This article provides a complete, practical walkthrough of the Splitout Webhook Create Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Extract the Most Engaging Moments from YouTube Videos with n8n: A No-Code Workflow Guide
   
   Meta Description:  
   Learn how to build a no-code automation using n8n to identify the most engaging moments in YouTube videos based on viewer interaction data. This walkthrough shows how to pull, filter, and return replay-intense timestamps using a webhook-triggered workflow.
   
   Keywords:  
   n8n, YouTube API, no-code automation, engaging moments, video intensity, video analysis, YouTube replay markers, Webhook automation, video highlights extractor, YouTube data, low-code workflows, n8n tutorial, HTTP Request node
   
   Third-Party APIs Used:  
   - LemnosLife YouTube API (https://yt.lemnoslife.com/): Used to fetch YouTube video replay intensity data through the "mostReplayed" endpoint.
   
   —
   
   📝 Article:
   
   # Detecting Engaging Moments in YouTube Videos with n8n Automation
   
   In the era of short attention spans and endless video content, pinpointing the most engaging segments in a video can provide massive value—whether you're a content creator, marketer, or developer building media analytics tools. This is where no-code automation platform n8n steps in. With the help of a custom webhook, a few smart filters, and a publicly available API, you can automatically extract and return the most replayed moments from any YouTube video.
   
   In this article, we'll walk you through a clever n8n workflow designed to find "intensity highlights" (moments where viewer engagement spikes) from YouTube content. This workflow retrieves replay markers, filters high-intensity timestamps, and formats them into user-friendly links—perfect for summaries, highlight reels, or content optimization strategies.
   
   ---
   
   ## 👀 What Does This Workflow Do?
   
   This workflow listens via a Webhook for a YouTube video ID, fetches replay intensity data via API, filters for high-engagement moments, removes duplicates (close timestamps), and returns clean, clickable highlight links—effortlessly.
   
   Here’s an overview of the key steps:
   
   1. Receive a YouTube video ID via Webhook
   2. Query the LemnosLife YouTube data API for replay intensity markers
   3. Check if the response contains such data
   4. Extract and loop through the markers
   5. Filter out low-intensity values (below 0.6)
   6. Convert milliseconds to seconds for readable URLs
   7. Remove closely clustered moments to reduce redundancy
   8. Produce a human-readable message including start time and direct timestamped URL
   9. Respond with a clean JSON payload of engaging moments
   
   ---
   
   ## 🔧 Workflow Breakdown
   
   ### 1. Triggering via Webhook
   The workflow begins with the "Webhook" node, triggered with a GET request like:
   
   ```
   {your-n8n-instance}/webhook/youtube-engaging-moments-extractor?ytID={youtubeID}
   ```
   
   This passes the YouTube ID as a query parameter, extracted in the next "Set" node called Input Variables.
   
   ### 2. Fetching Replay Markers
   Using the provided YouTube video ID, the workflow sends an HTTP GET request to:
   
   ```
   https://yt.lemnoslife.com/videos?part=mostReplayed&id={youtubeID}
   ```
   
   This API returns data on when users frequently rewind a video—the so-called "mostReplayed" markers.
   
   ### 3. Conditional Logic: Check for Data
   Before proceeding, the “IF” node validates whether "mostReplayed" data exists. If it doesn't, the workflow sends a clean "no data" JSON response immediately.
   
   ### 4. Processing the Replay Markers
   If the markers exist, the “Split Out” node breaks apart individual replay markers (each containing replay data per segment) into separate items for individual processing.
   
   ### 5. Filter by Engagement Intensity
   Next, the workflow filters out segments with an "intensityScoreNormalized" ≤ 0.6—ensuring only truly significant moments are kept.
   
   ### 6. Tidy Up the Timestamps
   The replay marker API returns time in milliseconds. A "Set" node converts this to seconds for use in YouTube’s timestamped URLs.
   
   ### 7. Prevent Duplicates
   The filter “Filter out moments close to each other” removes segments that are too close to one another (within 20 seconds), preventing near-duplicate highlights.
   
   ### 8. Format the Output
   A "Set" node generates human-readable and shareable links, like:
   
   ```
   Engaging moment #1: https://youtu.be/abcd1234?t=97
   ```
   
   It also includes a separate “directYTURL” field and normalized timestamp for flexibility.
   
   ### 9. Aggregate and Respond
   The clean, filtered, formatted list is aggregated into a single JSON object and sent back as the webhook response.
   
   In case no intensity data existed, a fallback payload is returned with a null as "engagingMoments".
   
   ---
   
   ## 📦 What You Get in the End
   
   A formatted JSON response like this:
   
   ```json
   {
     "youtubeID": "abcd1234",
     "engagingMoments": [
       {
         "humanReadableMessage": "Engaging moment #1: https://youtu.be/abcd1234?t=97",
         "startSec": 100,
         "directYTURL": "https://youtu.be/abcd1234?t=97"
       },
       ...
     ]
   }
   ```
   
   This is ideal for turning long-form video into snackable highlights, or for data-driven content strategy.
   
   ---
   
   ## 🌐 API Integration: LemnosLife (Unofficial YouTube Data Source)
   
   The workflow leverages the LemnosLife API—a community-provided scraper for advanced YouTube metrics. It provides access to YouTube's internal "mostReplayed" data, which isn’t accessible via the official YouTube Data API.  
   
   Endpoint used:
   ```
   https://yt.lemnoslife.com/videos?part=mostReplayed&id={videoID}
   ```
   
   ---
   
   ## ✅ Use Cases
   
   - Content creators identifying key moments to highlight
   - Video summarization or TL;DR tools
   - Editors looking to create hype reels
   - Developers building media analytics dashboards
   - Marketing teams analyzing viewer behavior
   
   ---
   
   ## 🚀 How to Use
   
   1. Deploy the workflow in your own n8n instance
   2. Copy the production URL from the Webhook node
   3. Activate the workflow
   4. Call the webhook with a YouTube ID:
   ```
   GET {yourWebhookURL}?ytID=YOUR_VIDEO_ID
   ```
   
   ---
   
   ## 🧩 Final Thoughts
   
   This n8n workflow demonstrates how powerful no-code automation can be when combined with clever data sources. By bringing together a webhook, replay intensity metrics, filtering logic, and clean formatting—all visually—it empowers anyone to surface the best parts of any YouTube video without writing a single line of traditional code.
   
   If you're working with video content or user engagement tracking, give this template a spin. And remember—sometimes, all it takes is a single intense moment to create lasting impact.
   
   ---
   
   Let the engaging moments roll.
   
   👏

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.