Workflow Templates

This template can be used to generate research ideas from PDF scientific papers based on the content gaps found in text using the InfraNodus knowledge graph GraphRAG knowledge graph representation. Simply upload several PDF files (research papers, corporate or market reports, etc) and the template will generate a research question, which will then be sent as an AI prompt to the InfraNodus GraphRAG system that will extract the answer from the documents. As a result, you find the gap in a collection of research papers and bridge it in a few seconds . The template is useful for: advancing scientific research generating AI prompts that drive research further finding the right questions to ask to bridge blind spots in a research field avoiding the generic bias of LLM models and focusing on what's important in your particular context Using Content Gaps for Generating Research Questions Knowledge graphs represent any text as a network: the main concepts are the nodes, their co-occurrences are the connections between them. Based on this representation, we build a graph and apply network science metrics to rank the most important nodes (concepts) that serve as the crossroads of meaning and also the main topical clusters that they connect. Naturally, some of the clusters will be disconnected and will have gaps between them. These are the topics (groups of concepts) that exist in this context (the documents you uploaded) but that are not very well connected. Addressing those gaps can help you see which groups of concepts you could connect with your own ideas. This is exactly what InfraNodus does: builds the structure, finds the gaps, then uses the built-in AI to generate research questions that bridge those gaps. How it works 1) Step 1: First, you upload your PDF files using an online web form, which you can run from n8n or even make publicly available. 2) Steps 2-4: The documents are processed using the Code and PDF to Text nodes to extract plain text from them. 3) Step 5: This text is then sent to the InfraNodus GraphRAG node that creates a knowledge graph, identifies structural gaps in this graph, and then uses built-in AI to research questions, which are then used as AI prompts. 4) Step 6: The research questino is sent to the InfraNodus GraphRAG system that represents the PDF documents you submitted as a knowledge graph and then uses the research question generated to come up with an answer based on the content you uploaded. 4) Step 7: The ideas are then shown to the user in the same web form. Optionally, you can derive the answers from a different set of papers, so the question is generated from one batch, but the answer is generated from another. If you'd like to sync this workflow to PDF files in a Google Drive folder, you can copy our Google Drive PDF processing workflow for n8n. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key. Add this key into the InfraNodus GraphRAG HTTP node(s) you use in this workflow. You do not need any OpenAI keys for this to work. Optionally, you can change the settings in the Step 4 of this workflow and enforce it to always use the biggest gap it identifies. Requirements An InfraNodus account and API key Note: OpenAI key is not required. You will have direct access to the InfraNodus AI with the API key. Customizing this workflow You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas). You can also hook up automated social media content creation workflows in the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way). Check out our n8n templates for ideas at https://n8n.io/creators/infranodus/ Also check the full tutorial with a conceptual explanation at https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow Also check out the video introduction to InfraNodus to better understand how knowledge graphs and content gaps work: For support and help with this workflow, please, contact us at https://support.noduslabs.com

This n8n template demonstrates a simple approach to using AI to automate the generation of blog content which aligns to your organisation's brand voice and style by using examples of previously published articles. In a way, it's quick and dirty "training" which can get your automated content generation strategy up and running for very little effort and cost whilst you evaluate our AI content pipeline. How it works In this demonstration, the n8n.io blog is used as the source of existing published content and 5 of the latest articles are imported via the HTTP node. The HTML node is extract the article bodies which are then converted to markdown for our LLMs. We use LLM nodes to (1) understand the article structure and writing style and (2) identify the brand voice characteristics used in the posts. These are then used as guidelines in our final LLM node when generating new articles. Finally, a draft is saved to Wordpress for human editors to review or use as starting point for their own articles. How to use Update Step 1 to fetch data from your desired blog or change to fetch existing content in a different way. Update Step 5 to provide your new article instruction. For optimal output, theme topics relevant to your brand. Requirements A source of text-heavy content is required to accurately breakdown the brand voice and article style. Don't have your own? Maybe try your competitors? OpenAI for LLM - though I recommend exploring other models which may give subjectively better results. Wordpress for blog but feel free to use other preferred publishing platforms. Customising this workflow Ideally, you'd want to "train" your agent on material which is similar to your output ie. your social media post may not get the best results from your blog content due to differing formats. Typically, this brand voice extraction exercise should run once and then be cached somewhere for reuse later. This would save on generation time and overall cost of the workflow.

