{"workflow":{"id":13103,"name":"Generate a weekly content calendar with OpenAI GPT-5-mini, RSS feeds, and Notion","views":99,"recentViews":0,"totalViews":99,"createdAt":"2026-01-29T18:01:38.721Z","description":"\n# Generate Weekly Content Calendar with AI from RSS Feeds\n  \n**Categories:** AI, Content Creation, Marketing Automation, Productivity\n  \nNever run out of content ideas again. This workflow transforms trending industry news into a week's worth of structured content ideas, automatically organized in your Notion workspace—all while you sleep.\n  \n## Benefits\n\n  - **Save 3+ hours weekly** on content ideation and planning\n\n- **Stay relevant** by automatically tracking trending topics in your industry\n\n- **Consistent publishing schedule** with 7 ready-to-execute content ideas every Monday\n\n- **Structured output** with title, format, target audience, and key points for each idea\n\n- **Flexible customization** to match your content style and publishing cadence\n  \n## How It Works\n  \nEvery Monday at 9 AM, the workflow springs into action:\n  \n1. **Gathers fresh content** from multiple RSS feeds (TechCrunch, Ars Technica, MIT News by default)\n\n2. **Filters recent articles** published in the last 7 days to ensure relevance\n\n3. **Analyzes trends** by sending the top 20 articles to OpenAI\n\n4. **Generates 7 content ideas** using structured output with strict JSON formatting\n\n5. **Distributes across the week** from Monday to Friday with varied content types\n\n6. **Creates Notion pages** automatically with all metadata ready for your workflow\n\n  Each generated idea includes:\n\n- Clear, actionable title (max 80 characters)\n\n- Content type (LinkedIn post, carousel, thread, video, etc.)\n\n- Target audience segment\n\n- Recommended publish day\n\n- Key talking point to develop\n  \nThe AI prompt is carefully engineered to produce practical, professional content ideas that balance trending topics with original angles—avoiding generic summaries.\n  \n## Required Setup\n  \n**RSS Feeds:**\n\n- Default feeds included: TechCrunch, Ars Technica, MIT Science & Tech\n\n- Easily swap with your industry's top sources\n\n- Duplicate nodes to add more feeds (no limit)\n  \n**OpenAI API:**\n\n- Model: GPT-5-mini (latest generation, fast and cost-effective)\n\n- Average cost: ~$0.01 per weekly execution\n\n- Alternative: Use GPT-5 for even more creative ideas\n  \n**Notion Database:**\n\nCreate a database with these exact property names:\n\n- **Title** (title type)\n\n- **Content Type** (select or rich text)\n\n- **Target Audience** (rich text)\n\n- **Publish Day** (select: Monday, Tuesday, Wednesday, Thursday, Friday)\n\n- **Status** (select: Draft, In Progress, Done)\n\n- **Key Points** (rich text)\n \n**Configuration in Code Node:**\n\nCustomize the filtering behavior by editing constants at the top:\n\n- `DAYS_BACK`: How many days to look back (default: 7)\n\n- `MAX_ARTICLES`: Maximum articles to send to AI (default: 20)\n\n- `SNIPPET_LENGTH`: Preview length for descriptions (default: 150 chars)\n \n## Business Use Cases\n \n**Content Creators & Marketers:**\n\n- Generate LinkedIn content calendar based on industry trends\n\n- Transform news into educational threads for Twitter/X\n\n- Plan newsletter topics with current relevance\n  \n**Agencies:**\n\n- Scale content planning across multiple client industries\n\n- Maintain consistent posting schedules without manual research\n\n- Demonstrate ROI by tracking trending topic engagement\n  \n**Solo Founders & Thought Leaders:**\n\n- Stay top-of-mind by consistently sharing timely insights\n\n- Reduce decision fatigue with pre-structured ideas\n\n- Focus on execution instead of ideation\n  \n**Content Teams:**\n\n- Coordinate multi-format campaigns (posts, videos, carousels)\n\n- Distribute workload with clear assignments by day\n\n- Track status from Draft → Done in one view\n  \n## Set Up Steps\n  \n1. **Import the workflow** into your n8n instance\n\n2. **Configure RSS