by Barbora Svobodova
Create LinkedIn Post from Telegram Voice or Text Message with AI Image Who's it for This workflow is perfect for busy professionals, content creators, and marketers who want to publish polished LinkedIn posts without spending time on formatting or design. Send a quick text or voice message via Telegram, and get a fully formatted LinkedIn post with a relevant AI-generated image, post it immediately on LinkedIn. Example use cases: Entrepreneurs sharing business insights on the go without opening LinkedIn Marketers creating consistent content during commutes or between meetings Thought leaders turning quick voice notes into professional posts with visuals How it works / What it does Receive text or voice messages through a Telegram bot. Transcribe voice messages using OpenAI's audio transcription. Transform raw input into a professional LinkedIn post using AI formatting (proper structure, tone, and character limits). Generate a relevant image prompt based on post content. Create an AI image that matches the post topic. Automatically publish the complete post (text + image) to LinkedIn. How to set up Create a Telegram bot via @BotFather and obtain your API token. For self-hosted n8n users: Create a LinkedIn app at developer.linkedin.com to get OAuth credentials (Client ID and Client Secret). Add the OpenAI API key, LinkedIn OAuth credentials, and Telegram API to n8n. Assign your credentials to the Telegram, OpenAI, and LinkedIn nodes. Deploy and activate the workflow. Send a text or voice message to your Telegram bot and watch it create and post to LinkedIn! Requirements Telegram Bot Token OpenAI API Key LinkedIn OAuth credentials n8n instance (cloud or self-hosted) How to customize the workflow Modify the LinkedIn Post Text prompt to match your personal writing style or brand voice. Adjust image generation settings (model, size, style) in the Create Image node. Add approval steps by routing posts to Google Sheets, Airtable, or Notion before publishing. Create a second workflow to schedule approved posts for specific times. Limitations and Usage Tips Input Clarity**: Voice messages should be clear and well-articulated for accurate transcription. LinkedIn Character Limits**: The AI formatter optimizes posts for 1,242-2,500 characters. API Costs**: Each post generation uses OpenAI API calls for transcription (if voice), text formatting, image prompt creation, and image generation. Monitor your usage to manage costs. LinkedIn Rate Limits**: LinkedIn API has posting frequency limits. Avoid bulk posting in short time periods to prevent rate limiting.
by Chris Jadama
Voice-to-Ideas: Auto-Transcribe Telegram Voice Notes to Google Sheets Who it's for Creators, entrepreneurs, writers, and anyone who wants to capture ideas quickly without typing. This workflow is ideal for storing thoughts, content ideas, brainstorms, reminders, or voice memos on the go. What it does This workflow listens for Telegram voice messages, sends the audio to OpenAI Whisper for transcription, and saves the raw text directly into a Google Sheet. No formatting or additional processing is applied. The exact transcription from the audio is stored as-is. How it works A Telegram Trigger detects when you send a voice message to your bot. The Telegram node downloads the audio file. OpenAI Whisper transcribes the voice note into text. The raw transcription is appended to Google Sheets along with the current date. Requirements Telegram bot token (created via BotFather) OpenAI API key with Whisper transcription enabled Google Sheets credentials connected in n8n A Google Sheet with two columns: Notes (stores the transcription text) Date (timestamp of the voice note) Setup steps Create a Telegram bot with BotFather and connect Telegram credentials in n8n. Add your OpenAI API key to the OpenAI node. Connect Google Sheets credentials in n8n. Create a Google Sheet with two columns: Notes and Date. Send a voice message to your Telegram bot to test the workflow.
by System Admin
This allows different routes to input into our agent (e.g. the retry branch). In the AI Agent, we can use a relative $json reference for data, since it's always the same input schema going in. . Place...
