures each post ends with valuable, engaging content to improve user satisfaction, branding, and SEO. How It Works Fetches published articles from your WordPress site via the REST API. Cleans and formats the article text for processing. Sends the content to OpenAI with a structured prompt. AI generates a new heading + 3-line conclusion tailored to the article. Appends the generated text to the original content. Updates the article back in WordPress automatically. Requirements n8n version: 1.49.0 or later (recommended). Active OpenAI API key. WordPress REST API enabled. WordPress API credentials (username + application password). Setup Instructions Import this workflow into n8n. Go to Credentials and configure: OpenAI API (API key). WordPress API (username + application password). Replace https://example.com with your site’s URL. Run manually or schedule it to enhance content automatically. Categories AI & Machine Learning WordPress Content Marketing SEO Tags ai, openai, wordpress, seo, content enhancement, automation, n8n

This workflow automates the discovery and structuring of FAQs from real AI search behavior using SE Ranking and OpenAI. It fetches domain-specific AI search prompts and answers, then extracts relevant questions, responses, and source links. Each question is enriched with AI-based intent classification and confidence scoring, and the final output is aggregated into a structured JSON format ready for SEO analysis, content planning, documentation, or knowledge base generation. Who this is for This workflow is designed for: SEO professionals and content strategists building FAQ-driven content Growth and digital marketing teams optimizing for AI Search and SERP intent Content writers and editors looking for data-backed FAQ ideas SEO automation engineers using n8n for research workflows Agencies producing scalable FAQ and topical authority content What problem this workflow is solving Modern SEO increasingly depends on AI search prompts, user intent, and FAQ coverage, but manually: Discovering real AI search questions Grouping questions by intent Identifying content gaps Structuring FAQs for SEO is slow, repetitive, and inconsistent. This workflow solves that by automatically extracting, classifying, and structuring AI-driven FAQ intelligence directly from SE Ranking’s AI Search data. What this workflow does This workflow automates end-to-end FAQ intelligence generation: Fetches real AI search prompts for a target domain using SE Ranking Extracts: Questions Answers Reference links Applies zero-shot AI classification using OpenAI GPT-4.1-mini Assigns: Intent category (HOW_TO, DEFINITION, PRICING, etc.) Confidence score Aggregates all data into a structured FAQ dataset Exports the final result as structured JSON for SEO, publishing, or automation Setup If you are new to SE Ranking, please signup on seranking.com Prerequisites n8n (Self-Hosted or Cloud)** SE Ranking API access** OpenAI API key (GPT-4.1-mini)** Configuration Steps Configure Credentials SE Ranking using HTTP Header Authentication. Please make sure to set the header authentication as below. The value should contain a Token followed by a space with the SE Ranking API Key. Add OpenAI API credentials Update Input Parameters In the Set the Input Fields node: Target domain Search engine type (AI mode) Region/source Include / exclude keyword filters Result limits and sorting Verify Output Destination Confirm the file path in the Write File to Disk node Or replace it with DB, CMS, or webhook output Execute Workflow Click Execute Workflow Structured FAQ intelligence is generated automatically How to customize this workflow You can easily adapt this workflow to your needs: Change Intent Taxonomy** Update categories in the AI zero-shot classifier schema Refine SEO Focus** Modify keyword include/exclude rules for niche targeting Adjust Confidence Thresholds** Filter low-confidence questions before export Swap Output Destination** Replace file export with: CMS publishing Notion Google Sheets Vector DB for RAG Automate Execution** Add a Cron node for weekly or monthly FAQ updates Summary This n8n workflow transforms AI search prompts into structured, intent-classified FAQ intelligence using SE Ranking and OpenAI GPT-4.1-mini. It enables teams to build high-impact SEO FAQs, content hubs, and AI-ready knowledge bases automatically, consistently, and at scale.

