Structured Output Parser Workflows
233 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
Transcribe and analyze sales meetings with Deepgram, Gemini, GHL, Slack & Gmail
Quick overview Youtube Video: https://youtu.be/GNAplBWdCDE?si=TjojVTZX7ViiRUiG This workflow receives meeting voice recording via webhook, transcribes it with Deepgram, and uses Gemini to extract client details and next-step tasks. It then updates GoHighLevel, posts a task summary to Slack, emails the client their action items via Gmail, and logs the meeting to Sheets. How it works Receives a POST webhook request containing a meeting ID, attendee email, meeting date/time, and an audio file. Looks up the contact in GoHighLevel by email and creates/updates the contact if it does not already exist. Checks Google Sheets for the meeting ID and only continues if no existing row is found. Sends the audio binary to Deepgram to transcribe the recording with speaker diarization and utterances enabled. Formats the transcript and sends it to a Google Gemini–powered agent that returns structured JSON with client identification and task lists. Creates a GoHighLevel task with the extracted service-provider tasks, posts the task summary to Slack, and emails the client their tasks via Gmail. Appends the meeting details, extracted company name, and action items to Google Sheets and returns a webhook
WDiscover and score engineering candidates with Groq, GitHub, LinkedIn, Stack Overflow, HN and Supabase
Quick Overview This workflow exposes a POST webhook that turns a job description into a structured hiring brief using Groq, searches candidates across GitHub, LinkedIn (via Apify), Stack Overflow, and Hacker News, scores and summarizes the shortlist, optionally saves results to Supabase, and returns a JSON response. How it works Receives a candidate search request via a POST webhook and normalizes the payload into a consistent schema. Validates that the request includes a job description or structured criteria, and returns a 400 JSON error if it is invalid. Uses Groq (via LangChain) to extract structured job requirements, then builds a search brief with queries and limits for each source. Searches GitHub, LinkedIn via Apify, Stack Overflow, and Hacker News in parallel and normalizes each source’s results into a common candidate format. Merges all candidates, sanitizes and deduplicates the pool, and returns an empty 200 response if no candidates remain. Scores candidates with a deterministic evidence formula, filters by the configured score threshold, and builds a recruiter-facing JSON report. Uses Groq (via LangChain) to generate an AI shortlist summary, attaches it to the report,
Draft Gmail reply drafts automatically with Google Gemini
Quick overview This workflow watches for new Gmail messages, uses Google Gemini to draft a concise reply based on the email content, and saves the response as a Gmail draft in the original thread for you to review before sending. How it works Triggers every minute when a new email is received in Gmail. Sends the email subject, sender, and snippet to Google Gemini with instructions to write a professional reply under 100 words matching the sender’s tone. Creates a Gmail draft containing the generated reply and sets the subject to “Re:” while attaching it to the original email thread. Setup Connect a Gmail OAuth2 credential and ensure the trigger has access to the inbox you want to monitor. Add a Google Gemini (PaLM) API credential for the Gemini chat model. Review the reply prompt and the Gmail trigger polling interval, then activate the workflow. No additional setup is required the workflow is ready to run as soon as both credentials are connected.
