Workflow Templates

Who’s it for This template is ideal for creators, bloggers, and automation enthusiasts who want to auto-generate blog posts from AI-generated content — without lifting a finger. Whether you're running a tech blog, AI newsletter, or just want to keep your WordPress site fresh, this workflow does the heavy lifting. How it works This n8n workflow automatically publishes WordPress posts using trending content from Reddit RSS feeds (like /r/artificial and /r/MachineLearning), enhanced with AI writing and royalty-free images. RSS Feed Trigger: Fetches new Reddit posts every minute from multiple AI-related subreddits. AI Blog Writer: Uses an LLM (Groq / GPT-4o) to convert Reddit titles + content into a full blog article (title, content, category, tags, image keyword). Image Generator: Queries the Pexels API using the keyword provided by the AI to fetch a relevant blog image. Category & Tag Manager: Automatically creates or reuses categories and tags in WordPress. WordPress Publisher: Posts the article in draft or published form — complete with featured image and metadata. Everything is dynamically generated — no hardcoded text or API keys! How to set up Estimated time: 15–20 minutes You’ll need: 🧠 Groq or OpenAI API key (for AI article generation) 🖼️ Pexels API key (for fetching featured images) 📰 WordPress API credentials (with media + post permissions) Customization via Sticky Notes: Choose your own RSS feeds (or subreddit URLs) Modify the AI prompt to match your writing style Set post status (draft or publish) Add your WordPress API URL and credentials Requirements Free n8n account (or self-hosted instance) API credentials (Groq/OpenAI, Pexels, WordPress) Working WordPress site with REST API access Sticky notes explaining: Setup instructions AI prompt format Required credential names

Instantly fetch live Gate.io Spot Market data directly in Telegram! This workflow integrates the Gate.io REST v4 API with GPT-4.1-mini-powered AI and Telegram, giving traders real-time access to price action, order books, candlesticks, and trade data. Perfect for crypto traders, analysts, and DeFi builders who need fast and reliable exchange insights. ⚙️ How It Works A Telegram bot listens for user queries (e.g., "BTC_USDT"). The workflow securely processes the request, authenticates the user, and attaches a sessionId. The Gate AI Agent orchestrates data retrieval via Gate.io Spot Market API, including: ✅ Latest Price & 24h Stats (/spot/tickers) ✅ Order Book Depth (with best bid/ask snapshots) ✅ Klines (candlesticks) for OHLCV data ✅ Recent Trades (up to 100 latest trades) Data is optionally cleaned using Calculator (for spreads, midpoints, % changes) and Think (for formatting). An AI-powered formatter (GPT-4.1-mini) structures results into Telegram-friendly reports. The final Gate.io Spot insights are sent back instantly in HTML-formatted Telegram messages. 💡 What You Can Do with This Agent This AI-driven Telegram bot enables you to: ✅ Track real-time spot prices for any Gate.io pair ✅ Monitor order book depth (liquidity snapshots) ✅ View recent trades for activity insights ✅ Analyze candlesticks across multiple intervals ✅ Compare bid/ask spreads with calculated metrics ✅ Get clean, structured data without raw JSON clutter 🛠️ Setup Steps Create a Telegram Bot Use @BotFather on Telegram to create a bot and obtain an API token. Configure Telegram API Credentials in n8n Add your bot token under Telegram API credentials. Replace the placeholder Telegram ID in the Authentication node with your own. Import & Deploy Workflow Load Gate AI Agent v1.02.json into n8n. Configure your OpenAI API key for . Configure your Gate api key. Save and activate the workflow. Run & Test Send a query (e.g., "BTC_USDT") to your Telegram bot. Receive instant Gate.io market insights formatted for easy reading. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock real-time Gate.io Spot Market insights directly in Telegram — fast, clean, and reliable. 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