Who is this for? This workflow is built for B2B marketers, consultants, founders, and agency owners who need to produce high-quality, research-backed thought leadership content — without spending hours on research and writing. What this workflow does This agent-powered workflow takes a simple topic input and transforms it into a comprehensive, professionally formatted lead magnet article saved directly to Google Docs. It runs parallel deep research across 5 strategic angles, compiles the findings, and produces a polished long-form article ready for LinkedIn, your blog, or a downloadable PDF. How it works Topic Input — You submit a topic via the built-in chat trigger. Strategic Query Generation — An AI agent refines your topic into 5 targeted research queries covering market context, pain points, frameworks, case studies, and future trends. Parallel Deep Research — Each query is researched independently by an AI agent, producing 400–600 words of data-rich content per section. Compilation & Structuring — All research is merged into a structured article with a table of contents, statistics, and sources. Final Writing & Editing — A writing agent produces the complete 2,500–4,000 word article with proper formatting. Google Docs Output — The article is created as a formatted Google Doc with bold text, headings, and a shareable link. Tracking — Each generated article is logged to a Google Sheet for tracking. Setup steps Connect your Ollama instance — Set up your Ollama API credentials (or swap the LLM node for OpenAI, Anthropic, etc.). Connect Google Docs OAuth2 — Create OAuth2 credentials for the Google Docs API. Connect Google Drive OAuth2 — Create OAuth2 credentials for the Google Drive API (used to make the doc shareable). Connect Google Sheets OAuth2 — Create OAuth2 credentials and update the Sheet URL in the "Log to Tracking Sheet" node to point to your own spreadsheet. Update author name — In the "Validate Queries" Code node, change YOUR_AUTHOR_NAME to your name. Activate and test — Open the chat trigger URL and submit a topic. Requirements n8n instance (self-hosted or cloud) Ollama running locally (or substitute with any supported LLM provider) Google Cloud project with Docs, Drive, and Sheets APIs enabled OAuth2 credentials for Google services How to customize Swap the LLM** — Replace the Ollama Chat Model node with OpenAI, Anthropic, Google Gemini, or any LangChain-compatible model. Change the output format** — Modify the "Final Editor and Polish" system prompt to produce blog posts, whitepapers, or email sequences instead. Adjust research depth** — Edit the number of strategic queries or word count targets in the agent prompts. Add distribution** — Extend the workflow to post directly to LinkedIn, send via email, or upload to your CMS.

Turn WhatsApp into an interactive personal classroom. This workflow automates the entire learning cycle—from generating AI-powered quizzes to tracking student progress in real-time—by combining WATI, OpenAI AI Agents, and Google Sheets. 🎯 What This Workflow Does Provides a complete end-to-end educational experience through simple WhatsApp commands: 📝 Interactive Quiz Trigger Student sends a topic (e.g., quiz photosynthesis) via WATI Trigger to start a session. 🚦 Intelligent Command Routing A Route Message switch node detects specific student intents: quiz: Triggers the AI generation of new questions. answer: Routes to the evaluation engine to grade student replies. progress: Triggers the historical performance report branch. 👁️ AI-Powered Content Creation An AI Agent using GPT-4o generates 3 tailored MCQ questions based on the requested topic, formatted as structured JSON. 📊 Automated Grading & Logging Evaluation: Compares student replies (e.g., answer 1a 2b 3c) against stored correct answers fetched from Google Sheets. Logging: Saves the final score, topic, and date to the master database. 📈 Progress Visualization Fetches all historical scores to calculate average performance, identifies the "Best Topic," and generates a visual progress bar. ✨ Key Features Dynamic AI Tutoring:** Quizzes are never repetitive; the AI generates fresh questions every time a topic is requested. Session Management:** Uses a "Session Key" (Phone + Date) to ensure students can only take one specific quiz per day per topic. Visual Performance Feedback:** Students receive formatted reports with emojis and visual bars (███░░) to track their improvement. Easy Answer Format:** Simple shorthand for students (e.g., 1a 2b) makes it accessible for mobile-first learning. Centralized Database:** All academic data is logged in Google Sheets, making it easy for teachers or parents to monitor results. 