Track expenses from phone notifications with Google Gemini and Google Sheets
Quick overview This workflow receives phone push notification through FlowTrigger mobile app, extracts the transaction amount and date, uses Google Gemini to categorize the expense and adds it to a Google Sheets transactions log. How it works Receives a POST webhook request containing a captured notification payload from FlowTrigger mobile app. Parses the notification data and skips the flow if no amount is detected in the notification payload. Sends the notification title and body to Google Gemini and parses a structured response with cleaned merchant name, expense category, reasoning, and ISO currency code. Appends the date, amount, category, currency, and merchant to a selected Google Sheets tab. Returns a success response with the saved fields, or an error response if the AI categorization or Google Sheets write fails. Setup Create and connect a Google Gemini API key credential for the Google Gemini Chat Model. Create and connect a Google Sheets OAuth2 credential, then set the Google Sheets Document ID and Sheet Tab Name in the Google Sheets append step. Activate the workflow, copy the Webhook production URL from the Webhook trigger, and paste it into FlowTrigger’s Notification
Qualify Product Hunt leads with Google Gemini, Apify, and Google Sheets
Quick overview Youtube Video: https://youtu.be/h47YeiivZvs?si=V-S1X-ME5V24Tuch This workflow runs daily to pull the latest Product Hunt posts, qualifies them with Google Gemini, scrapes ICP-matching product websites with Apify to find emails, then writes the lead data to Google Sheets and creates contacts in GoHighLevel. How it works Runs every day on a schedule trigger. Queries the Product Hunt GraphQL API for the latest posts and iterates through each result. Resolves each product’s website redirect target, extracts a clean domain, and filters out blocked domains like app stores, social networks, and link aggregators. Sends the product name, tagline, and description to a Google Gemini–powered agent to score ICP fit and keeps only matches. Uses Apify to crawl each matched website and extract email addresses from the site content. Groups scraped results by domain, keeps only products with at least one email, and appends or updates a matching row in Google Sheets. Creates a GoHighLevel contact using the first email and stores any additional emails in a custom field. Setup Add Product Hunt OAuth2 credentials and ensure the GraphQL query in the Product Hunt request returns the fields
Enrich and route inbound leads using You.com, Groq, Notion, and Slack
Quick overview This workflow receives inbound lead details via webhook, enriches the company using You.com search and website content extraction, generates a one-page profile and fit score with Groq, then routes hot leads to Slack, logs all leads to Notion, and returns the enriched result in the webhook response. How it works Receives a POST webhook request containing a company name and/or domain and normalizes the input into consistent fields. Rejects the request with a 400 response if neither a company name nor a domain is provided. Uses You.com Web Search to gather recent company signals (for example funding, news, and leadership changes) and resolves a best-guess company URL. Uses You.com Content Extraction to pull website content and combines the search signals and site content into a single enrichment context. Uses Groq (Llama 3.3 70B) to generate a concise one-page company profile and then scores the lead against the defined fit criteria with structured output. If the fit score meets or exceeds the hot-lead threshold, posts an alert message to a selected Slack channel with an @mention. Logs the lead, fit score, tier, and profile summary to a Notion database and returns the f
Grade system prompts in Google Sheets with a Gemini LLM judge
Quick overview This workflow manually grades a system prompt by running it against a sample user task with Google Gemini, then has a second Gemini judge score the prompt (1–10) and write the grade and reason back to Google Sheets. How it works Starts when you run the workflow manually. Reads the prompt list from a Google Sheets spreadsheet and keeps only the last row as the system prompt under test. Sets a fixed sample customer-support task and sends it to a Google Gemini-powered agent using the sheet prompt as its system instructions. Sends the original prompt, the sample task, and the agent’s response to a second Google Gemini judge that returns a structured grade and short justification. Updates the same Google Sheets row with the returned grade and reason. Setup Connect a Google Sheets OAuth2 credential with access to the target spreadsheet. Connect a Google AI Studio (Gemini) credential for the candidate model, grader model, and parser-fixer model. Ensure your sheet has columns for at least prompt, grade, and reason, and that the workflow can match rows using the row_number field. Update the spreadsheet ID/sheet and edit the sample task text if you want to test prompts against
Extract ecommerce product data with Google Sheets, ScrapingBee and Gemini