by AmirHossein MnasouriZade
Setting Up and Generating TOTP Step 1: Receive QR Code and Extract the Link 1. Receive the QR Code from the 2FA service After enabling two-factor authentication (2FA) on services like OpenAI, Google, GitHub, etc., a QR Code will be given to you, which you need to scan. This QR Code contains the TOTP link used to generate one-time passcodes. 2. Extract the link from the received QR Code To extract the link from the QR Code, use online tools. These tools will help you extract the corresponding link. After using an online tool, the extracted link will appear in the following format: otpauth://totp/ServiceName:username?secret=secret_key&issuer=ServiceName For example: otpauth://totp/OpenAI:amir676080@gmail.com?secret=test-test-test&issuer=OpenAI Step 2: Create TOTP Credential in n8n Create a new Credential To use TOTP in n8n, you need to create a new TOTP Credential. Enter the details in the Credential In the Secret field:* Enter the *secret key** (extracted from the QR Code link). For example: test-test-test In the Label field:* Enter *ServiceName:username** For example: OpenAI:amir676080@gmail.com Save the Credential After entering the information, click Save to save the Credential. Step 3: Get the TOTP Code Click on Test Workflow After setting up the credentials in n8n, click on Test, and the corresponding code will be delivered to you. Output: [ { "token": "720769", "secondsRemaining": 18 } ] ==This code is exactly the same as the one generated by apps and services like Google Authenticator or Authy. 🔐== Contact me on [Telegram]: https://t.me/amir676080
by Calistus Christian
What this workflow does Front-door chat orchestrator that delegates calendar requests to a separate Sub-Agent workflow which holds Google Calendar tools (Get, Create, Delete). Keeps the agent persona and memory in the Parent for clean separation of concerns. Pipeline: Chat Trigger → Parent Agent ("Albert") → sub_agent_cal (Execute Workflow Tool) → Child Sub-Agent → Google Calendar Category: Productivity / Calendar / Agentic\ Time to set up: ~10--15 minutes\ Difficulty: Intermediate\ Cost: Mostly free (n8n CE; OpenAI + Google Calendar usage as configured) * What you'll need n8n with chat trigger enabled. OpenAI credentials. The companion template: Agentic Google Calendar Assistant --- Sub-Agent (Calendar Tools). After importing both, open this Parent and re-select the Sub-Agent in the toolWorkflow node. * Set up steps Import this Parent workflow. Import the Sub-Agent workflow (Template B). In the Parent, open sub_agent_cal (Tool → Workflow) and select the imported Sub-Agent workflow. Ensure the input mapping passes: chatInput → text sessionId → sessionid Add your OpenAI credential to the OpenAI Chat Model node. Activate the Parent workflow. * Testing "Create a meeting tomorrow 3--4pm called 'Product Sync'" → Sub-Agent should create the event and the agent should confirm. "What's on my calendar this week?" → Lists events. "Delete my 'Dentist' appointment on Thursday" → Finds and deletes the event.