💼 Perfect For Students:** Quick self-testing on subjects before exams or competitive tests. Teachers:** Providing an automated "homework bot" for students to practice curriculum topics. Corporate Trainers:** Deploying bite-sized knowledge checks to employees via mobile. Language Learners:** Testing vocabulary or grammar rules on the go. 🔧 What You'll Need Required Integrations WATI** – To handle WhatsApp message triggers and automated feedback delivery. OpenAI API** – For the AI Agent and Chat Model (GPT-4o) to generate quizzes. Google Sheets** – To act as the database for active quiz sessions and permanent score history. Optional Customizations Difficulty Levels:** Adjust the AI Agent's system message to generate "Beginner," "Intermediate," or "Advanced" quizzes. Timed Challenges:** Use n8n Wait nodes to send "Time's Up" reminders if a student hasn't answered within an hour. 🚀 Quick Start Import Template – Copy the JSON and import it into your n8n instance. Set Credentials – Connect your WATI, OpenAI, and Google Sheets accounts. Setup Spreadsheet – Create two sheets: Active Quizzes: Headers for sessionKey, phone, topic, correctAnswers, questionCount, today. Scores: Headers for date, phone, senderName, topic, score, total, percentage. Start Learning – Send quiz solar system to your WhatsApp bot to begin! 🎨 Customization Options Question Count:** Modify the AI prompt and code nodes to generate 5 or 10 questions instead of 3. Persona Tweak:** Change the System Message in the AI Agent to make the tutor sound like a "Fun Scientist" or a "Strict Professor". Filtered Progress:** Edit the Build Progress Report code to show reports for only the last 30 days. 📈 Expected Results 100% automated quiz generation and grading—no manual teacher intervention required. Immediate student feedback providing correct answers for missed questions. Increased engagement through a familiar, low-friction WhatsApp interface. Actionable insights into which topics students struggle with most. 🏆 Use Cases Exam Preparation A high school student uses the bot to drill on "Biology" and "History" topics daily, tracking their score increase over time via the progress command. Employee Onboarding A new hire receives a "Company Policy" quiz via WhatsApp; their score is automatically logged for HR compliance. Community Education An NGO uses the bot to teach health and safety protocols in rural areas where WhatsApp is the primary digital tool. 💡 Pro Tips Strict JSON:** The AI Agent is prompted to return only JSON to ensure the workflow doesn't crash on conversational filler. Flexible Matching:** The Build Progress Report node uses String() casting to ensure phone numbers match correctly even if formatted differently in Sheets. Topic Extraction:** Use specific topics for best results; "Photosynthesis" works better than just "Biology". Ready to launch your AI classroom? Import this template and connect your OpenAI key to start generating quizzes today!

What this template does Collects the latest crypto news from multiple RSS feeds, filters and deduplicates them, uses OpenAI GPT-4 to analyze and select the top stories, translates and formats them into Russian, and posts a digest to a Telegram channel or group. The workflow runs automatically on a schedule and ensures all messages fit Telegram’s 4096-character limit. How it works (high level) RSS Sources: Reads fresh items from CoinDesk, Cointelegraph, Decrypt, Cryptobriefing, and Nulltx. Filter & Deduplicate: Keeps only unique items from the last 24 hours. AI Analysis (Crypto Analyst): An OpenAI agent identifies the most important events and selects the best article for each. AI Formatting (SMM Editor): Another OpenAI agent writes a styled digest in Russian with Telegram-compatible HTML formatting. Message Preparation: Long texts are split into safe chunks ≤ 4096 characters. Telegram Post: The digest is posted automatically to your configured Telegram channel or group. Prerequisites n8n Cloud or n8n >= 1.107.4 Credentials: OpenAI (gpt-4o-mini or gpt-4.1-mini) Telegram Bot with rights to post in your target chat Setup (5 minutes) Import this workflow into n8n. Open the Telegram node “Post to Group” and set your chatId (e.g., @your_channel or numeric ID). Connect your OpenAI and Telegram credentials. (Optional) Adjust the Scheduler interval (default: every 3 hours). Run once manually to test, then activate. Customization Add or replace RSS sources. Modify the prompts in Crypto Analyst and SMM Editor to adapt tone, style, or language. Swap out the Telegram node to publish on other platforms (Slack, Discord, etc.).