feeds**:\n\n- Click each RSS node\n\n- Replace URLs with your industry's top sources\n\n- Duplicate nodes for additional feeds (right-click → Duplicate)\n\n3. **Add OpenAI credentials**:\n\n- Click \"Generate Content Calendar (Structured)\" node\n\n- Add your OpenAI API key\n\n- Confirm model is set to `gpt-5-mini`\n\n4. **Create Notion database**:\n\n- Open Notion and create a new database\n\n- Add the 6 required properties (see Required Setup above)\n\n- Configure select options for Content Type and Status\n\n5. **Connect Notion**:\n\n- Click \"Create Database Page in Notion\" node\n\n- Add your Notion credentials\n\n- Select your content calendar database\n\n- Verify field mappings match your property names\n\n6. **Customize filtering** (optional):\n\n- Open \"Filter and Format Articles\" code node\n\n- Edit `DAYS_BACK`, `MAX_ARTICLES`, `SNIPPET_LENGTH` at the top\n\n7. **Test the workflow**:\n\n- Click \"Execute Workflow\" to run manually\n\n- Verify 7 pages are created in Notion\n\n- Check that fields are populated correctly\n\n8. **Enable the schedule**:\n\n- Toggle \"Active\" to enable weekly execution\n\n- Confirm trigger is set to Mondays at 9 AM\n  \n**Troubleshooting Tips:**\n\n- If no articles appear, check that RSS feeds are accessible\n\n- If AI returns errors, verify your OpenAI API key has credits\n\n- If Notion fails, ensure property names match exactly (case-sensitive)\n\n- For field mapping issues, use \"Add Field\" in the Notion node\n\n  **Difficulty Level:** Intermediate\n\n**Estimated Setup Time:** 20-30 minutes\n\n**Monthly Operating Cost:** ~$0.10-$0.30 (OpenAI API at 4 runs/month)\n\n  \n## Why This Template Stands Out\n  \nUnlike basic RSS-to-Notion workflows that just dump articles, this template:\n\n- **Analyzes and synthesizes** trends into original content angles\n\n- **Structures output** with strict validation for reliable automation\n\n- **Distributes strategically** across the workweek\n\n- **Mixes content formats** to maintain audience engagement\n\n- **Includes fallback handling** if no recent articles are found\n\n  \n\nThe code node is heavily documented with configuration constants, making it accessible even for non-developers to customize behavior without touching complex logic.\n","workflow":{"id":"Rq90UFhzDszsXRyyx5SgZ","meta":{"instanceId":"cbeebdeaf8bbc721fb723a5ddd32639a318ef9cb6556e00e4d2dc7a2110a9ea6"},"name":"Generate weekly content calendar with AI from RSS feeds","tags":[],"nodes":[{"id":"b44f2fe5-42ee-4950-a1ba-7e669b78ca91","name":"Weekly Monday 9AM","type":"n8n-nodes-base.scheduleTrigger","position":[1088,560],"parameters":{"rule":{"interval":[{"field":"weeks","triggerAtDay":[1],"triggerAtHour":9}]}},"typeVersion":1.2},{"id":"2544fab0-093b-4d42-bc2b-1148f5b2f00d","name":"RSS Feed - Tech News","type":"n8n-nodes-base.rssFeedRead","position":[1312,464],"parameters":{"url":"https://techcrunch.com/feed/","options":{}},"typeVersion":1},{"id":"cd4ab05f-e858-4b72-a586-ef01cc4dc556","name":"RSS Feed - Biz & IT","type":"n8n-nodes-base.rssFeedRead","position":[1312,656],"parameters":{"url":"https://feeds.arstechnica.com/arstechnica/technology-lab","options":{}},"typeVersion":1},{"id":"d5887fcb-ed45-4c73-9044-7caf86e47fbd","name":"RSS Feed - MIT Science & Tech","type":"n8n-nodes-base.rssFeedRead","position":[1312,864],"parameters":{"url":"https://news.mit.edu/rss/topic/science-technology-and-society","options":{}},"typeVersion":1},{"id":"2ea32e74-4006-4a67-8719-0c2aa271dc0d","name":"Combine All Articles","type":"n8n-nodes-base.merge","position":[1744,640],"parameters":{"numberInputs":3},"typeVersion":3},{"id":"2192d450-36c0-4b24-a84a-edf5aebbe6a1","name":"Filter and Format Articles","type":"n8n-nodes-base.code","position":[1968,656],"parameters":{"jsCode":"/*\n * Filter and Format Articles for AI\n * ==================================\n * Purpose: Filters recent articles and formats them as a numbered list\n *          for AI prompt consumption.