🖼️ Text-to-Image Generator using n8n + Flux AI This n8n workflow automates image generation from text prompts using the Text-to-Image Flux AI API. It reads prompts from Google Sheets, generates images via API, uploads them to Google Drive, and logs the outcome. 🌟 Key Features Integrates with Text-to-Image Flux AI on RapidAPI Converts base64 image data to downloadable files Stores images on Google Drive Updates logs and errors back into Google Sheets Skips prompts already processed 📄 Google Sheet Column Structure Your source Google Sheet should include the following columns: | Column Name | Description | |-------------------|--------------------------------------------------| | Prompt | The text prompt to generate an image from | | drive path | (Optional) File path or URL of saved image | | Generated Date | Date/time the image was generated | | Base64 | Base64 string or error message (for logging) | Only rows with a non-empty Prompt and empty drive path will be processed. 📌 Use Case Perfect for: Bulk AI image generation for content marketing Creative automation with prompt-based image creation Building image assets based on structured datasets Any workflow where prompts are tracked via Google Sheets Uses the Text-to-Image Flux AI API to generate high-quality images on demand. 🔧 Workflow Summary | Step | Node | Description | |------|------|-------------| | 1 | Manual Trigger | Manually start the workflow | | 2 | Google Sheets2 | Reads prompts from Google Sheets | | 3 | Loop Over Items | Processes rows one by one | | 4 | If2 | Skips rows that already have images | | 5 | HTTP Request1 | Calls Text-to-Image Flux AI via RapidAPI | | 6 | Code1 | Converts base64 image to binary file | | 7 | Google Drive1 | Uploads the image file to a Drive folder | | 8 | Google Sheets1 | Logs base64 result and timestamp back | | 9 | If1 | Handles errors from the API | | 10 | Google Sheets4 | Logs errors to the sheet | | 11 | Wait | Adds delay between batches to prevent rate-limiting | 🚀 RapidAPI: Text-to-Image Flux AI This flow is powered by Text-to-Image Flux AI. Be sure to: Sign up at RapidAPI and subscribe to the API. Copy your API Key. Replace "your key" in the HTTP Request1 node’s x-rapidapi-key header. You can test the API directly here before connecting it to n8n. ✅ Tips for Setup Ensure you’ve set up a Google Service Account with access to both Sheets and Drive. Fill only the Prompt column — leave drive path and Base64 empty for new prompts. Monitor your RapidAPI dashboard for usage and quota. Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!

Who is this for? This workflow is designed for travel bloggers, content creators, social media managers, and anyone who wants to transform their travel photos into engaging written narratives. It's perfect for travelers looking to create compelling stories from their photo collections without spending hours crafting content manually, families wanting to document memorable trips, and digital nomads who need to produce travel content efficiently. What problem is this workflow solving? Converting travel photos into engaging stories is time-consuming and requires both creative writing skills and the ability to analyze visual content meaningfully. This workflow solves the challenge of: Transforming visual memories into compelling written narratives Organizing photos chronologically to create logical story flow Generating professional-quality travel content without writing expertise Analyzing photo content to extract meaningful themes and emotions Creating day-by-day structured narratives from unorganized photo collections Reducing the time spent on manual content creation for travel documentation What this workflow does This AI-powered photo storyteller takes your travel photos and automatically generates immersive, first-person travel narratives. The workflow: Accepts multiple photos through a webhook endpoint Uses OpenAI Vision API (GPT-4o) to analyze each photo's content, emotions, and themes Automatically organizes photos chronologically by date and timestamp Groups photos by travel days and extracts daily themes Leverages GPT-4.1 (minimum required) to craft engaging, first-person travel stories with creative day titles Generates structured narratives with sensory details, cultural observations, and emotional insights Outputs JSON formatted content ready for formatting Creates day-by-day story structure with memorable moments and reflective conclusions Setup Required Credentials: OpenAI API key configured in n8n for both Vision Analysis and Story Generation nodes Ensure you have sufficient OpenAI credits for image analysis and text generation Webhook Configuration: The workflow creates a webhook endpoint at /tripteller-upload Configure your photo upload interface to POST photos array to this endpoint Photos should be sent as base64 encoded data with filename and metadata Photo Requirements: Supported formats: Standard image formats (JPEG, PNG, etc.) Photos should include timestamp metadata for chronological organization Caution Do not upload all photos at once. Start with a small number of photos, like 5 at a time. How to customize this workflow to your needs Story Style Customization: Modify the system prompt in the "Generate Travel Story" node to adjust writing tone (nostalgic, adventurous, poetic, etc.) Customize the story structure by editing the output format requirements Add specific cultural or geographical context prompts for location-specific storytelling Photo Analysis Enhancement: Adjust the Vision Analysis node prompt to focus on specific elements (architecture, food, people, landscapes) Modify the grouping logic in the "Group Photos by Day" node for different time-based organization Add location extraction from EXIF data for geographical context Output Format Adjustment: Customize the final response structure in the "Format Final Response" node Add integration with publishing platforms (blog APIs, social media, etc.) Include additional metadata like location tags, travel duration, or trip statistics Performance Optimization: Adjust the execution timeout based on your typical photo volume Modify the parallel processing approach for large photo collections Add progress tracking for longer processing workflows