Quick Overview This workflow manually runs to read a list of webpage URLs from Google Sheets, scrape each page with ScrapingBee, and use Google Gemini to extract structured product data from screenshots with an HTML fallback, then append the results back into a Google Sheets sheet. How it works Runs when you manually trigger the workflow. Reads the list of URLs to scrape from a Google Sheets spreadsheet. Fetches a full-page screenshot for each URL using the ScrapingBee API. Sends the screenshot (and the URL for context) to a Google Gemini model to extract product details into a structured JSON format, calling a ScrapingBee HTML fetch tool when screenshot extraction is incomplete. Converts any fetched HTML to Markdown and returns it to the Gemini agent to complete the extraction. Splits the extracted product array into individual items and appends them as new rows in the Google Sheets “Results” sheet. Setup Create a Google Sheets service account connection in n8n and set the target spreadsheet and the “List of URLs” and “Results” sheet selections. Add a Google Gemini (PaLM) API credential in n8n and ensure the selected model (gemini-1.5-pro-latest) is available for your account. Add
CQualify LinkedIn leads and draft multi-step outreach with Airtable, Apify and Claude
Quick overview This workflow pulls unprocessed leads from Airtable, enriches them with LinkedIn profile, company, and post data via Apify, optionally scrapes the company website with Firecrawl, then uses Anthropic Claude to qualify leads and draft multi-step LinkedIn outreach messages, saving results back to Airtable. How it works Runs when you manually execute the workflow. Reads qualification and writing prompts from Airtable, then searches Airtable for leads where the “Réponse” and “Match” fields are empty. Iterates through each lead and uses Apify to fetch LinkedIn profile details, marking the Airtable record as “Likedin pas dispo” when the profile cannot be retrieved. For available profiles, uses Apify to fetch company details when a company LinkedIn URL exists and, if a website is available, uses Firecrawl to scrape the homepage and clean the returned markdown. Uses Apify to fetch recent LinkedIn posts for the lead and selects a relevant recent personal post URL to include in the enrichment dataset. Sends the consolidated lead, company, homepage, and post data to Anthropic Claude to decide whether the lead matches the qualification criteria, marking non-matching leads as “Fal
Score leads and send WhatsApp proposals with Gemini, HighLevel and Redis
Quick Overview This workflow captures new leads via webhook, enriches them with Apify-powered Google AI search, scores them using Google Gemini, and updates HighLevel CRM while sending WhatsApp template messages; it also handles inbound WhatsApp support with a Gemini-driven agent that uses Redis memory, updates HighLevel, and notifies a team via Telegram. How it works Receives new lead details through an HTTP webhook. Normalizes the lead fields and uses Apify (Google AI Mode search) to fetch a public professional background overview for the lead. Sends the enriched lead context to Google Gemini to produce a structured lead score, rationale, recommendation, and next steps. Routes the lead based on the score threshold and upserts the contact in HighLevel with the AI scoring details stored in custom fields. Creates a HighLevel opportunity, sends a WhatsApp template message to the lead, and updates the opportunity’s pipeline/stage fields. Triggers on incoming WhatsApp messages, looks up the sender in HighLevel, fetches related opportunities, and hands the conversation to a Google Gemini agent with Redis chat history. Uses the agent’s decisions to save requirement notes and update/close
Generate client-ready workflow diagrams from sales call transcripts with Claude
Who it's for This workflow is for automation agencies and n8n consultants who conduct discovery calls with prospects and want to instantly turn conversation transcripts into polished, client-ready workflow diagrams — without manual canvas work. How it works A consultant pastes a sales call transcript into a form trigger. A first AI agent (Claude) parses the transcript and extracts structured workflow briefs — one per identified business process — with titles, tools, logic, and step-by-step descriptions. A code node splits the output into individual workflow items, one per identified process. A second AI agent generates a complete n8n workflow JSON for each brief, using French business-oriented node names and proper canvas positioning. A code node validates and parses the generated JSON to ensure structural integrity. A third AI agent clusters nodes into logical business groups and generates canvas layout coordinates and sticky note annotations. A fourth AI agent renames all nodes with clear, descriptive French labels following a consistent naming convention. All renames and layout changes are applied, and the finalized workflow is published directly to an n8n instance via the API.
Automate employee onboarding with Groq, Gmail, Slack and Google Workspace