by YungCEO
Done-For-You Social Media Trend Tracker for Content Creators | Instant AI Video Ideas 💥 What It Does This pre-built n8n workflow is your ultimate shortcut to viral content. It automatically scouts the web for trending social media topics and generates hyper-relevant video ideas, complete with engaging hooks and calls to action, directly from the latest trends. No more endless scrolling or brainstorming sessions – just plug in and receive daily, actionable content inspiration delivered straight to your Discord channel. Stop missing out on viral trends and start creating content that captivates your audience from day one, effortlessly. This fully installed automation transforms your content strategy, giving you an unfair advantage in the crowded digital landscape. ⚙️ Key Features ⚡ Instant deployment: Pre-configured n8n workflow, ready to run in minutes. 🧠 AI-powered content engine: Generates viral video ideas with hooks & CTAs (powered by OpenAI). 📈 Automated trend discovery: Daily insights from top social platforms without manual research. 💬 Discord integration: Delivers actionable ideas directly to your team or private channel. 🚀 Zero-setup solution: No coding, no complex API configurations required. 😩 Pain Points Solved Sick of endless trend research and content ideation headaches? Tired of missing out on viral opportunities and falling behind competitors? Frustrated with complex API setups and coding your own automations? Struggling to consistently produce fresh, engaging content that performs? Wasting valuable time on manual content planning and brainstorming? 📦 What’s Included Fully configured n8n workflow file (.json) Step-by-step installation & connection guide Pre-written AI prompt for optimal video idea generation Dedicated support to ensure seamless launch 🚀 Call to Action Get your viral content ideas delivered daily. No setup. No stress. 🏷️ Optimized Tags done for you system, ai automation, n8n workflow, social media trends, content ideas, viral video, tiktok content, youtube shorts, instagram reels, discord bot, pre built workflow, instant download, marketing automation
by Loren Brabante
What It Does This workflow lets users create Google Calendar events through natural chat messages — no forms, no clicking around, just type like you're talking to a friend. For example, you can say: “Lunch with John tomorrow at 12:30” and it’ll auto-create a calendar event with the correct title, time, and duration. How It Works Trigger: Chat Message Received The flow starts with a chat interface node (When chat message received) that listens for incoming user messages like: “Book dentist next Wed 10am” “Schedule Zoom call with Jane Friday 3–4pm” AI Agent with Scheduling Instructions The message is handed off to a Langchain-powered AI Agent that: Parses the message Resolves relative time (like "next Tuesday") into actual ISO timestamps Generates a title (summary) if not provided by the user Ensures all required fields are correctly filled Handles vague messages by asking a single clarifying question LLM (OpenAI) The agent is powered by gpt-4o-mini (or your preferred OpenAI model). You can customize this or swap it out. Google Calendar Integration Once the AI agent has structured the event details, it uses the Google Calendar Tool Node to create the event via your connected Google account. (Optional) A response node (Respond to Chat) is included (but currently disabled) — you can enable it to send a confirmation message back to the user like: “📅 Booked: Lunch with John on Aug 30 at 12:30 PM Asia/Manila.” Requirements To make this workflow functional, you need to connect: 🔐 Google Calendar OAuth2 credentials Add your Google account under Credentials > Google Calendar OAuth2 API. 🧠 OpenAI credentials Provide your OpenAI API key (used for message interpretation and slot filling). Customization Ideas Add email collection to invite attendees Expand to support recurring events Add error handling or fallback if date parsing fails Connect to Slack or Telegram for real-time event booking Important Note on Credentials This template does not include any personal API keys or credential tokens. You’ll need to connect your own Google and OpenAI credentials after import.
by Max Mitcham
The Blog Agent Description An intelligent content automation system that manages the complete blog content lifecycle, from strategic planning to publish-ready articles. It combines AI-powered research, SEO-optimized writing, and strategic content management to execute a pillar/cluster content strategy that establishes thought leadership and drives organic search performance. Overview This automation workflow orchestrates a multi-agent system to continuously produce high-quality blog content for Trigify.io. It intelligently manages content strategy, conducts focused research, and generates complete, SEO-optimized blog posts that follow best practices for both traditional search engines and AI-powered search platforms. The system maintains state across multiple content projects, tracks completion status, and ensures consistent brand positioning throughout all content. 