Who is this for? This template is designed for internal support teams, product specialists, and knowledge managers in technology companies who want to automate ingestion of product documentation and enable AI-driven, retrieval-augmented question answering via WhatsApp. What problem is this workflow solving? Support agents often spend too much time manually searching through lengthy documentation, leading to inconsistent or delayed answers. This solution automates importing, chunking, and indexing product manuals, then uses retrieval-augmented generation (RAG) to answer user queries accurately and quickly with AI via WhatsApp messaging. What these workflows do Workflow 1: Document Ingestion & Indexing Manually triggered to import product documentation from Google Docs. Automatically splits large documents into chunks for efficient searching. Generates vector embeddings for each chunk using OpenAI embeddings. Inserts the embedded chunks and metadata into a MongoDB Atlas vector store, enabling fast semantic search. Workflow 2: AI-Powered Query & Response via WhatsApp Listens for incoming WhatsApp user messages, supporting various types: Text messages: Plain text queries from users. Audio messages: Voice notes transcribed into text for processing. Image messages: Photos or screenshots analyzed to provide contextual answers. Document messages: PDFs, spreadsheets, or other files parsed for relevant content. Converts incoming queries to vector embeddings and performs similarity search on the MongoDB vector store. Uses OpenAI’s GPT-4o-mini model with retrieval-augmented generation to produce concise, context-aware answers. Maintains conversation context across multiple turns using a memory buffer node. Routes different message types to appropriate processing nodes to maximize answer quality. **Setup Setting up vector embeddings** 1- Authenticate Google Docs and connect your Google Docs URL containing the product documentation you want to index. 2- Authenticate MongoDB Atlas and connect the collection where you want to store the vector embeddings. Create a search index on this collection to support vector similarity queries. 3- Ensure the index name matches the one configured in n8n (data_index). See the example MongoDB search index template below for reference. Setting up chat 1- Authenticate the WhatsApp node with your Meta account credentials to enable message receiving and sending. 2- Connect the MongoDB collection containing embedded product documentation to the MongoDB Vector Search node used for similarity queries. 3- Set up the system prompt in the Knowledge Base Agent node to reflect your company’s tone, answering style, and any business rules, ensuring it references the connected MongoDB collection for context retrieval. Make sure Both MongoDB nodes (in ingestion and chat workflows) are connected to the same collection with: An embedding field storing vector data, Relevant metadata fields (e.g., document ID, source), and The same vector index name configured (e.g., data_index).