How it works New hire submits an onboarding form with their details Groq AI generates personalised welcome content, Slack messages, and IT access request Welcome email sent to the new hire via Gmail Automated emails sent to HR, the manager, and IT team Company Policy and Employee Handbook PDFs downloaded from Drive and attached Slack messages posted to #general and #hr-team channels Onboarding record appended to Google Sheets tracker Set up steps Estimated time: ~15 minutes Connect Groq API, Gmail, Slack, Google Drive, and Google Sheets credentials Upload your Policy and Handbook PDFs to Drive and link them in the Download nodes Select your Slack channels in the two Slack nodes Select your onboarding Google Sheet in the Append row node Activate the workflow and share the form link with new hires
Classify LinkedIn posts as quality or slop with OpenAI and Qdrant
Purpose This workflow is the official backend for the StopSlopIn Chrome extension – it classifies LinkedIn posts as quality or slop using a strict LLM quality gate and learns from user votes over time via a Qdrant vector store. What this is for This runs the webhook that powers the StopSlopIn Chrome extension on the Chrome Web Store. The extension sends LinkedIn posts here for analysis and user votes here for training – everything stays on your own n8n instance. Setup Add your OpenAI credentials to the chat model and embeddings nodes Add your Qdrant credentials to both vector store nodes, pointing to a collection named stopslopin Activate the workflow, copy the webhook URL, and paste it into the StopSlopIn Chrome extension settings Follow the instructions on the yellow sticky notes for anything else How it works A single webhook exposes two actions, selected via a ?action= query parameter: analyze for classification, vote for training. A Switch node routes incoming requests based on the action parameter On analyze: each post is enriched with similar prior-rated posts pulled from Qdrant (RAG), batched together, and sent to the LLM with a strict quality-gate system prompt The LLM ret
Audit multi-page CRO with GPT-4o-mini, Google Sheets, and Gmail alerts
Description Submit up to 3 landing page URLs using a simple form and the workflow audits each one automatically. For every page, GPT-4o-mini scrapes the content, scores it across five dimensions, identifies the top conversion issue, and generates five specific page fixes. Every result is logged to Google Sheets and pages that score below your alert threshold trigger an automatic Gmail alert with the full breakdown. Built for marketing managers, agency owners, and growth teams who need structured, repeatable conversion audits without spending hours reviewing pages manually. What This Workflow Does Scrapes and cleans each page automatically** — Fetches the raw HTML for every URL submitted, strips all scripts and styles, and prepares clean text for AI analysis Scores pages across five CRO dimensions** — GPT-4o-mini rates each page on overall conversion potential, CTA strength, trust score, and message clarity on a 1–10 scale Generates a letter grade per page** — Assigns A+ through F based on the overall score so you can rank pages at a glance Produces five page-specific fixes** — Every fix references actual content from the page and is scoped to be doable within 1–2 days — no generic
Route and triage support tickets with Claude Sonnet and your CRM
Overview This workflow automates customer support ticket processing using AI-powered analysis, classification, and intelligent routing. It processes incoming tickets from email or webhook, translates messages when needed, analyzes sentiment and urgency, and routes tickets to auto-reply or escalation flows. The system also updates CRM platforms and logs observability metrics for monitoring. This enables faster response times, improved customer experience, and scalable support operations. How It Works Input Sources Receives tickets via: IMAP Email Trigger Webhook endpoint Workflow Configuration Defines: CRM/Helpdesk API endpoint Escalation webhook URL Observability logging endpoint Data Cleaning & Normalization Extracts and cleans HTML content Normalizes ticket data: Ticket ID User email Message content Timestamp Source channel Language Detection & Translation Detects the original language Translates message into English if needed Returns confidence score AI Support Intelligence Classifies ticket into: Sentiment (positive/neutral/negative) Urgency (low → critical) Category (billing, bug, technical, etc.) Generates: Short summary Churn risk score (0–1) Recommended action path Decision
SOrchestrate credit onboarding checks with GPT-4o, Airtable, Gmail and Slack
How It Works This workflow automates credit operations onboarding by running KYC verification, credit bureau checks, identity validation, and sanctions screening through a single AI-powered agent. Built for credit operations teams, compliance officers, and fintech platforms, it eliminates manual eligibility reviews that are slow and error-prone. Triggered via webhook, the Credit Operations Agent orchestrates all verification tools simultaneously, then routes customers by eligibility status, eligible, ineligible, pending documentation, or compliance escalation. Each path prepares structured data stored in Airtable, triggers appropriate follow-up actions (email, Slack alerts), and logs a full audit trail. A final formatted response is returned to the originating system, closing the loop end-to-end with no manual handoffs. Setup Steps Set webhook URL and connect Credit Operations webhook node to your intake system. Add OpenAI API key to the OpenAI Chat Model node. Configure KYC, Credit Bureau, Identity, and Sanctions tool credentials. Add Gmail OAuth2 and Slack bot token for notification nodes. Connect Airtable API key; set base/table IDs for eligible and ineligible customer stores. P