🔄 Workflow Process 1. Schedule Trigger Automated content pipeline activation Runs weekly on Mondays, Tuesdays, and Wednesdays Triggers the content lifecycle management process Ensures consistent content production cadence Can also be manually triggered via chat interface 2. Blog Status Manager Agent Strategic content lifecycle orchestration Queries Linear API to retrieve all previously written blog posts Cross-references completed blogs with Google Sheets strategy state Updates blog statuses from PLANNED to DRAFT_CREATED when content exists in Linear Identifies next priority blog topic from existing pillar/cluster strategy Selects topics marked as PLANNED for content creation When all current content is complete, analyzes SEO Report to identify new high-priority pillars Creates new pillar/cluster strategies based on SEO opportunities Updates Google Sheets with new content plans and status changes Passes selected blog topic to Researcher Agent with clear instructions 3. Google Sheets Integration Centralized content strategy management Strategy_State Sheet**: Tracks current pillar, cluster statuses, and progress SEO Report Sheet**: Contains comprehensive SEO analysis and keyword opportunities Maintains real-time state of content pipeline Stores pillar/cluster relationships and completion tracking Enables data-driven content prioritization 4. Researcher Agent Fast, focused content research Receives blog topic from Blog Status Manager Agent Conducts efficient research using FireCrawl MCP (maximum 2 calls) Gathers competitor information and market statistics Creates comprehensive blog briefs with structured outlines Defines content type (PILLAR or CLUSTER) and word count targets Specifies metadata requirements (title ≤60 chars, description ≤160 chars) Identifies image requirements with source URLs Documents key data points and sources for attribution Plans internal linking strategy Defines Trigify positioning angle and CTA Outputs structured brief for Blog Writer Agent 5. Blog Writer Agent Complete, publish-ready content generation Receives comprehensive blog brief from Researcher Agent Conducts additional research using FireCrawl MCP tools Writes complete blog posts following pillar/cluster structure: Pillar Posts: 2,000-3,000+ words, resource hub style Cluster Posts: 800-1,500 words, focused deep-dives Implements SEO optimization: Creates metadata within strict character limits Implements strategic internal linking Positions Trigify as the primary solution Uses target keywords naturally throughout content Ensures brand consistency: Avoids em dashes (uses parentheses, commas, colons) Provides real source URLs (never temporary screenshot links) Includes proper image instructions with public source URLs Maintains Trigify-first positioning Generates complete, publish-ready articles (not summaries) Formats content with proper markdown structure Creates Linear issue with full blog post content 6. FireCrawl MCP Integration Web scraping and research capabilities Enables web scraping for competitor research Gathers pricing information and product details Collects statistics and market data Provides source URLs for proper attribution Supports image source identification 7. Linear Integration Content management and tracking Queries existing Linear issues to track completed blogs Creates new Linear issues with complete blog post content Stores full articles (not summaries) for editorial review Maintains content library and prevents duplicate creation Enables team collaboration and content review 8. Multi-Model AI Architecture Optimized AI model selection Claude Sonnet 4.5**: Primary model for Blog Writer Agent (with thinking enabled) Claude Opus 4.5**: Research and analysis tasks GPT-5**: Secondary model option for content generation Anthropic Chat Models**: Strategic planning and research Models configured with appropriate token limits and reasoning budgets 🛠️ Technology Stack n8n**: Workflow orchestration and automation platform Claude Sonnet 4.5**: Primary AI model for content generation Claude Opus 4.5**: Research and strategic analysis GPT-5**: Alternative content generation model FireCrawl MCP**: Web scraping and research tool Google Sheets API**: Content strategy and state management Linear API**: Content tracking and issue management LangChain Agents**: Multi-agent orchestration framework ✨ Key Features Automated Content Lifecycle Management**: Tracks content from planning to completion Pillar/Cluster SEO Strategy**: Implements proven content architecture for search performance Multi-Agent AI System**: Specialized agents for research, writing, and management State Management**: Maintains content strategy state across multiple runs SEO Optimization**: Creates metadata, internal links, and keyword-optimized content Brand Consistency**: Ensures Trigify positioning and brand voice throughout Quality Control**: Prevents duplicate content and maintains high standards Research Efficiency**: Limits research calls to maintain speed and cost-effectiveness Source Attribution**: Properly documents sources and image requirements Publish-Ready Output**: Generates complete articles, not summaries or outlines 🎯 Ideal Use Cases Perfect for organizations seeking systematic, scalable content creation: B2B SaaS Companies** building thought leadership through content Marketing Teams** executing pillar/cluster SEO strategies Content Teams** needing consistent, high-quality blog production SEO-Focused Organizations** optimizing for search performance Companies** requiring brand-consistent content at scale Teams** managing multiple content projects simultaneously Organizations** wanting to automate content research and writing Businesses** tracking content performance and strategy execution 📈 Business Impact Transform content creation from manual process to automated system: Consistent Content Production**: Weekly automated content creation SEO Performance**: Pillar/cluster architecture improves search rankings Time Efficiency**: Automates research, writing, and content management Brand Consistency**: Ensures Trigify positioning across all content Scalability**: Manages multiple content projects simultaneously Quality Assurance**: Prevents duplicates and maintains content standards Strategic Alignment**: Data-driven content prioritization from SEO reports Team Collaboration**: Integrates with Linear for editorial workflow This workflow ensures every blog post is strategically planned, thoroughly researched, SEO-optimized, and ready for publication, creating a sustainable system for thought leadership content that drives organic growth.
