Back to Catalog

Automated viral content engine for LinkedIn & X with AI generation & publishing

Diptamoy BarmanDiptamoy Barman
3575 views
2/3/2026
Official Page

Social Media Spark (SMS) โ€” Automated Viral Content Engine

Automate your entire content workflow: discover viral ideas, generate posts in your tone, repurpose for X, and auto-publish โ€” reducing 90% of manual effort.


๐Ÿš€ What it Does

  • Scrapes competitors or niche profiles on LinkedIn to find high-performing posts.
  • Classifies and saves evergreen content ideas for later use.
  • Generates fresh posts in your own voice with matching images.
  • Repurposes content for X (Twitter) in a platform-optimized style.
  • Automatically publishes content to LinkedIn and X on your schedule.
  • Allows on-demand commands via Telegram for research or instant content generation.

๐Ÿงฉ Why Use It

  • Save time: no more manual scraping, idea collection, or formatting.
  • Stay consistent: maintain a daily content pipeline.
  • Multi-platform leverage: create once, adapt for LinkedIn and X.
  • Creative control: mix automation with optional human review.
  • Scalable: extend to more platforms, analytics, and workflows as you grow.

๐Ÿ”ง Prerequisites & Setup

Before importing or activating the workflow, prepare these:

  • AI Provider (OpenAI / Gemini / OpenRouter)
    For classifying posts, generating new content, repurposing for X.

  • Google Sheets
    Central database for competitors, ideas, generated posts, and posting status.

  • Google Drive
    Stores generated images.

  • Apify & Browseract
    Scrapes LinkedIn profiles, posts, and performs research tasks.

  • LinkedIn API
    Needed for automated LinkedIn publishing.

  • X (Twitter) API
    Requires OAuth 1.0a for image uploads and OAuth 2.0 for text posting.

  • Telegram Bot
    Enables on-demand commands and notifications.
    Set your Telegram User ID in the trigger node.

> ๐Ÿ”Ž In each sub-workflow, look for nodes marked โ€œConfigure Me!โ€ to replace example prompts, search keywords, sheet IDs, etc.


โš™๏ธ How It Works (Simplified Flow)

  1. Scrape & Classify: Collect high-engagement posts โ†’ keep evergreen ones.
  2. Generate Content: Rewrite ideas into new posts in your voice โ†’ create images.
  3. Repurpose for X: Adapt LinkedIn posts for short-form, high-impact tweets.
  4. Auto-Publish: Post daily on LinkedIn and X.
  5. Control via Telegram: Manually trigger scraping, research, or post generation.

๐Ÿ’ก Best Practices & Tips

  • Keep all API keys private โ€” never share them in public repos or screenshots.
  • Adjust cron schedules (e.g., scraping on weekends, posting on weekdays) to fit your content rhythm.
  • Add Human-in-the-Loop review steps for brand-sensitive content.
  • Extend to other platforms (Instagram, TikTok, YouTube Shorts) as needed.
  • Experiment with prompt variations for different tones or creative styles.
  • Add analytics logging (likes, comments, clicks) to measure content performance.

๐Ÿ™‹โ€โ™‚๏ธ Who is This For

  • Solo creators & founders who want to post consistently but donโ€™t have time for daily ideation.
  • Small marketing teams that need to keep up with trends without spending hours on research.
  • Consultants & thought leaders who want to amplify their personal brand on LinkedIn and X.
  • Startups & bootstrapped businesses that need a lean but reliable content engine.
  • Content strategists who want a data-driven, repeatable pipeline for finding and using what works.

Or anyone who wants to boost social presence by 300%


๐Ÿ’ก Why SMS Stands Out

  • Authentic voice: Uses your own tone and style (defined in prompts and examples), so posts feel personal โ€” not generic AI fluff.
  • Data-driven: Pulls from real, viral posts in your niche to inspire fresh content.
  • Quality over quantity: Focuses only on proven viral ideas instead of churning random posts.
  • Consistent growth: Keeps your posting regular, so you stay visible and relevant.
  • Efficient workflow: Minimizes manual work while letting you step in when needed (e.g., for approvals or special campaigns).

> โšก SMS combines real market data with your unique voice โ€” so you post smarter, not just more often.

Automated Viral Content Engine for LinkedIn & X with AI Generation & Publishing

This n8n workflow automates the process of generating and publishing viral content across LinkedIn and X (formerly Twitter), leveraging AI for content creation and a human-in-the-loop approval system. It streamlines content distribution, ensuring that only approved, high-quality posts reach your audience.