\n * \n * Input: Array of article items from merged RSS feeds\n * Output: Object with articleCount, articlesList (formatted), rawArticles\n * \n * To customize: Change the UPPERCASE values below\n */\n\n// ⚙️ CONFIGURATION - Edit these to customize behavior\nconst DAYS_BACK = 7;           // Number of days to look back for articles\nconst MAX_ARTICLES = 20;       // Maximum number of articles to send to AI\nconst SNIPPET_LENGTH = 150;    // Maximum characters for article description preview\n\n// ==================== CODE START ====================\n\n// Create a date object for the cutoff point (7 days ago)\nconst cutoffDate = new Date();\n// Subtract DAYS_BACK days from today's date to get the oldest allowed date\ncutoffDate.setDate(cutoffDate.getDate() - DAYS_BACK);\n\n// Get all items from the previous node (Merge) and extract just the JSON data\n// $input.all() returns all items as array, .map() extracts the .json property from each\nconst allArticles = $input.all().map(item => item.json);\n\n// Filter, sort, and limit the articles\nconst processedArticles = allArticles\n  // Keep only articles that have a pubDate AND were published after the cutoff\n  .filter(article => {\n    // Skip articles without a publication date\n    if (!article.pubDate) return false;\n    // Compare article date with cutoff - keep if newer than cutoff\n    return new Date(article.pubDate) >= cutoffDate;\n  })\n  // Sort by publication date, newest first (descending order)\n  // b - a = descending (newest first), a - b would be ascending (oldest first)\n  .sort((a, b) => new Date(b.pubDate) - new Date(a.pubDate))\n  // Take only the first MAX_ARTICLES items (default: 20)\n  .slice(0, MAX_ARTICLES);\n\n// Format articles as a numbered list string for the AI prompt\nconst formattedList = processedArticles\n  .map((article, index) => {\n    // Get the article snippet, with fallbacks if contentSnippet doesn't exist\n    // Try contentSnippet first, then description, finally use default text\n    const snippet = (article.contentSnippet || article.description || 'No description')\n      // Truncate to SNIPPET_LENGTH characters to keep the list manageable\n      .substring(0, SNIPPET_LENGTH);\n    // Format each article as: \"1. \"Article Title\" - Description preview...\"\n    return `${index + 1}. \"${article.title}\" - ${snippet}...`;\n  })\n  // Join all formatted articles with newline characters into one string\n  .join('\\n');\n\n// ==================== CODE END ======================\n\n// Return the processed data in n8n's required format\n// Must return an array of objects, each with a 'json' property\nreturn [{\n  json: {\n    articleCount: processedArticles.length,  // Number of articles found (for conditional check)\n    articlesList: formattedList,              // Formatted string for AI prompt\n    rawArticles: processedArticles            // Original article objects (for reference/debugging)\n  }\n}];\n"},"typeVersion":2},{"id":"5730d377-6228-4d7c-9ec0-d02a6003cd96","name":"Has Articles?","type":"n8n-nodes-base.if","position":[2176,640],"parameters":{"options":{},"conditions":{"options":{"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"condition-has-articles","operator":{"type":"number","operation":"gt"},"leftValue":"={{ $json.articleCount }}","rightValue":0}]}},"typeVersion":2},{"id":"38d662bb-a7f7-493c-9d79-27b409dabc61","name":"Generate Content Calendar (Structured)","type":"@n8n/n8n-nodes-langchain.openAi","position":[2400,544],"parameters":{"modelId":{"__rl":true,"mode":"list","value":"gpt-5-mini","cachedResultName":"GPT-5-MINI"},"options":{"maxTokens":4000},"messages":{"values":[{"role":"system","content":"=# ROLE\nYou are a content strategist creating a weekly content calendar.\n\n# TASK\n\nYour task is to analyze a list of trending articles and generate content ideas for the following week.\n\n# RULES\n\n## STRICT OUTPUT RULES:\n\n- Output MUST be valid JSON only.\n- Do NOT include Markdown, comments, explanations, or extra text.\n\n- Each object MUST follow EXACTLY this structure:\n\n{\n  \n  \"Title\": \"...