Add AI-generated headings & conclusions to WordPress posts with GPT-4.1
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
Add AI-Generated Headings & Conclusions to WordPress Posts with GPT-4
This n8n workflow automates the process of enriching WordPress posts by generating AI-powered headings and conclusions using OpenAI's GPT-4, and then updating the posts.
What it does
This workflow streamlines content enhancement for WordPress posts through the following steps:
- Manual Trigger: The workflow is initiated manually, allowing you to control when to process posts.
- Edit Fields (Set): This node is intentionally left empty in the provided JSON, suggesting it's a placeholder for defining input data or variables if needed before making API calls.
- HTTP Request (Placeholder): This node is configured as an HTTP Request, likely intended to fetch WordPress post content or interact with another API. However, its specific configuration (URL, method, headers, body) is not present in the provided JSON, indicating it's a placeholder or incomplete.
- OpenAI (Placeholder): This node is set up for OpenAI, likely intended to interact with the GPT-4 model to generate headings and conclusions. Similar to the HTTP Request node, its specific configuration (model, prompt, API key) is missing from the JSON, suggesting it's a placeholder.
- Code (Placeholder): This node is a Code node, typically used for custom JavaScript logic. In its current state in the JSON, it's empty, implying it's a placeholder for any custom processing, data manipulation, or integration logic required after AI generation and before updating WordPress.
- HTTP Request (Placeholder): Another HTTP Request node, likely intended to update the WordPress post with the newly generated content. Its configuration is also missing from the JSON.
- Sticky Note: A sticky note is present in the workflow, likely for documentation or comments within the n8n editor.
Prerequisites/Requirements
To fully utilize this workflow once configured, you will need:
- WordPress Account: Access to a WordPress site with API capabilities enabled.
- OpenAI API Key: An API key for OpenAI to access GPT-4 or other models for content generation.
- n8n Instance: A running n8n instance to import and execute the workflow.
Setup/Usage
- Import the workflow: Import the provided JSON into your n8n instance.
- Configure Credentials:
- Set up your OpenAI credentials within n8n.
- Configure any necessary WordPress API credentials (e.g., Basic Auth, OAuth) if the HTTP Request nodes are intended to interact directly with WordPress.
- Configure Placeholder Nodes:
- HTTP Request nodes: Update the two "HTTP Request" nodes with the correct URLs, methods (e.g., GET for fetching posts, POST/PUT for updating posts), headers (e.g., for authentication), and body content to interact with your WordPress API.
- OpenAI node: Configure the "OpenAI" node with the appropriate model (e.g.,
gpt-4), and a detailed prompt to generate headings and conclusions based on the WordPress post content. - Code node: Implement JavaScript logic in the "Code" node to extract relevant content from the WordPress post, format the prompt for OpenAI, parse the AI-generated response, and structure the data for updating the WordPress post.
- Edit Fields (Set) node: If you need to define specific input data or variables at the start of the workflow, configure this node accordingly.
- Test the workflow: Run the workflow manually using the "When clicking ‘Execute workflow’" trigger to ensure all steps are correctly executed and the WordPress posts are updated as expected.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
Automated YouTube video uploads with 12h interval scheduling in JST
This workflow automates a batch upload of multiple videos to YouTube, spacing each upload 12 hours apart in Japan Standard Time (UTC+9) and automatically adding them to a playlist. ⚙️ Workflow Logic Manual Trigger — Starts the workflow manually. List Video Files — Uses a shell command to find all .mp4 files under the specified directory (/opt/downloads/单词卡/A1-A2). Sort and Generate Items — Sorts videos by day number (dayXX) extracted from filenames and assigns a sequential order value. Calculate Publish Schedule (+12h Interval) — Computes the next rounded JST hour plus a configurable buffer (default 30 min). Staggers each video’s scheduled time by order × 12 hours. Converts JST back to UTC for YouTube’s publishAt field. Split in Batches (1 per video) — Iterates over each video item. Read Video File — Loads the corresponding video from disk. Upload to YouTube (Scheduled) — Uploads the video privately with the computed publishAtUtc. Add to Playlist — Adds the newly uploaded video to the target playlist. 🕒 Highlights Timezone-safe: Pure UTC ↔ JST conversion avoids double-offset errors. Sequential scheduling: Ensures each upload is 12 hours apart to prevent clustering. Customizable: Change SPANHOURS, BUFFERMIN, or directory paths easily. Retry-ready: Each upload and playlist step has retry logic to handle transient errors. 💡 Typical Use Cases Multi-part educational video series (e.g., A1–A2 English learning). Regular content release cadence without manual scheduling. Automated YouTube publishing pipelines for pre-produced content. --- Author: Zane Category: Automation / YouTube / Scheduler Timezone: JST (UTC+09:00)
Create personalized email outreach with AI, Telegram bot & website scraping
Demo Personalized Email This n8n workflow is built for AI and automation agencies to promote their workflows through an interactive demo that prospects can try themselves. The featured system is a deep personalized email demo. --- 🔄 How It Works Prospect Interaction A prospect starts the demo via Telegram. The Telegram bot (created with BotFather) connects directly to your n8n instance. Demo Guidance The RAG agent and instructor guide the user step-by-step through the demo. Instructions and responses are dynamically generated based on user input. Workflow Execution When the user triggers an action (e.g., testing the email demo), n8n runs the workflow. The workflow collects website data using Crawl4AI or standard HTTP requests. Email Demo The system personalizes and sends a demo email through SparkPost, showing the automation’s capability. Logging and Control Each user interaction is logged in your database using their name and id. The workflow checks limits to prevent misuse or spam. Error Handling If a low-CPU scraping method fails, the workflow automatically escalates to a higher-CPU method. ⚙️ Requirements Before setting up, make sure you have the following: n8n — Automation platform to run the workflow Docker — Required to run Crawl4AI Crawl4AI — For intelligent website crawling Telegram Account — To create your Telegram bot via BotFather SparkPost Account — To send personalized demo emails A database (e.g., PostgreSQL, MySQL, or SQLite) — To store log data such as user name and ID 🚀 Features Telegram interface using the BotFather API Instructor and RAG agent to guide prospects through the demo Flow generation limits per user ID to prevent abuse Low-cost yet powerful web scraping, escalating from low- to high-CPU flows if earlier ones fail --- 💡 Development Ideas Replace the RAG logic with your own query-answering and guidance method Remove the flow limit if you’re confident the demo can’t be misused Swap the personalized email demo with any other workflow you want to showcase --- 🧠 Technical Notes Telegram bot created with BotFather Website crawl process: Extract sub-links via /sitemap.xml, sitemap_index.xml, or standard HTTP requests Fall back to Crawl4AI if normal requests fail Fetch sub-link content via HTTPS or Crawl4AI as backup SparkPost used for sending demo emails --- ⚙️ Setup Instructions Create a Telegram Bot Use BotFather on Telegram to create your bot and get the API token. This token will be used to connect your n8n workflow to Telegram. Create a Log Data Table In your database, create a table to store user logs. The table must include at least the following columns: name — to store the user’s name or Telegram username. id — to store the user’s unique identifier. Install Crawl4AI with Docker Follow the installation guide from the official repository: 👉 https://github.com/unclecode/crawl4ai Crawl4AI will handle website crawling and content extraction in your workflow. --- 📦 Notes This setup is optimized for low cost, easy scalability, and real-time interaction with prospects. You can customize each component — Telegram bot behavior, RAG logic, scraping strategy, and email workflow — to fit your agency’s demo needs. 👉 You can try the live demo here: @emaildemobot ---