by Yaron Been
CPO Agent with Product Team Description Streamline product development with an AI-powered Chief Product Officer (CPO) agent orchestrating specialized product team members for comprehensive product strategy and execution. Overview This n8n workflow creates a comprehensive product development department using AI agents. The CPO agent analyzes product opportunities and delegates tasks to specialized agents for product management, UX design, user research, analytics, documentation, and strategic planning. Features Strategic CPO agent using OpenAI O3 for complex product strategy and decision-making Six specialized product agents powered by GPT-4.1-mini for efficient execution Complete product lifecycle coverage from ideation to launch Automated user research and persona development UX/UI design specifications and wireframing Product analytics and KPI tracking Technical documentation and API specifications Team Structure CPO Agent**: Product vision and strategy coordination (O3 model) Product Manager**: Roadmaps, feature specifications, user stories, planning UX/UI Designer**: User flows, wireframes, interface design, usability User Research Specialist**: Research plans, personas, market analysis, insights Product Analytics Specialist**: Metrics, KPIs, A/B testing, data analysis Technical Writer**: Product documentation, API docs, user guides Product Strategy Analyst**: Competitive analysis, market positioning, GTM strategy How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send product requests via chat (e.g., "Design a new mobile app feature for user onboarding") The CPO will analyze and delegate to appropriate specialists Receive comprehensive product deliverables and strategic insights Use Cases Feature Development**: Concept → Research → Design → Specifications → Metrics Product Launch**: Strategy → Documentation → Analytics → Go-to-market planning User Experience Optimization**: Research → Personas → User flows → Testing → Iteration Competitive Analysis**: Market research → Positioning → Differentiation strategies Product Roadmapping**: Vision → Priorities → Timeline → Resource planning Documentation Suite**: User guides → API documentation → Technical specifications Analytics Implementation**: KPI definition → Tracking setup → Performance analysis Market Research**: Customer interviews → Persona development → Requirements gathering Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CPO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with product management tools (Jira, Figma, etc.) Cost Optimization O3 model used only for strategic CPO decisions GPT-4.1-mini provides 90% cost reduction for specialist tasks Parallel processing enables simultaneous agent execution Template library leverages proven product frameworks Integration Options Connect to product management tools (Jira, Asana, Linear) Integrate with design platforms (Figma, Sketch, Adobe XD) Link to analytics tools (Mixpanel, Amplitude, Google Analytics) Export to documentation platforms (Notion, Confluence) Performance Metrics Feature adoption rates and user engagement Product-market fit indicators User satisfaction and NPS scores Development velocity and cycle times Documentation completeness and clarity Contact & Resources Website**: nofluff.online YouTube**: @YaronBeen LinkedIn**: Yaron Been Tags #ProductManagement #UXDesign #UserResearch #ProductStrategy #ProductOps #ProductAnalytics #TechnicalWriting #ProductDevelopment #FeatureDesign #ProductAI #n8n #OpenAI #MultiAgentSystem #ProductTech #ProductLeadership #Innovation
by Einar César Santos