This AI Blog Generator is an advanced n8n-powered automation workflow that leverages Google Gemini and Google Sheets to generate SEO-friendly blog articles for Shopify products. It automates the entire process — from fetching product data to creating structured HTML content — with zero manual effort. 💡 Key Advantages Our AI Blog Generator offers five core advantages that make it the perfect solution for automated content creation: 🔗 Shopify Product Sync** — Automatically pulls product data (titles, descriptions, images, etc.) via Shopify API. ✍️ SEO Blog Generation** — Gemini generates blog titles, meta descriptions, and complete articles using product information. 🗂️ Structured Content Output** — Creates well-formatted HTML with headers and bullet points for seamless Shopify blog integration. 📄 Google Sheets Integration** — Tracks blog creation and prevents duplicate publishing using a centralized Google Sheet. 📤 Shopify Blog API Integration** — Publishes the generated blog to Shopify with a single API call. ⚙️ How It Works The workflow follows a systematic 8-step process that ensures quality and efficiency: Step-by-Step Process Manual Trigger – Start the workflow via a test trigger or scheduler. Fetch Products from Shopify – Retrieves all product details, including images and descriptions. Fix Input Format – Organizes and updates the input table using Code and Google Sheet nodes. Filter Duplicates – Ensures no previously used rows are processed again. Limit Control – Processes one row at a time and loops until all blogs are posted. Gemini AI Generation – Creates SEO-friendly blog content in HTML format from product data. HTML Structure Fix – Adjusts content for JSON compatibility by cleaning unsupported HTML tags. Article API Posting – Sends finalized blog content to Shopify for publishing or drafting. 🛠️ Setup Steps Required Node Configuration To implement this workflow, you'll need to configure the following n8n nodes: Trigger Node:** Start the workflow instantly. Shopify Node:** Fetch product details. Google Sheet Node:** Store input/output data and track blog creation status. Code Node:** Format data as required. Filter Node:** Remove used rows to avoid duplication. Limit Node:** Process one blog at a time. Agent Node:** Sends prompt to Gemini and returns parsed SEO-ready content. HTTP Node:** Posts content to Shopify via the API. 🔐 Credentials Required Authentication Setup Before running the workflow, ensure you have the following credentials configured: Shopify Access Token** – For fetching products and posting blogs Gemini API Key** – For AI-powered blog generation Google Sheets OAuth** – For logging and tracking workflow data 👤 Ideal For Target Users This automation workflow is specifically designed for: Ecommerce teams** automating blogs for hundreds of products Shopify store owners** boosting organic traffic effortlessly Marketing teams** building scalable, AI-driven content workflows 💬 Bonus Tip Extensibility Features The workflow is fully modular and highly customizable. You can easily extend it for: Internal linking** between related products Multi-language translation** for global markets Social media sharing** automation Email marketing** integration All extensions can be implemented within the same n8n flow, making it a comprehensive content automation solution.

Description Transform Figma design files into detailed QA test cases with AI-driven analysis and structured export to Google Sheets. This workflow helps QA and product teams streamline design validation, test coverage, and documentation — all without manual effort. 🎨🤖📋 What This Template Does Step 1: Trigger manually and input your Figma file ID. 🎯 Step 2: Fetches the full Figma design data (layers, frames, components) via API. 🧩 Step 3: Sends structured design JSON to GPT-4o-mini for intelligent test case generation. 🧠 Step 4: AI analyzes UI components, user flows, and accessibility aspects to generate 5–10 test cases. ✅ Step 5: Parses and formats results into a clean structure. Step 6: Exports test cases directly to Google Sheets for QA tracking and reporting. 📊 Key Benefits ✅ Saves 2–3 hours per design by automating test case creation ✅ Ensures consistent, comprehensive QA documentation ✅ Uses AI to detect UX, accessibility, and functional coverage gaps ✅ Centralizes output in Google Sheets for easy collaboration Features Figma API integration for design parsing GPT-4o-mini model for structured test generation Automated Google Sheets export Dynamic file ID and output schema mapping Built-in error handling for large design files Requirements Figma Personal Access Token OpenAI API key (GPT-4o-mini) Google Sheets OAuth2 credentials Target Audience QA and Test Automation Engineers Product & Design Teams Startups and Agencies validating Figma prototypes Setup Instructions Connect your Figma token as HTTP Header Auth (X-Figma-Token). Add your OpenAI API key in n8n credentials (model: gpt-4o-mini). Configure Google Sheets OAuth2 and select your sheet. Input Figma file ID from the design URL. Run once manually, verify output, then enable for regular use.