🚀 Automated LinkedIn Post Generator from Article Links (Telegram → AI → Google Sheets → LinkedIn) This workflow lets you collect article links through a Telegram bot, automatically analyze and summarize them with AI, store everything neatly in Google Sheets, and generate polished LinkedIn posts on demand whenever the user types “generate”. Perfect for creators, marketers, and founders who want to post consistently without spending hours analyzing articles or writing drafts. 🧠 How It Works 1️⃣ User Sends Articles via Telegram Your Telegram bot is the main input point. Whenever the user drops a link, the workflow: Detects the URL Fetches the content Sends it to AI for analysis This keeps the process simple. 2️⃣ AI Analyzes & Summarizes the Article The workflow uses your LLM (OpenAI, Anthropic, etc.) to: Summarize the article Extract key insights Identify main arguments Capture tone and context It produces a clean, structured dataset for each link. 3️⃣ Everything is Saved into Google Sheets Each article becomes a new row in your Google Sheet. The sheet serves as your content library with fields like: Date Title Link Summary Insights Commentary You can save dozens of articles and generate posts from any of them later. 4️⃣ User Requests a Post with “generate” When the user types “generate”, the workflow will: Pull the latest article(s) from Google Sheets (or any selection logic you choose) Build a LinkedIn-ready post using AI Apply the requested tone/style Format it as a clean, professional post The final post is sent right back to Telegram — ready to copy/paste into LinkedIn. 🛠️ Setup Steps 🔧 1. Create a Telegram Bot Go to @BotFather on Telegram Create a new bot Copy the API token Paste the token into the Telegram Trigger node in n8n 🔧 2. Add Your AI Credentials Go to Credentials → OpenAI (or your provider) Add your API key Select this credential in all AI nodes You can switch to GPT-4o, GPT-4o-mini, or any model you prefer. 🔧 3. Connect Google Sheets Go to Credentials → Google Authenticate with your Google account Make sure the sheet contains the required columns: Date Title Link Summary Insights Commentary You can customize or add additional columns as needed. 🔧 4. Adjust Workflow Logic (Optional) You can modify: How the AI summarizes The LinkedIn post style How posts are selected (latest, random, specific tone, etc.) Whether you store more metadata Multi-language support Everything is modular. 🔧 5. Test the Flow Send yourself a link via the Telegram bot Check that it appears in Google Sheets Type “generate” Receive your LinkedIn post instantly 🎉 You’re Ready! This workflow helps you build a personal content pipeline that: Collects links Saves ideas Summarizes insights Generates LinkedIn posts on demand All directly from your phone, inside Telegram. If you remix or extend this template, I’d love to see what you build!

Description Automate your financial reporting by pulling charge and refund data from Stripe, calculating key revenue and risk metrics, and delivering professional reports directly into Slack. This workflow runs on a monthly or quarterly schedule, processes Stripe data into insights, and formats a rich Slack message with revenue breakdowns, top customers, refund analysis, and payment method insights. 📊💰💬 What This Template Does Runs automatically on a monthly (1st day) or quarterly schedule (every 3 months) at 9 AM. ⏱️ Fetches Stripe charges and refunds for the reporting period. 💳 Merges charge and refund data for a unified dataset. 🔄 Calculates financial metrics: total revenue, net revenue, average transaction value, refund rate. 📈 Estimates growth metrics: Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR). 🚀 Identifies top 3 customers by revenue. 🏆 Breaks down payment methods used (e.g., Visa, Mastercard, etc.). 💳 Performs risk analysis on transactions by Stripe’s risk scores. ⚠️ Analyzes refund reasons and generates insights. 🔄 Formats all results into a clear, structured Slack message with sections for finance, growth, risk, and customers. 💬 Key Benefits Eliminates manual Stripe report exports. ⚡ Ensures timely financial reporting (monthly or quarterly). 