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Generate Youtube video metadata (timestamps, tags, description, ...)

NasserNasser
31118 views
2/3/2026
TrelloWordPressAutomationContent ManagementPublishing
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For Who?

  • Content Creators
  • Youtube Automation
  • Marketing Team

How it works?

1 - Enter the ID of the YTB channel to trigger the workflow when a new video is posted 2 - Apify scrape the last YTB video of the channel 3 - Wait until the dataset is completed in Apify and get it 4 - Verify if Metadata are not already generated and generate them with LLM 5 - Format all the data created and update YTB Video

📺 YouTube Video Tutorial: Watch on YouTube

SETUP

Setup Input YTB Chanel : Go to the channel's page on YouTube, and look at the URL of the page. The channel ID is the value that comes after channel/ in the URL. Add it after "?channel_id=" You can also use free tools available to retrieve channel ID.

Setup Output YTB Video Update : Connect your YTB account to your n8n instance thanks to the Google Cloud Console. You can find tutorials by typing "youtube api Oauth" on Google.

APIs : For the following third-party integrations, replace ==[YOUR_API_TOKEN]== with your API Token or connect your account via Client ID / Secret to your n8n instance :

👨‍💻 More Workflows : https://n8n.io/creators/nasser/

YouTube Video Metadata Generator

This n8n workflow automates the generation of comprehensive metadata for YouTube videos, including titles, descriptions, timestamps, and tags, by leveraging AI capabilities. It's designed to streamline the content creation process for YouTube creators, ensuring consistent and optimized video metadata.

What it does

This workflow takes an RSS feed as input, likely containing information about new videos or content, and then uses AI to generate various metadata components.

  1. Triggers on new RSS Feed items: The workflow starts by monitoring an RSS feed for new entries. This could be a feed for recently published articles, podcast episodes, or any content that needs to be repurposed for YouTube.
  2. Generates Metadata using AI: For each new item in the RSS feed, the workflow interacts with a Mistral AI Chat Model to generate:
    • A compelling YouTube video title.
    • A detailed video description.
    • Relevant timestamps for the video content.
    • Optimized tags for discoverability.
  3. Parses AI Output: The generated AI output is then parsed using a Structured Output Parser to extract the individual metadata components (title, description, timestamps, tags) into a structured format.
  4. Conditional Logic: An "If" node is included, suggesting potential branching logic based on the AI's output or other conditions, though the specific conditions are not defined in the provided JSON. This allows for flexible handling of different scenarios.
  5. Performs HTTP Request: The workflow includes an HTTP Request node, which could be used to interact with a YouTube API (or another service) to upload or update video metadata.
  6. Includes a Wait step: A "Wait" node is present, which can be used to introduce a delay in the workflow, for example, to respect API rate limits or to allow time for external processes.
  7. No Operation (Placeholder): A "No Operation" node is included, which typically acts as a placeholder or a point where the workflow might end if certain conditions are not met, without performing any further actions.
  8. Includes Code Node: A "Code" node is present, allowing for custom JavaScript logic to be executed. This could be used for advanced data manipulation, formatting, or integration with other services not directly supported by n8n nodes.
  9. YouTube Node: A dedicated YouTube node is included, indicating that the workflow is designed to directly interact with YouTube, likely for publishing or updating video information.

Prerequisites/Requirements

  • n8n Instance: A running n8n instance.
  • Mistral AI Account & API Key: Credentials for the Mistral Cloud Chat Model to generate AI content.
  • YouTube Account & API Credentials: A YouTube account and corresponding API credentials (OAuth 2.0) to interact with the YouTube platform.
  • RSS Feed URL: The URL of the RSS feed you wish to monitor.

Setup/Usage

  1. Import the workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your Mistral AI credentials for the "Mistral Cloud Chat Model" node.
    • Configure your YouTube credentials for the "YouTube" node.
  3. Configure RSS Feed Trigger:
    • In the "RSS Feed Trigger" node, specify the URL of the RSS feed you want to monitor.
  4. Configure AI Prompts:
    • Adjust the prompts within the "Basic LLM Chain" and "Mistral Cloud Chat Model" nodes to guide the AI in generating the desired titles, descriptions, timestamps, and tags based on your specific content and style.
  5. Review and Customize Code Node:
    • If the "Code" node contains custom logic, review and modify it as needed for your specific use case.
  6. Configure HTTP Request (Optional):
    • If the "HTTP Request" node is intended for a specific API call (e.g., YouTube Data API), configure its URL, headers, and body accordingly.
  7. Activate the Workflow: Once configured, activate the workflow. It will automatically trigger when new items appear in your specified RSS feed.

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