This workflow solves a critical problem in AI chat implementations: handling multiple rapid messages naturally without creating processing bottlenecks. Unlike traditional approaches where every user waits in the same queue, our solution implements intelligent conditional buffering that allows each conversation to flow independently. Key Features: Aggregates rapid user messages (like when someone types multiple lines quickly) into single context Only the first message in a burst waits - subsequent messages skip the queue entirely Each user session operates independently with isolated Redis queues Reduces LLM API calls by 45% through intelligent message batching Maintains conversation memory for contextual responses Perfect for: Customer service bots, AI assistants, support systems, and any chat application where users naturally send multiple messages in quick succession. The workflow scales linearly with users, handling hundreds of concurrent conversations without performance degradation. Some Use Cases: Customer support systems handling multiple concurrent conversations AI assistants that need to understand complete user thoughts before responding Educational chatbots where students ask multi-part questions Sales bots that need to capture complete customer inquiries Internal company AI agents processing complex employee requests Any scenario where users naturally communicate in message bursts Why This Template? Most chat buffer implementations force all users to wait in a single queue, creating exponential delays as usage scales. This template revolutionizes the approach by making only the first message wait while subsequent messages flow through immediately. The result? Natural conversations that scale effortlessly from one to hundreds of users without compromising response quality or speed. Prerequisites n8n instance (v1.0.0 or higher) Redis database connection OpenAI API key (or alternative LLM provider) Basic understanding of webhook configuration Tags ai-chat, redis, buffer, scalable, conversation, langchain, openai, message-aggregation, customer-service, chatbot
by BizThrive.ai
📄 Description This workflow automates the extraction of structured invoice data from PDF files sent via Telegram and stores it in Airtable. It leverages GPT-4o for intelligent parsing and includes conversational memory for a seamless user experience. Designed for businesses and freelancers who receive invoices digitally and want to streamline their record-keeping. ⚙️ How It Works Telegram Trigger – Listens for incoming messages and PDF attachments. Switch Node – Filters messages to ensure only PDFs are processed. Extract from File – Parses the PDF content for text extraction. Edit Fields – Prepares the extracted data for AI processing. AI Agent (GPT-4o) – Orchestrates the workflow, prompts the user for missing info, and extracts structured data. Simple Memory – Maintains conversational context across sessions. Create Invoice (Airtable Tool) – Creates a new invoice record in Airtable. Create Line Item (Airtable Tool) – Adds individual line items linked to the invoice. Telegram Response – Sends confirmation back to the user. 🔐 Required Credentials To run this workflow successfully, you’ll need: Telegram Bot Token** (via @BotFather) OpenAI API Key** (with GPT-4o access) Airtable API Key** and access to: Base: Invoice Tracker Proper Tables: Invoices and Line Items 🧰 Airtable Structure Invoices Table Fields: Invoice Number Date Supplier Supplier Address Tax ID PO Number Due Date Receiver Name Receiver Address Delivery Date Total Tax Total Amount Line Items Table Fields: Product Code Description Unit Price Quantity Unit Type Sub Total Invoice (linked) 🧠 Features AI-powered invoice parsing PDF text extraction Airtable record creation with relational linking Telegram-based user interaction Conversational memory Error handling and data validation
by Le Nguyen
How it works Fetch campaign & members from Salesforce. GPT‑4 auto‑writes a channel‑appropriate, personalised outbound message. Switch node sends via Twilio (SMS/WhatsApp), SMTP (Email). Mark each member as processed to avoid double‑touches. Error trigger notifies Slack if anything fails. Set‑up steps Time: ~10‑15 min once credentials are ready. Prereqs: Active Salesforce OAuth app, Twilio account, SMTP creds, Slack app. In‑flow sticky notes walk you through credential mapping, environment variables, and optional tweaks (e.g., campaign SOQL filter). > Copy the workflow, add your keys, and run a quick manual test—after that you can place it on a cron or Salesforce trigger.