📅 Provides instant visibility of revenue, refunds, and risks in Slack. 📲 Surfaces top customers and payment methods for strategic insights. 🏅 Helps finance and ops teams catch anomalies early (high refunds or risky transactions). 🛡️ Keeps leadership and teams aligned with automated reporting. 👩‍💻👨‍💻 Features Schedule Triggers – Automates reporting on monthly or quarterly cycles. Stripe Charges & Refunds – Pulls transaction and refund data directly from Stripe API. Merge Node – Combines charges and refunds into a single dataset. Custom Code Metrics – Calculates revenue, net revenue, refund rates, and growth metrics. Top Customer Analysis – Highlights top revenue-generating customers. Payment Breakdown – Shows revenue split by card brand/payment method. Refund Analysis – Summarizes refund reasons and rates. Risk Analysis – Categorizes payments by low, medium, or high risk scores. Slack Integration – Delivers insights in a professional report format. Requirements n8n instance (cloud or self-hosted). Stripe API credentials with read access to charges and refunds. Slack Bot token with chat:write permission. Target Audience Finance teams needing automated recurring Stripe reports. 💼 SaaS companies monitoring MRR, ARR, and refunds. 🚀 Founders/Execs who want financial dashboards in Slack. 👩‍💼 Operations teams tracking risk and refund trends. 🛠️ Remote teams relying on Slack for reporting. 🌍 Step-by-Step Setup Instructions Connect your Stripe API credentials in n8n. 🔑 Connect your Slack API credentials and select your target channel. 💬 Adjust the schedule triggers (monthly/quarterly) if needed. ⏱️ Customize the Slack message formatting if you want branding or tone changes. 🎨 Test the workflow with sample data to confirm financial metrics. ✅

This n8n template demonstrates how to automatically generate and publish SEO/AEO-optimized Shopify blog articles from a list of keywords using AI for content creation, image generation, and metadata optimization. Who’s it for Shopify marketers, content teams, and solo founders who want consistent, hands-off blog production with built-in SEO/AEO hygiene and internal linking. What it does The workflow picks a keyword from your Google Sheet based on priority, search volume, and difficulty. It then checks your Shopify blog for existing slugs to avoid duplicate, drafts a 900+ word article optimized for SEO/AEO, generates a hero image, creates the article in Shopify, sets SEO metafields (title/description), and logs the result to your Sheets for tracking and future internal links. How it works Google Sheets → Candidate selection:* Reads *Keywords, **Links, and Published tabs: ranks by priority → volume → difficulty. (In the workflow it is explained how to exactly set up the Google Sheets) De-dupe slugs:** Paginates your blog via Shopify GraphQL to collect existing handles and make sure to use a different one. OpenAI content + image:** Builds a structured prompt (SEO/AEO and internal linking), calls Chat Completions and Image Generation for a hero image. Shopify publish:** Creates the article via REST and updates title_tag / description_tag metafields via GraphQL. Log + link graph:* Appends to *Published* tab to keep track of articles posted and *Links** tab for ongoing internal-link suggestions. How to set up Open Set – Config and fill: shopDomain, siteBaseUrl, blogId, blogHandle, sheetId, author. Optional: autoPublish, maxPerRun, tz. Create the Google Sheet with Keywords, Links, Published tabs using the provided column structure. I have personally used Semrush to generate that list of keywords. Add credentials: Shopify Admin token (Header/Bearer), OpenAI API key, and Google Service Account. Requirements Shopify store with Blog API access OpenAI API key Google Service Account with access to Google Sheets API (can be activated here here) How to customize Change the cron in Schedule Trigger for different days/times. Adjust maxPerRun, autoPublish, language or any other variables in the "Set - Config" node. Adjust the prompt from the "Code - Build Prompt" node. Extend the Sheets schema with extra scoring signals if needed.