\",\n  \"Content type\": \"...\",\n  \"Target Audience\": \"...\",\n  \"Publish Day\": \"...\",\n  \"Status\": \"Draft\",\n  \"Key Point\": \"...\"\n}\n\n## FIELD RULES:\n- \"Title\": short, clear, and actionable (max 80 characters).\n- \"Content type\": choose one (e.g. LinkedIn post, Carousel, Short video, Newsletter, Thread, Case study, Checklist).\n- \"Target Audience\": specific professional segment.\n- \"Publish Day\": MUST be one of these exact values:\n  MONDAY, TUESDAY, WEDNESDAY, THURSDAY, FRIDAY\n- \"Status\": MUST always be \"Draft\".\n- \"Key Point\": one concise sentence describing the main takeaway.\n\n## CONTENT RULES:\n\n- Generate exactly 7 ideas.\n- Distribute ideas across MONDAY–FRIDAY (no empty days; some days may repeat).\n- Mix content types across the week (avoid repeating the same type more than twice).\n- Each idea must be inspired by the trends but provide a unique, original angle.\n- Focus on practical, actionable value for professionals.\n\n# IMPORTANT:\nReturn JSON only."},{"content":"=Based on these trending articles from this week:\n\n{{ $json.articlesList }}\n\nGenerate exactly 7 content ideas for next week's content calendar.\n"}]},"jsonOutput":true},"typeVersion":1.8},{"id":"2b237c53-b051-4983-bc34-04ebaeacd40a","name":"Split Into Individual Ideas","type":"n8n-nodes-base.splitOut","position":[2688,544],"parameters":{"options":{},"fieldToSplitOut":"message.content.ideas"},"typeVersion":1},{"id":"85f07e46-72c9-469e-bb33-26921ef65ab5","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[448,176],"parameters":{"width":520,"height":924,"content":"## Generate weekly content calendar with AI from RSS feeds\n\n### How it works\nThis workflow automatically generates a weekly content calendar by analyzing trending articles from your industry RSS feeds. Every Monday at 9 AM, it collects articles from TechCrunch, Ars Technica, and MIT News, filters those published in the last 7 days, and uses OpenAI's structured output to generate exactly 7 content ideas in validated JSON format. Each idea includes a title, content type, target audience, and key talking points—then automatically adds them to your Notion database.\n\n### Setup steps\n1. **Configure RSS feeds**: Replace the example URLs with feeds relevant to your industry\n2. **Add OpenAI credentials**: Connect your OpenAI API key (gpt-5-mini recommended)\n3. **Create Notion database** with these properties:\n   - Title (title)\n   - Content Type (select: blog, linkedin, twitter, video, newsletter)\n   - Target Audience (rich text)\n   - Publish Day (select: Monday-Friday)\n   - Status (select: Draft, In Progress, Done)\n   - Key Points (rich text)\n4. **Connect Notion**: Add your Notion credentials and select your database\n5. **Map fields**: In the Notion node, map the AI output fields to your database properties\n6. **Test manually** before enabling the schedule\n\n**Tip**: Duplicate RSS nodes to add more sources. The AI automatically adjusts to more input."},"typeVersion":1},{"id":"87048c0a-6fd0-4275-b7cb-e978a8dc4e71","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[1232,352],"parameters":{"color":7,"width":272,"height":720,"content":"### 📥 RSS Sources\nAdd your industry feeds here.\nDuplicate nodes for more sources."},"typeVersion":1},{"id":"fa37bf50-0e1e-4035-ac45-65b89bec62e8","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[1664,448],"parameters":{"color":7,"width":472,"height":440,"content":"### 🔄 Processing\nAggregate and filter articles from last 7 days.\n\n**Customize in code:**\n- `DAYS_BACK` → time window\n- `MAX_ARTICLES` → limit for AI"},"typeVersion":1},{"id":"66b56246-3251-4ff5-8f75-52035c5d4935","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[2336,400],"parameters":{"color":7,"width":464,"height":352,"content":"### 🤖 AI Generation\nGPT creates 7 content ideas with strict JSON output.\n\nDistributes across Monday-Friday."