This n8n template offers a free and automated way to convert images from a Google Drive folder into a single PDF document. It uses Google Slides as an intermediary, allowing you to control the final PDF's page size and orientation. If you're looking for a no-cost solution to batch convert images to PDF and need flexibility over the output dimensions (like A4, landscape, or portrait), this template is for you! It's especially handy for creating photo albums, visual reports, or simple portfolios directly from your Google Drive. How it works The workflow first copies a Google Slides template you specify. The page setup of this template (e.g., A4 Portrait) dictates your final PDF's dimensions. It then retrieves all images from a designated Google Drive folder, sorts them by creation date. Each image is added to a new slide in the copied presentation. Finally, the entire Google Slides presentation is converted into a PDF and saved back to your Google Drive. How to use Connect your Google Drive and Google Slides accounts in the relevant nodes. In the "Set Pdf File Name" node, define the name for your output PDF. In the "CopyPdfTemplate" node: Select your Google Slides template file (this sets the PDF page size/orientation). Choose the Google Drive folder containing your source images. Ensure your images are in the specified folder. For best results, images should have an aspect ratio similar to your chosen Slides template. Run the workflow to generate your PDF by clicking 'Test Workflow' Requirements Google Drive account. Google Slides account. Google Slides Template stored on your Google Drive Customising this workflow Adjust the "Filter: Only Images" node if you use image formats other than PNG (e.g., image/jpeg for JPGs). Modify the image sorting logic in the "Sort by Created Date" node if needed.

This template creates a Telegram AI Assistant that answers questions based on your documents, powered by Google Gemini and Supabase. Key features include Intelligent HTML Post-processing for rich formatting in Telegram and Adaptive Message Chunking to handle long text responses. 📹 Watch the Bot in Action ▶️ Click the image above to watch a live demo on YouTube. This video provides a live demonstration of the bot's core features and how it interacts. See a quick walkthrough of its capabilities and user flow. How it works: User uploads a PDF document to a Telegram bot. The workflow processes the PDF, creates embeddings using Google Gemini, and stores these embeddings in a Supabase vector table. Users then ask questions to the bot. The workflow performs a vector search in Supabase to find relevant document chunks based on the user's query. Google Gemini uses the retrieved relevant chunks to generate an intelligent answer. The bot sends the formatted answer back to the user on Telegram, utilizing HTML markup for enhanced presentation. Set up steps: Setup should take approximately 15-20 minutes. Import the workflow into your n8n instance. Configure credentials for Telegram, Google Gemini, and Supabase. Set up your Supabase vector table using the provided SQL script. Activate the workflow. Detailed setup instructions, including how to get API keys and configure nodes, are available in the sticky notes within the workflow itself.

One-way sync between Telegram, Notion, Google Drive, and Google Sheets Who is this for? This workflow is perfect for productivity-focused teams, remote workers, virtual assistants, and digital knowledge managers who receive documents, images, or notes through Telegram and want to automatically organize and store them in Notion, Google Drive, and Google Sheets—without any manual work. What problem is this workflow solving? Managing Telegram messages and media manually across different tools like Notion, Drive, and Sheets can be tedious. This workflow automates the classification and storage of incoming Telegram content, whether it’s a text note, an image, or a document. It saves time, reduces human error, and ensures that media is stored in the right place with metadata tracking. What this workflow does Triggers on a new Telegram message** using the Telegram Trigger node. Classifies the message type** using a Switch node: Text messages are appended to a Notion block. Images are converted to base64, uploaded to imgbb, and then added to Notion as toggle-image blocks. Documents are downloaded, uploaded to Google Drive, and the metadata is logged in Google Sheets. Sends a completion confirmation** back to the original Telegram chat. Setup Telegram Bot: Set up a bot and get the API token. Notion Integration: Share access to your target Notion page/block. Use the Notion API credentials and block ID where content should be appended. Google Drive & Sheets: Connect the relevant accounts. Select the destination folder and spreadsheet. imgbb API: Obtain a free API key from imgbb. Replace placeholder credential IDs and asset URLs as needed in the imported workflow. How to customize this workflow to your needs Change Storage Locations**: Update the Notion block ID or Google Drive folder ID. Switch Google Sheet to log in a different file or sheet. Add More Filters**: Use additional Switch rules to handle other Telegram message types (like videos or voice messages). Modify Response Message**: Personalize the Telegram confirmation text based on the file type or sender. Use a different image hosting service** if you don’t want to use imgbb.