Monitor and optimize carbon emissions for ESG reporting with GPT-4o, Slack and Sheets
How It Works This workflow automates end-to-end carbon emissions monitoring, strategy optimisation, and ESG reporting using a multi-agent AI supervisor architecture in n8n. Designed for sustainability managers, ESG teams, and operations leads, it eliminates the manual effort of tracking emissions, evaluating reduction strategies, and producing compliance reports. Data enters via scheduled pulls and real-time webhooks, then merges into a unified feed processed by a Carbon Supervisor Agent. Sub-agents handle monitoring, optimisation, policy enforcement, and ESG reporting. Approved strategies are auto-executed or routed for human sign-off. Outputs are consolidated and pushed to Slack, Google Sheets, and email, keeping all stakeholders informed. The workflow closes the loop from raw sensor data to actionable ESG dashboards with minimal human intervention. Setup Steps Connect scheduled trigger and webhook nodes to your emissions data sources. Add credentials for Slack (bot token), Gmail (OAuth2), and Google Sheets (service account). Configure the Carbon Supervisor Agent with your preferred LLM (OpenAI or compatible). Set approval thresholds in the Check Approval Required node. Map Googl
Monitor and optimize carbon emissions for ESG with GPT‑4o, Slack and Google Sheets
How It Works This workflow automates end-to-end carbon emissions monitoring, strategy optimisation, and ESG reporting using a multi-agent AI supervisor architecture in n8n. Designed for sustainability managers, ESG teams, and operations leads, it eliminates the manual effort of tracking emissions, evaluating reduction strategies, and producing compliance reports. Data enters via scheduled pulls and real-time webhooks, then merges into a unified feed processed by a Carbon Supervisor Agent. Sub-agents handle monitoring, optimisation, policy enforcement, and ESG reporting. Approved strategies are auto-executed or routed for human sign-off. Outputs are consolidated and pushed to Slack, Google Sheets, and email, keeping all stakeholders informed. The workflow closes the loop from raw sensor data to actionable ESG dashboards with minimal human intervention. Setup Steps Connect scheduled trigger and webhook nodes to your emissions data sources. Add credentials for Slack (bot token), Gmail (OAuth2), and Google Sheets (service account). Configure the Carbon Supervisor Agent with your preferred LLM (OpenAI or compatible). Set approval thresholds in the Check Approval Required node. Map Googl
Generate M&A due diligence PDF reports with LlamaIndex, OpenAI, Pinecone, and S3
Streamline M&A due diligence with AI. This n8n workflow automatically parses financial documents using LlamaIndex, embeds data into Pinecone, and generates comprehensive, AI-driven reports with GPT-5-mini, saving hours of manual review and ensuring consistent, data-backed insights. Why Use This Workflow? Time Savings: Reduces manual document review and report generation from days to minutes. Cost Reduction: Minimizes reliance on expensive human analysts for initial data extraction and summary. Error Prevention: AI-driven analysis ensures consistent data extraction, reducing human error and oversight. Scalability: Effortlessly processes multiple documents and deals in parallel, scaling with your business needs. Ideal For Investment Analysts & Private Equity Firms:** Quickly evaluate target companies by automating the extraction of key financials, risks, and business models from deal documents. M&A Advisors:** Conduct preliminary due diligence efficiently, generating comprehensive overview reports for clients without extensive manual effort. Financial Professionals:** Accelerate research and analysis of company filings, investor presentations, and market reports for critical decision
Discover buying-intent leads on Twitter and Instagram with GPT-4o-mini and send summaries to Slack and Notion
📊 Description Automate B2B lead discovery by identifying high-intent prospects directly from Reddit discussions using AI-powered intent analysis. 🎯🤖 This workflow scans Reddit for conversations related to CRM and marketing automation tools, analyzes snippets to detect buying intent, identifies relevant decision-makers on LinkedIn, enriches contact details via RocketReach, and logs qualified leads into Google Sheets. Running every three hours, it ensures your sales team never misses fresh outbound opportunities without manual research. 🚀📊 🔁 What This Template Does 1️⃣ Runs automatically every 3 hours to search Reddit for tool-related discussions. ⏰ 2️⃣ Extracts Reddit snippets, links, and highlighted keywords from search results. 🔍 3️⃣ Uses AI to classify buying intent as High, Medium, or Low. 🤖 4️⃣ Identifies the core problem and suggests a safe, non-salesy outreach angle. 💬 5️⃣ Filters only High and Medium intent opportunities. 🚦 6️⃣ Searches LinkedIn for matching decision-makers based on role and seniority. 👥 7️⃣ Enriches lead profiles with emails and company data using RocketReach. 📇 8️⃣ Saves qualified leads into Google Sheets with deduplication logic. 📊 9️⃣ Sends