What it does

This workflow simplifies and automates your social media content strategy through the following steps:

  1. Manual Trigger / Scheduled Execution: The workflow can be initiated manually or on a predefined schedule.
  2. AI Content Generation: It calls a sub-workflow ("Execute Sub-workflow") which is responsible for generating content using an AI Agent (likely powered by Google Gemini or OpenRouter Chat Model) and potentially other tools.
  3. Structured Output Parsing: The AI-generated content is then processed by a "Structured Output Parser" to ensure it adheres to a predefined format.
  4. Human-in-the-Loop Approval (Telegram): The generated content is sent to a Telegram chat for review.
  5. Conditional Approval: An "If" node checks for approval from Telegram.
  6. Content Filtering: If approved, the content is further filtered by an "If" node, potentially based on content type or platform.
  7. Content Transformation: An "Edit Fields (Set)" node prepares the content for publishing.
  8. Loop Over Items: The workflow iterates through the content items.
  9. Platform-Specific Publishing:
    • LinkedIn: Publishes the content to LinkedIn.
    • X (formerly Twitter): Publishes the content to X.
  10. Delay: A "Wait" node introduces a delay between posts to avoid overwhelming platforms or appearing spammy.
  11. Google Sheets Logging: The published content details are logged into a Google Sheet for tracking and analytics.
  12. Google Drive Storage: Content-related files (e.g., images, videos) can be stored in Google Drive.
  13. File Conversion/Extraction: Includes nodes for converting and extracting files, suggesting support for various media types.
  14. Duplicate Removal: A "Remove Duplicates" node ensures unique content is processed.
  15. Aggregation: An "Aggregate" node can combine data from multiple sources or steps.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Telegram Account & Bot: A Telegram bot token and chat ID for the human-in-the-loop approval process.
  • LinkedIn Account: Credentials for your LinkedIn account to publish posts.
  • X (formerly Twitter) Account: Credentials for your X account to publish tweets.
  • Google Sheets Account: A Google account with access to Google Sheets for logging.
  • Google Drive Account (Optional): A Google account with access to Google Drive for file storage.
  • AI Model Credentials: API keys or credentials for your chosen AI model (e.g., Google Gemini, OpenRouter) to be configured within the "Execute Sub-workflow" (or directly in the AI Agent node if the sub-workflow is simple).

Setup/Usage

  1. Import the Workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • Set up your Telegram Bot credentials.
    • Configure your LinkedIn API credentials.
    • Configure your X (formerly Twitter) API credentials.
    • Set up your Google Sheets credentials.
    • Set up your Google Drive credentials (if using).
    • Ensure the AI Model credentials (e.g., Google Gemini, OpenRouter) are correctly configured within the "Execute Sub-workflow" or the relevant AI nodes.
  3. Customize Workflow Nodes:
    • Telegram Trigger/Send Message: Update the Chat ID in the Telegram nodes to your specific Telegram chat for approvals.
    • Execute Sub-workflow: Ensure the referenced sub-workflow exists and is configured for your AI content generation logic.
    • If Nodes: Review and adjust the conditions for content approval and filtering as needed.
    • Edit Fields (Set): Modify the content transformation logic to fit your desired output format for LinkedIn and X.
    • LinkedIn/X Nodes: Customize the post content and any media attachments.
    • Google Sheets: Specify the Spreadsheet ID and sheet name for logging.
    • Wait: Adjust the delay duration between posts.
  4. Activate the Workflow: Once configured, activate the workflow. You can trigger it manually for testing or set up a schedule using the "Schedule Trigger" node.

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 competitorโ€™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 โ€” Manually start the workflow or schedule it to run periodically. Input Setup โ€” Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) โ€” 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 โ€” Clean and convert GPT output into JSON format. Data Storage (Google Sheets) โ€” 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 โ€œSet Input Fieldsโ€ 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 โ†’ Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection โ†’ Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report โ†’ Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization โ†’ Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs โ†’ 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 Itโ€™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.

Ranjan DailataBy Ranjan Dailata
161

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chatโ€”turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. ๐Ÿ“‹ What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing ๐Ÿ”ง Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation ๐Ÿ”‘ Required Credentials OpenAI API Setup Go to platform.openai.com โ†’ API keys (sidebar) Click "Create new secret key" โ†’ Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai โ†’ Dashboard โ†’ API Keys Generate a new API key โ†’ Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) โš™๏ธ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowโ€”chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" ๐ŸŽฏ Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration โš ๏ธ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive โžœ Download PDF โžœ OCR text โžœ AI normalize to JSON โžœ Upsert Buyer (Account) โžœ Create Opportunity โžœ Map Products โžœ Create OLI via Composite API โžœ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content โ†’ the parsed JSON (ensure itโ€™s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id โžœ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total โžœ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger โ†’ Download File From Google Download File From Google โ†’ Extract from File โ†’ Update File to One Drive Extract from File โ†’ Message a model Message a model โ†’ Create or update an account Create or update an account โ†’ Create an opportunity Create an opportunity โ†’ Build SOQL Build SOQL โ†’ Query PricebookEntries Query PricebookEntries โ†’ Code in JavaScript Code in JavaScript โ†’ Create Opportunity Line Items --- Quick setup checklist ๐Ÿ” Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. ๐Ÿ“‚ IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) ๐Ÿง  AI Prompt: Use the strict system prompt; jsonOutput = true. ๐Ÿงพ Field mappings: Buyer tax id/name โ†’ Account upsert fields Invoice code/date/amount โ†’ Opportunity fields Product name must equal your Product2.ProductCode in SF. โœ… Test: Drop a sample PDF โ†’ verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep โ€œReturn only a JSON arrayโ€ as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields donโ€™t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your orgโ€™s domain or use the Salesforce nodeโ€™s Bulk Upsert for simplicity.

Le NguyenBy Le Nguyen
942