},"typeVersion":1},{"id":"b6dc2f28-9f0c-407d-a2de-b6fe93f0e727","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[2832,384],"parameters":{"color":7,"width":256,"height":384,"content":"### 📝 Notion Output\nEach idea becomes a database page.\n\nReady for your content workflow."},"typeVersion":1},{"id":"d2554d17-ab84-4d9d-89f9-d118372ac06c","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[2368,784],"parameters":{"color":7,"width":400,"height":240,"content":"\n\n\n\n\n\n\n\n\n\n\n**No articles found in timeframe**\n\nStop execution gracefully."},"typeVersion":1},{"id":"1c2c3d0c-e5aa-484a-b5f0-1b694a641a7a","name":"No Recent Articles","type":"n8n-nodes-base.noOp","position":[2400,800],"parameters":{},"typeVersion":1},{"id":"22f4adea-5c1f-4498-a657-ff34bb52c2da","name":"Create Database Page in Notion","type":"n8n-nodes-base.notion","position":[2896,544],"parameters":{"title":"={{ $json.Title }}","options":{},"resource":"databasePage","databaseId":{"__rl":true,"mode":"list","value":""},"propertiesUi":{"propertyValues":[{"key":"Content Type","richText":"={{ $json['Content type'] }}"},{"key":"Target Audience","richText":"={{ $json['Target Audience'] }}"},{"key":"Publish Day","richText":"={{ $json['Publish Day'] }}"},{"key":"Status","richText":"={{ $json.Status }}"},{"key":"Key Points","richText":"={{ $json['Key Point'] }}"}]}},"typeVersion":2.2}],"active":false,"pinData":{},"settings":{"availableInMCP":false,"executionOrder":"v1"},"versionId":"d070e9ed-1d62-4db9-9231-892f76bee2eb","connections":{"Has Articles?":{"main":[[{"node":"Generate Content Calendar (Structured)","type":"main","index":0}],[{"node":"No Recent Articles","type":"main","index":0}]]},"Weekly Monday 9AM":{"main":[[{"node":"RSS Feed - Tech News","type":"main","index":0},{"node":"RSS Feed - Biz & IT","type":"main","index":0},{"node":"RSS Feed - MIT Science & Tech","type":"main","index":0}]]},"RSS Feed - Biz & IT":{"main":[[{"node":"Combine All Articles","type":"main","index":1}]]},"Combine All Articles":{"main":[[{"node":"Filter and Format Articles","type":"main","index":0}]]},"RSS Feed - Tech News":{"main":[[{"node":"Combine All Articles","type":"main","index":0}]]},"Filter and Format Articles":{"main":[[{"node":"Has Articles?","type":"main","index":0}]]},"Split Into Individual Ideas":{"main":[[{"node":"Create Database Page in Notion","type":"main","index":0}]]},"RSS Feed - MIT Science & Tech":{"main":[[{"node":"Combine All Articles","type":"main","index":2}]]},"Generate Content Calendar (Structured)":{"main":[[{"node":"Split Into Individual Ideas","type":"main","index":0}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":17,"nodeTypes":{"n8n-nodes-base.if":{"count":1},"n8n-nodes-base.code":{"count":1},"n8n-nodes-base.noOp":{"count":1},"n8n-nodes-base.merge":{"count":1},"n8n-nodes-base.notion":{"count":1},"n8n-nodes-base.splitOut":{"count":1},"n8n-nodes-base.stickyNote":{"count":6},"n8n-nodes-base.rssFeedRead":{"count":3},"n8n-nodes-base.scheduleTrigger":{"count":1},"@n8n/n8n-nodes-langchain.openAi":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Diego Alejandro Parrás","username":"diegoalejandroparras","bio":"AI Management Professor @ UBA & Founder @ Nodemat. My baby: a production n8n cluster with 22 containers (6 dedicated webhooks including one for MCP servers, 6 runners, 6 workers, Redis & PostgreSQL). \n\nCreator of GIA Method. \n\nTeaching advanced automation while building enterprise AIBPS solutions. \nLet's talk complex architectures.","verified":true,"links":["https://www.linkedin.com/in/diegoparras/"],"avatar":"https://gravatar.com/avatar/2cc7ac6eaa28f81a5a481407b4230cd28d274eb4a0ab1e01e1516522ff17e90a?r=pg&d=retro&size=200"},"nodes":[{"id":20,"icon":"fa:map-signs","name":"n8n-nodes-base.if","codex":{"data":{"alias":["Router","Filter","Condition","Logic","Boolean","Branch"],"details":"The IF node can be used to implement binary conditional logic in your workflow. You can set up one-to-many conditions to evaluate each item of data being inputted into the node. 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