Automated YouTube Chapter Generation and Description Update - n8n Workflow

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This robust n8n workflow solves the tedious problem of manually writing chapter timestamps for new YouTube videos. By leveraging the channel's RSS feed as a reliable n8n trigger, the system automatically detects new uploads. It utilizes Airtable for effective deduplication, ensuring the processing only runs once per video, making it a highly reliable n8n workflow. The core intelligence relies on fetching the detailed video transcript via the SupaData API. This transcript is then passed to an OpenAI large language model (LLM) through an n8n node to intelligently parse and format the chapter markers into YouTube-compliant timestamps. Finally, a dedicated YouTube n8n node updates the video description, appending the generated chapters for improved viewer experience and SEO effectiveness. This specific n8n template is a powerful demonstration of how low-code automation can enhance content workflows.

1. Trigger Detection: The process starts with the Get New YouTube Video n8n trigger, which constantly monitors your YouTube channel's RSS feed for a new upload.


2. Deduplication Check: The workflow immediately uses the Check Airtable n8n node to see if the video ID already exists in a tracking base. This crucial step prevents the n8n workflow from running redundantly on previously processed content.


3. Data Tracking & Prep: If the video is new, it is immediately logged using the Save to Airtable n8n node. The Format Video ID node then prepares the necessary video ID for API calls.


4. Transcript Retrieval: The Fetch Transcript HTTP Request n8n node securely calls the SupaData API, retrieving the complete video transcript using the video ID passed in the URL.


5. Custom Data Processing: The Prepare Transcript + Duration Code n8n node processes the raw JSON transcript. It converts millisecond offsets into clean minute:second timestamps, compiling a single formattedTranscript string suitable for AI ingestion, and calculating the video's total duration.


6. AI Chapter Generation: The AI: Generate Chapters LangChain n8n node submits the prepared transcript and duration to the connected OpenAI Chat Model (GPT-4o). The prompt strictly guides the AI to output only a list of YouTube-style chapter timestamps starting at 00:00.


7. YouTube Description Update: The final stages use the YouTube n8n node. First, it fetches the video's existing description. Then, the Update Description n8n node appends the AI-generated chapters to the end of the existing description and publishes the update back to YouTube, completing the n8n workflow.

1. Importing the n8n workflow: Download the provided JSON file and import it directly into your n8n instance using the 'New' > 'Import from JSON' option.


2. Credential Configuration: This n8n workflow requires setup for four different credentials:

1. RSS Trigger Setup: Update the Get New YouTube Video n8n trigger. Change the default feedUrl parameter to your specific YouTube channel RSS feed URL (e.g., https://www.youtube.com/feeds/videos.xml?channelid=YOURCHANNEL_ID).


2. Airtable Base Configuration: Verify that the Base ID and Table ID in the Airtable n8n node settings match the Airtable base you use for video tracking.

Get New YouTube Video (RSS Feed Read Trigger): This serves as the primary n8n trigger, polling the channel's RSS feed to start the n8n workflow whenever a new video is published.
Check Airtable / Save to Airtable (Airtable n8n node): These nodes manage the state of the n8n workflow, using a search operation to check for existing video IDs and a create operation to save new ones, ensuring effective deduplication.
Fetch Transcript (HTTP Request n8n node): Connects to the SupaData transcript API. It is configured with generic HTTP Header Authentication to securely pass the required API key for data retrieval.
Prepare Transcript + Duration (Code n8n node): A powerful custom JavaScript n8n node that transforms the raw transcript JSON into a clean, annotated text string, ready for input into the AI model.
AI: Generate Chapters (LangChain Agent n8n node): This crucial n8n node uses a detailed system prompt to instruct the connected OpenAI Chat Model. It performs the complex task of structuring the raw transcript into chapter timestamps (00:00, 01:10, etc.).
Update Description (YouTube n8n node): The final action node in the n8n workflow. It combines the original video description with the AI-generated chapters and submits the final text back to YouTube's API to update the video description.