For Who? Content Creators Youtube Automation Marketing Team How it works? 1 - Every week, retrieve the keywords you want to track 2 - Thanks to Apify, scrape videos from YouTube Search related to these keywords, filtered by relevance 3 - Wait until the dataset is completed 4 - Get the information contained in the dataset 5 - For each video, clean and summarize the script 6 - Upload everything to your Airtable database 📺 YouTube Video Tutorial: Setup (~5min) Scheduled Trigger: Select the frequency you want. If you change it, update the data accordingly in the "Create Videos Dataset" HTTP Request node in Body ➡️ JSON ➡️ dateFilter. Setup Keywords: Enter keywords related to the niche you want. If you change the number of keywords, update the data accordingly in the "Create Videos Dataset" HTTP Request node in Body ➡️ JSON ➡️ searchQueries. Create Videos Dataset: Refer to the Apify documentation for more: https://docs.apify.com/api/v2/getting-started APIs: For all HTTP Request nodes in the URL field, replace [YOUR_API_TOKEN] with your API token. 👨‍💻 More Workflows : https://n8n.io/creators/nasser/

AI Image Generator & Editor with GPT-4 Vision - Complete Workflow Template Description Transform text prompts into stunning images or edit existing visuals using OpenAI's latest GPT-4 Vision model through an intuitive web form interface. This comprehensive n8n automation provides three powerful image generation modes: 🎨 Text-to-Image Generation Simply enter a descriptive prompt and generate high-quality images from scratch using OpenAI's gpt-image-1 model. Perfect for creating original artwork, concepts, or visual content. 🖼️ Image-to-Image Editing Upload an existing image file and transform it based on your text prompt. The AI analyzes your input image and applies modifications while maintaining the original structure and context. 🔗 URL-Based Image Editing Provide a direct URL to any online image and edit it with AI. Great for quick modifications of web images or collaborative workflows. Key Features Smart Input Processing Flexible Form Interface**: User-friendly web form with authentication Multiple Input Methods**: File upload, URL input, or text-only generation Quality Control**: Selectable quality levels (low, medium, high) Format Support**: Accepts PNG, JPG, and JPEG formats Advanced AI Integration Latest GPT-4 Vision Model**: Uses gpt-image-1 for superior results Intelligent Switching**: Automatically detects input type and routes accordingly Context-Aware Editing**: Maintains image coherence during modifications Customizable Parameters**: Control size (1024x1024), quality, and generation settings Dual Storage Options Google Drive Integration**: Automatic upload with public sharing permissions ImgBB Hosting**: Alternative cloud storage for instant public URLs File Management**: Organized storage with timestamp-based naming Instant Telegram Delivery Real-time Notifications**: Results sent directly to your Telegram chat Rich Media Messages**: Includes generated image with prompt details Quick Access Links**: Direct links to view and download results Markdown Formatting**: Clean, professional message presentation Technical Workflow Form Submission → User submits prompt and optional image Smart Routing → System detects input type (text/file/URL) AI Processing → OpenAI generates or edits image based on mode Binary Conversion → Converts base64 response to downloadable file Cloud Upload → Stores in Google Drive or ImgBB with public access Telegram Delivery → Sends result with viewing links and metadata Perfect For Content Creators**: Generate unique visuals for social media and marketing Designers**: Quick concept development and image variations Developers**: Automated image processing for applications Teams**: Collaborative image editing and sharing workflows Personal Use**: Transform ideas into visual content effortlessly Setup Requirements OpenAI API Key**: Access to GPT-4 Vision model Google Drive API** (optional): For Google Drive storage ImgBB API Key** (optional): For alternative image hosting Telegram Bot**: For result delivery Basic Auth Credentials**: For form security What You Get ✅ Complete image generation and editing pipeline ✅ Secure web form with authentication ✅ Dual cloud storage options ✅ Instant Telegram notifications ✅ Professional result formatting ✅ Flexible input methods ✅ Quality control settings ✅ Automated file management Start creating AI-powered images in minutes with this production-ready template! Tags: #AI #ImageGeneration #OpenAI #GPT4 #ImageEditing #Telegram #GoogleDrive #Automation #ComputerVision #ContentCreation