This workflow fetches deals and their notes from Pipedrive, cleans up stage IDs into names, aggregates the information, and uses OpenAI to generate a daily summary of your funnel. ⚙️ Setup Instructions 1️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 2️⃣ Connect Pipedrive In Pipedrive → Personal preferences → API → copy your API token URL shortcut: https://{your-company}.pipedrive.com/settings/personal/api In n8n → Credentials → New → Pipedrive API Company domain: {your-company} (the subdomain in your Pipedrive URL) API Token: paste the token from step 1 → Save In the Pipedrive nodes, select your Pipedrive credential and (optionally) set filters (e.g., owner, label, created time). 🧠 How It Works Trigger**: Workflow runs on manual execution (can be scheduled). Get many deals**: Pulls all deals from your Pipedrive. Code node**: Maps stage_id numbers into friendly stage names (Prospecting, Qualified, Proposal Sent, etc.). Get many notes**: Fetches notes attached to each deal. Combine Notes**: Groups notes by deal, concatenates content, and keeps deal titles. Set Field Names**: Normalizes the fields for summarization. Aggregate for Agent**: Collects data into one object. Turn Objects to Text**: Prepares text data for AI. OpenAI Chat Model + Summarize Agent: Generates a **daily natural-language summary of deals and their current stage. 💬 Example Prompts “Summarize today’s deal activity.” “Which deals are still in negotiation?” “What updates were added to closed-won deals this week?” 📬 Contact Need help extending this (e.g., send summaries by Slack/Email, or auto-create tasks in Pipedrive)? 📧 rbreen@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

Who’s it for Learners, teachers, and content creators who track German vocabulary in Google Sheets and want automatic enrichment with synonyms, example sentences, and basic lexical info—without copy-and-paste. How it works / What it does When a new row is added to your sheet (column vocabulary), the workflow looks up the word in OpenThesaurus and checks if any entries are found. If so, an LLM generates a strict JSON object containing: natural_sentence (a clear German example), part_of_speech, translation_ja (concise Japanese gloss), and level (CEFR estimate). The JSON is parsed and written back to the same row, keeping your spreadsheet the single source of truth. If no entry is found, the workflow writes a helpful “not found” note. How to set up Connect Google Sheets and select your spreadsheet/tab. Confirm a vocabulary column exists. Configure OpenThesaurus (no API key required). Add your LLM credentials and keep the prompt’s “JSON only” constraint. Rename nodes clearly and add a yellow sticky note with this description. Requirements Access to Google Sheets LLM credentials (e.g., OpenAI) A tab containing a vocabulary column How to customize the workflow Adjust the If condition (e.g., require terms.length > 1 or fall back to the headword). Tweak the LLM prompt for tone, length, or level policy. Map extra fields in the Set node; add columns for difficulty tags or usage notes. Follow security best practices (no hardcoded secrets in HTTP nodes).

Generate AI blog posts with human review using SE Ranking and Claude Who is this for Content teams scaling blog production with AI SEO agencies creating client content at scale Marketing teams with editorial calendars What this workflow does Find high-opportunity keywords, generate AI content briefs and draft articles, then send everything to a human reviewer before anything gets published. What you'll get Keyword opportunities scored by volume, difficulty, and ranking potential AI-generated content briefs with outlines and related keywords Full draft articles written by Claude based on the briefs Email-based human review with one-click approve/reject Everything tracked in Google Sheets How it works Pulls keyword opportunities for your domain from SE Ranking Scores and filters the best targets by volume and difficulty Grabs related keywords and "People Also Ask" questions AI creates a detailed content brief for each keyword AI writes a full draft article based on the brief Sends a review email with approve/reject buttons Updates Google Sheets with the decision Approved articles are split and ready for publishing Requirements Self-hosted n8n instance SE Ranking community node v1.3.5+ (Install from npm) SE Ranking API token (Get one here) Anthropic API key (for Claude) SMTP credentials for review emails Google Sheets account (optional) Setup Install the SE Ranking community node Add your SE Ranking, Anthropic, and SMTP credentials Update the Configuration node with your domain, brand, and reviewer email Connect Google Sheets for tracking (optional) Customization Change min_volume and max_difficulty to adjust keyword targeting Edit articles_per_run to generate more or fewer articles per batch Swap Claude models in the AI nodes for different quality/cost tradeoffs