Instantly access Upbit Spot Market Data in Telegram with AI Automation This workflow integrates the Upbit REST API with GPT-4o-mini and Telegram, giving you real-time price data, order books, trades, and candles directly in chat. Perfect for crypto traders, market analysts, and investors who want structured Upbit data at their fingertips—no manual API calls required. ⚙️ How It Works A Telegram bot listens for user queries like upbit KRW-BTC 15m. The Upbit AI Agent parses the request and fetches live data from the official Upbit REST API: Price & 24h stats (/v1/ticker) Order book depth & best bid/ask (/v1/orderbook) Recent trades (/v1/trades/ticks) Dynamic OHLCV candles across all timeframes (/v1/candles/{seconds|minutes|days|weeks|months|years}) A built-in Calculator tool computes spreads, % change, and midpoints. A Think module reshapes raw JSON into simplified, clean fields. The agent formats results into concise, structured text and sends them back via Telegram. 📊 What You Can Do with This Agent ✅ Get real-time prices and 24h change for any Upbit trading pair. ✅ View order book depth and best bid/ask snapshots. ✅ Fetch multi-timeframe OHLCV candles (from 1s to 1y). ✅ Track recent trades with price, volume, side, and timestamp. ✅ Calculate midpoints, spreads, and percentage changes. ✅ Receive clean, human-readable reports in Telegram—no JSON parsing needed. 🛠 Set Up Steps Create a Telegram Bot Use @BotFather and save your bot token. Configure Telegram API and OpenAI in n8n Add your bot token under Telegram credentials. Replace your Telegram ID in the authentication node to restrict access. Import the Workflow Load Upbit AI Agent v1.02.json into n8n. Ensure connections to tools (Ticker, Orderbook, Trades, Klines). Deploy and Test Example query: upbit KRW-BTC 15m → returns price, order book, candles, and trades. Example query: upbit USDT-ETH trades 50 → returns 50 latest trades. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock clean, structured Upbit Spot Market data instantly—directly in Telegram! 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

How it works: This template turns rows in a Google Sheet into polished newsletter drafts in Notion using an AI writing agent. You click Execute workflow in n8n. It fetches all rows marked N8n Status = Pending, generates a draft from Newsletter Title and About the Newsletter, creates a Notion page, writes the full draft, then flips the sheet row to Done before moving to the next one. Before you start (use your own credentials): Create and select your credentials in n8n: Google Sheets (OAuth2 or Service Account) with access to the target spreadsheet. Notion (Internal Integration) with access to the target database. OpenAI (API Key) for the Chat Model. Replace any placeholders in nodes: Spreadsheet ID/URL and sheet/tab name (e.g., newsletter). Notion Database ID / Parent and any page or block IDs used by HTTP Request nodes. OpenAI model name if you prefer a different model. Give the Notion integration access to the database (Share → Invite the integration). Do not hard-code secrets in nodes. Store them in n8n Credentials. Step-by-step: Manual Trigger Start the run with When clicking ‘Execute workflow’. Fetch pending input (Google Sheets → Get row(s) in sheet) Read the newsletter tab and pull only rows where N8n Status = Pending. Iterate (Split In Batches → Loop Over Items) Process one sheet row at a time for stable memory use and pacing. Generate the newsletter (AI Agent + OpenAI Chat Model) AI Agent loads the “System Role Instructions” that define style, sections, and format. Pass Newsletter Title and About the Newsletter to the OpenAI Chat Model to produce the draft. Create a Notion page (Notion → Create Page) Create a page in your Newsletter Automation database with the page title set from Newsletter Title. Prepare long content for Notion (Code) Split the AI output into \~1,800-character chunks and wrap as Notion paragraph blocks to avoid payload limits. Write content blocks to Notion (HTTP Request → UpdateNotionBlock) Send a PATCH request to append all generated blocks so the full draft appears on the page. Mark the sheet row as done (Google Sheets → Update row in sheet) Update N8n Status = Done for the processed Newsletter Title. Continue the loop Return to Split In Batches for the next pending row until none remain. Tools integration: Google Sheets** — input queue and status tracking (Pending → Done) OpenAI** — LLM that writes the draft from provided fields Notion** — destination database for each draft page n8n Code + HTTP Request** — chunking and Notion API block updates Want auto-runs? Add a Cron trigger before step 2 and keep the flow unchanged.