Automate Gmail Organization with AI-Powered Email Classification and Smart Labeling
📧 AI-Powered Gmail Auto-Labeling with Smart Classification This n8n workflow automatically organizes your Gmail inbox by intelligently categorizing incoming emails and applying custom labels using AI-powered sentiment analysis. Say goodbye to manual email sorting and hello to an organized inbox! Use Cases Business Email Management**: Automatically sort partnership inquiries, meeting requests, and promotional emails Sales Team Automation**: Identify and label cold outreach and high-priority leads Executive Assistants**: Filter important meetings and urgent matters for busy professionals Marketing Teams**: Separate promotional content from genuine business communications Good to Know The workflow runs every minute to check for new emails Each email is processed only once - already labeled emails are automatically skipped Uses OpenAI's GPT model for accurate email classification (API costs apply) Processes emails in batches to handle multiple incoming messages efficiently How It Works Gmail Trigger continuously monitors your inbox for new emails every minute Switch Node checks if emails already have labels (Other, Promotion, or Meeting) to avoid duplicate processing Loop Node process
WAutomate YouTube Content Strategy with AI, Apify & Google Sheets
📌 Overview This advanced multi-phase n8n workflow automates the complete research, analysis, and ideation pipeline for a YouTube strategist. It scrapes competitor channels, analyzes top-performing titles and thumbnails, identifies niche trends, gathers audience sentiment from comments, and produces data-driven content ideas—automatically writing them into a structured Google Sheets dashboard. This system is ideal for: YouTube creators Agencies Content strategists Automation engineers Anyone who wants to generate YouTube content ideas backed by real data 🧠 High‑Level Architecture The workflow is split into 5 phases, each building on the previous: Phase 1 — Niche Outliers (Input: User Form) Scrapes 3 high‑quality channels from your niche, extracts their outlier videos, and analyzes why they work. Phase 2 — Broad Niche Insights (Weekly) Scrapes the top trending content in your broad niche (e.g., "AI", "fitness", "personal finance") and logs weekly insights. Phase 3 — Niche Insights (Daily) Scrapes the top videos in your specific micro‑niche daily to keep track of content momentum. Phase 4 — Comment Analysis Analyzes real comments from your channel to understand what your audience li
WAutomatically Scrape Make.com Job Board with GPT-5-mini Summaries & Email Digest
Automatically Scrape Make.com Job Board with GPT-5-mini Summaries & Email Digest Overview Who is this for? Make.com consultants, automation specialists, and freelancers who want to catch new client opportunities without manually checking the forum. What problem does it solve? Scrolling through forum posts to find jobs wastes time. This automation finds new postings, uses AI to summarize what clients need, and emails you a clean digest. How it works: Runs on schedule → scrapes the Make.com professional services forum → filters jobs from last 7 days → AI summarizes each posting → sends formatted email digest. Use Cases Freelancers: Get daily job alerts without forum browsing, respond to opportunities faster Agencies: Keep sales teams informed of potential clients needing Make.com expertise Job Seekers: Track contract and full-time positions requiring Make.com skills Detailed Workflow Scraping: HTTP module pulls HTML from the Make.com forum job board Parsing: Extracts job titles, dates, authors, and thread links Filtering: Only jobs posted within last 7 days pass through (configurable) AI Processing: GPT-5-mini analyzes each post to extract: Project type Key requirements Complexity le
Create & Upload AI Videos to YouTube with Kling 2.5 & Auto-SEO
++What it is++ An automated workflow for creating Kling 2.5 videos and posting them to YouTube. The workflow is divided into three main phases: Create Kling 2.5 Video Wait for Video Processing Post to YouTube ++Create Kling 2.5 Video++ This phase handles the initial video creation based on user input. Type Prompt: A form trigger allows the user to input details for the video, including: Prompt: A simple scenario for the video. Video Style: (e.g., Dialogue, Monologue, Advertisement, Documentary) Aspect Ratio: (e.g., 16:9, 9:16, 1:1) Videography (AI Refinement): Refines the user’s prompt into a detailed “script-to-screen” format suitable for video generation. FAL.AI Request: The refined prompt is sent to the Fal.ai Kling 2.5 model via an HTTP request to generate the video. Store Data: Details of the video request, including the date requested, the refined prompt, and the request URL, are stored in a Google Sheet. ++Wait for Video Processing++ Wait 5 mins: The workflow pauses for 5 minutes. This waiting period is necessary as it typically takes 3–5 minutes for the video to be ready after the generation request. ++Post to YouTube++ This phase focuses on generating YouTube SEO details a