This n8n template demonstrates how to automatically generate and publish blog posts using trending keywords, AI-generated content, and watermarked stock images. Use cases include maintaining an active blog with fresh SEO content, scaling content marketing without manual writing, and automating the full publishing pipeline from keyword research to WordPress posting. Good to know At time of writing, each AI content generation step will incur costs depending on your OpenAI pricing plan. Image search is powered by Pexels, which provides free-to-use stock images. The workflow also applies a watermark for branding. Google Trends data may vary by region, and results depend on availability in your selected location. How it works The workflow begins with a scheduled trigger that fetches trending keywords from Google Trends. The XML feed is converted to JSON and filtered for relevant terms, which are logged into a Google Sheet for tracking. One random keyword is selected, and OpenAI is used to generate blog content around it. A structured output parser ensures the text is clean and well-formatted. The system then searches Pexels for a matching image, uploads it, adds metadata for SEO, and applies a watermark. Finally, the complete article (text and image) is published directly to WordPress. How to use The schedule trigger is provided as an example, but you can replace it with other triggers such as webhooks or manual inputs. You can also customize the AI prompt to match your niche, tone, or industry focus. For higher volumes, consider adjusting the keyword filtering and batching logic. Requirements OpenAI account for content generation Pexels API key for stock image search Google account with Sheets for keyword tracking WordPress site with API access for publishing Customising this workflow This automation can be adapted for different use cases. Try adjusting the prompts for technical blogs, fashion, finance, or product reviews. You can also replace the image source with other providers or integrate your own media library. The watermark feature ensures branding, but it can be modified or removed depending on your needs.

Who's it for Content marketers and SEO specialists who need to generate multiple SEO-optimized articles targeting keyword variations. Ideal for affiliate sites, niche blogs, or service-based businesses creating location/product-specific landing pages. How it works This workflow automates bulk content creation from keyword list to Webflow draft: Loads keywords from Google Sheets with structured format (main keyword + slug) AI generates articles - Creates 600+ word content following SEO best practices Creates custom images - Calls a sub-workflow using Gemini 2.5 Flash to generate relevant featured images Quality validation - Ensures minimum word count; expands content if needed HTML conversion - Transforms markdown to Webflow-ready HTML Result tracking - Logs success/errors to separate Google Sheets The workflow includes automatic content expansion, error handling, and uses a separate sub-workflow as a tool for AI image generation. Important: The subworkflow should be created as an individual one. Then, in the Agent Tool node, you need to select it as the tool. DON'T try to run it inside the same workflow. Requirements OpenAI API key (for content generation) OpenRouter API key or similar (for Gemini image generation via sub-workflow) Google Sheets with three tabs: keywords, content_created, webflow_error_logs Webflow site with CMS collection configured Google Drive folder for image storage Companion workflow**: "AI image generation for automatic content creation" (imported separately and called as a tool) How to set up 1. Import both workflows separately: Main workflow: "Bulk SEO content generation and Webflow draft creation with AI images" Sub-workflow: "AI image generation for automatic content creation" 2. Configure your Google Sheet with the recommended structure Required sheets: keywords: id, main keyword, head terms, modifiers, slug, status content_created: id, slug, meta description, content, generatedAt, updated on webflow_error_logs: keyword, error, timestamp, status 3. Add API credentials: OpenAI API OpenRouter API with Gemini access or similar (for image generation) Webflow OAuth2 API (see Webflow setup instructions in sticky note) Google Sheets Google Drive 4. Update workflow configuration: Google Sheets: Update document IDs in all Google Sheets nodes Webflow: Set your Site ID and Collection ID in Create/Update Post nodes Google Drive: Set folder ID in the image generation sub-workflow AI Image Tool: Verify the "AI Image Generation Tool1" node points to your imported sub-workflow 5. Test with a single keyword: 6. Schedule for production: Enable the Schedule Trigger (currently set to monthly) How to customize Content customization: Adjust article length in AI Agent prompt (currently 600-800 words) Modify article structure/sections in the system prompt Change content tone by editing the AI Agent system message Add/remove content sections in the prompt template Image customization: Change AI model in sub-workflow (currently Gemini 2.5 Flash) Modify image style/prompt in the AI Image Generation Tool parameters Update Google Drive destination folder Webflow customization: Add custom CMS fields by updating Create/Update Post nodes Modify field mappings to match your Webflow collection structure Change draft behavior or add auto-publish logic Workflow behavior: Adjust batch size in Loop Over Items node Modify quality threshold (currently 600 words minimum) Change error handling/retry logic Update scheduling frequency in Schedule Trigger