Instantly access live Bybit Spot Market data in Telegram! This workflow integrates the Bybit REST v5 API with Telegram and optional GPT-4.1-mini formatting, delivering real-time crypto market insights such as latest prices, order books, trades, and candlesticks — all presented in clean, structured Telegram messages. 🔎 How It Works A Telegram Trigger node listens for incoming user requests. User Authentication checks the Telegram ID against an allowlist. A Session ID is created from chat.id for lightweight memory across interactions. The Bybit AI Agent orchestrates multiple API requests via HTTP nodes: Latest Price & 24h Stats (/v5/market/tickers?category=spot&symbol=BTCUSDT) Order Book Depth (/v5/market/orderbook?category=spot&symbol=BTCUSDT&limit=50) Best Bid/Ask Snapshot (from order book top levels) Candlestick Data (Klines) (/v5/market/kline?category=spot&symbol=BTCUSDT&interval=15&limit=200) Recent Trades (/v5/market/recent-trade?category=spot&symbol=BTCUSDT&limit=100) Utility Nodes process and format the response: Calculator → computes spreads, mid-prices, % changes. Think → transforms JSON into human-readable reports. Simple Memory → stores symbol, sessionId, and previous inputs. Message Splitter ensures responses over 4000 characters are broken into chunks. Final results are sent back to Telegram in structured, readable format. ✅ What You Can Do with This Agent Get real-time Bybit prices & 24h statistics. Retrieve spot order book depth and liquidity snapshots. Analyze candlesticks (OHLCV) across multiple timeframes. View recent trades for market activity. Monitor bid/ask spreads & mid-prices with calculated values. Receive Telegram-ready reports, cleanly formatted and auto-split when long. 🛠️ Setup Steps Create a Telegram Bot Use @BotFather to create a bot and get a token. Configure in n8n Import Bybit AI Agent v1.02.json. Update the User Authentication node with your Telegram ID. Add your Telegram API credentials (bot token). Add OpenAI API key (Optional) Add Bybit API key if you want AI-enhanced formatting. Deploy and Test Activate the workflow in n8n. Send a message like BTCUSDT to your bot. Instantly receive Bybit Spot data inside Telegram. 📺 Setup Video Tutorial Watch the full setup guide on YouTube: ⚡ Unlock Bybit Spot Market insights in Telegram — fast, structured, and API-key free. 🧾 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

VEXA: AI-Powered Meeting Intelligence I'll be honest, I built this because I was getting lazy in meetings and missing key details. I started with a simple VEXA integration for transcripts, then added AI to pull out summaries and tasks. But that just solved part of the problem. The real breakthrough came when we integrated Mem0, creating a persistent memory of every conversation. Now, you can stop taking notes and actually focus on the person you're talking to, knowing a system is tracking everything that matters. This is the playbook for how we built it. How It Works This isn't just one workflow; it's a two-part system designed to manage the entire meeting lifecycle from start to finish. Bot Management: It starts when you flick a switch in your CRM (Baserow). A command deploys or removes an AI bot from Google Meet. No fluff—it's there when you need it, gone when you don't. The workflow uses a quick "digital sticky note" in Redis to remember who the meeting is with and instantly updates the status in your Baserow table. AI Analysis & Memory: Once the meeting ends, VEXA sends the transcript over. Using the client ID (thank god for redis) , we feed the conversation to an AI model (OpenAI). It doesn't just summarize; it extracts actionable next steps and potential risks. All this structured data is then logged into a memory layer (Mem0), creating a permanent, searchable record of every client conversation. Setup Steps: Your Action Plan This is designed for rapid deployment. Here's what you do: Register Webhook: Run the manual trigger in the workflow once. This sends your n8n webhook URL to VEXA, telling it where to dump transcripts after a call. Connect Your CRM: Copy the vexa-start webhook URL from n8n. Paste it into your Baserow automation so it triggers when you set the "Send Bot" field to Start_Bot. Integrate Your Tools: Plug your VEXA, Mem0, Redis, and OpenAI API credentials into n8n. Use the Baserow Template: I've created a free Baserow template to act as your control panel. Grab it here: https://baserow.io/public/grid/t5kYjovKEHjNix2-6Rijk99y4SDeyQY4rmQISciC14w. It has all the fields you need to command the bot. Requirements An active n8n instance or cloud account. Accounts for VEXA.ai, Mem0.ai, Baserow, and OpenAI. A Redis database . Your Baserow table must have these fields: Meeting Link, Bot Name, Send Bot, and Status. Next Steps: Getting More ROI This workflow is the foundation. The real value comes from what you build on top of it. Automate Follow-ups:** Use the AI-identified next steps to automatically trigger follow-up emails or create tasks in your project management tool. Create a Unified Client Memory:** Connect your email and other communication platforms. Use Mem0 to parse and store every engagement, building a complete, holistic view of every client relationship. Build a Headless CRM:** Combine these workflows to build a fully AI-powered system that handles everything from lead capture to client management without any manual data entry. Copy the workflow and stop taking notes

Who’s it for This template is ideal for YouTube video creators who spend a lot of time manually generating SEO assets like descriptions, tags, titles, keywords, and thumbnails. If you're looking to automate your YouTube SEO workflow, this is the perfect solution for you. How it works / What it does Connect a Google Sheet to n8n and pull in the Hindi script (or any language). Use OpenAI to generate SEO content: Video description Tags Keywords Titles Thumbnail titles etc. Use the generated description as input to create a thumbnail image using an image generation API. Store all outputs in the same Google Sheet in separate columns. Optionally, use tools like VidIQ or TubeBuddy to test the SEO strength of generated titles, tags, and keywords. 💡 Note: This example uses Runway’s image generation API, but you can plug in any other image-generation service of your choice. Requirements A Google Sheet with clearly named columns Hindi, English, or other language scripts in the sheet OpenAI API key Runway API key (or any other image generation API) How to set up You can set up this workflow in 15 minutes by following the pre-defined steps. Replace the manual Google Sheet trigger with a scheduled trigger for daily or timed automation. You may also swap Google Sheets with any database or data source of your choice. No Google Sheets API required. Requires minimal JavaScript or Python knowledge for advanced customizations.

This n8n template demonstrates how to build an intelligent entity research system that automatically discovers, researches, and creates comprehensive profiles for business entities, concepts, and terms. Use cases are many: Try automating glossary creation for technical documentation, building standardized definition databases for compliance teams, researching industry terminology for content creation, or developing training materials with consistent entity explanations! Good to know Each entity research typically costs $0.08-$0.34, depending on the complexity and sources required. The workflow includes smart duplicate detection to minimize unnecessary API calls. The workflow requires multiple AI services and a vector database, so setup time may be longer than simpler templates. Entity definitions are stored locally in your Qdrant database and can be reused across multiple projects. How it works The workflow checks your existing knowledge base first to avoid duplicate research on entities you've already processed. If the entity is new, an AI research agent intelligently combines your vector database, Wikipedia, and live web research to gather comprehensive information. The system creates structured entity profiles with definitions, categories, examples, common misconceptions, and related entities - perfect for business documentation. AI-powered validation ensures all entity profiles are complete, accurate, and suitable for business use before storage. Each researched entity gets stored in your Qdrant vector database, creating a growing knowledge base that improves research efficiency over time. The workflow includes multiple stages of duplicate prevention to avoid unnecessary processing and API costs. How to use The manual trigger node is used as an example, but feel free to replace this with other triggers such as form submissions, content management systems, or automated content pipelines. You can research multiple related entities in sequence, and the system will automatically identify connections and relationships between them. Provide topic and audience context to get tailored explanations suitable for your specific business needs. Requirements OpenAI API account for o4-mini (entity research and validation) Qdrant vector database instance (local or cloud) Ollama with nomic-embed-text model for embeddings Automate Web Research with GPT-4, Claude & Apify for Content Analysis and Insights workflow (for live web research capabilities) Anthropic API account for Claude Sonnet 4 (used by the web research workflow) Apify account for web scraping (used by the web research workflow) Customizing this workflow Entity research automation can be adapted for many specialized domains. Try focusing on specific industries like legal terminology (targeting official legal sources), medical concepts (emphasizing clinical accuracy), or financial terms (prioritizing regulatory definitions). You can also customize the validation criteria to match your organization's specific quality standards.

How It Works This template is an n8n workflow that integrates with Jira to provide automated replies. When a ticket is assigned to a user, the workflow analyzes the ticket content, retrieves relevant knowledge from a vector database, and generates a response. By continuously enriching the knowledge base, the system improves response quality in Jira. Prerequisites A Jira account with API access A Pinecone account and credentials (API key and environment settings) An AI provider credential (e.g., OpenAI API key) Setup Instructions Jira Credentials Create Jira credentials in n8n (API token and email). In the Jira node, select the registered Jira account ID. Vector Database Setup (Pinecone) Register your Pinecone credentials (API key and environment variables) in n8n. Ensure that your knowledge base is indexed in Pinecone. AI Assistant Node Configure the OpenAI (or other LLM) node with your API key. Provide a system prompt that explains how to respond to Jira tickets using retrieved knowledge. Workflow Execution The workflow runs only via the Scheduled Trigger node at defined intervals. When Jira tickets are assigned, their summary, description, and latest comments are retrieved. These details are passed to the AI assistant, which queries Pinecone and generates a response. The generated response is then posted as a Jira comment. Step by Step Scheduled Trigger The workflow is executed at regular intervals using the Scheduled Trigger node. Jira Trigger (Issue Assigned) Retrieves the summary, description, and latest comments of assigned tickets. AI Assistant Sends ticket details to the AI assistant, which searches and summarizes relevant knowledge from Pinecone. Response Generation / Ticket Update The AI generates a response and automatically posts it as a Jira comment. (Optionally, the workflow can update the ticket status or mention the assignee.) Notes Keep your Pinecone knowledge base updated to improve accuracy. You can customize the AI assistant’s behavior by adjusting the system prompt. Configure the Scheduled Trigger frequency carefully to avoid API rate limits. Further Reference For a detailed walkthrough (in Japanese), see this article: 👉 Automating Jira responses with n8n, AI, and Pinecone (Qiita) You can find the template file on GitHub here: 👉 Template File on GitHub

This n8n workflow automates the creation of high-quality, SEO-optimized blog posts using AI. It pulls keyword data from Google Sheets, conducts research via Perplexity AI, generates structured content (title, introduction, key takeaways, body, conclusion, and FAQs) with OpenAI and Anthropic models, assembles the post, performs final edits, converts to HTML, and publishes directly to WordPress. Ideal for content marketers, bloggers, or agencies looking to scale content production while maintaining relevance and engagement. Key Features Keyword-Driven Generation: Fetches primary keywords, search intent, and related terms from a Google Sheets spreadsheet to inform content strategy. AI Research & Structuring: Uses Perplexity for in-depth topic research and OpenAI/Anthropic for semantic analysis, outlines, and full content drafting. Modular Content Creation: Generates sections like introductions, key takeaways, outlines, body, conclusions, and FAQs with tailored prompts for tone, style, and SEO. Assembly & Editing: Combines sections into a cohesive Markdown post, adds internal/external links, and applies final refinements for readability and flow. Publishing Automation: Converts Markdown to styled HTML and posts drafts to WordPress. Customization Points: Easily adjust AI prompts, research depth, or output formats via Code and Set nodes. Requirements Credentials: OpenAI API (for GPT models), Perplexity API (for research), Google Sheets OAuth2 (for keyword input), WordPress API (for publishing). Setup: Configure your Google Sheets with columns like "keyword", "search intent", "related keyword", etc. Ensure the sheet is shared with your Google account. Dependencies: No additional packages needed; relies on n8n's built-in nodes for AI, HTTP, and data processing. How It Works Trigger & Input: Start manually or schedule; pulls keyword data from Google Sheets. Research Phase: Uses Perplexity to gather topic insights and citations from reputable sources. Content Generation: AI nodes create title, structure, intro, takeaways, outline, body, conclusion, and FAQs based on research and SEO guidelines. Assembly & Refinement: Merges sections, embeds links, edits for polish, and converts to HTML. Output: Publishes as a WordPress draft or outputs the final HTML for manual use. Benefits Time Savings: Automate 80-90% of content creation, reducing manual writing from hours to minutes. SEO Optimization: Incorporates primary/related keywords naturally, aligns with search intent, and includes semantic structures for better rankings. Scalability: Process multiple keywords in batches; perfect for content calendars or high-volume blogging. Quality Assurance: Built-in editing ensures engaging, error-free content with real-world examples and data-backed insights. Versatility: Adaptable for any niche (e.g., marketing, tech, finance) by tweaking prompts or sheets. Potential Customizations Add more AI models (e.g., via custom nodes) for varied tones. Integrate image generation or social sharing for full content pipelines. Filter sheets for specific topics or add notifications on completion.