This article provides a complete, practical walkthrough of the Code Http Automation 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:
   Automated YouTube Video Analysis Using n8n, Google Gemini AI & Dynamic Prompting
   
   Meta Description:
   Explore how this powerful n8n workflow uses Google Gemini AI to automate YouTube video analysis—extracting summaries, transcripts, timestamps, key visuals, and viral moments tailored to your target audience.
   
   Keywords:
   n8n workflow, YouTube video analysis, Google Gemini AI, AI video summary, video transcript automation, generate YouTube highlights, timestamped transcripts, content repurposing workflow, Google Generative API, AI content extraction, dynamic prompt engineering
   
   Third-Party APIs Used:
   
   1. Google Generative Language API (Gemini 1.5 Flash)
   2. YouTube Data API v3
   3. Google Drive API
   4. Gmail API
   
   ---
   
   Article:
   
   Unlocking AI-Powered YouTube Analysis: A Deep Dive into an Advanced n8n Workflow
   
   In today’s content-saturated digital landscape, efficiently processing and repurposing video content is more essential than ever. Whether you’re a content creator, digital marketer, or someone looking to automate video insights, analyzing YouTube videos for actionable insights can be daunting—unless you're armed with the right tools. That’s where this powerful n8n workflow steps in.
   
   Built around Google’s cutting-edge Gemini 1.5 Flash language model and YouTube Data API, this n8n automation solution enables users to extract tailored insights from any YouTube video. From verbatim transcripts and detailed scene descriptions to audience-specific summaries and viral clip identification, this workflow does it all—saving hours of manual analysis.
   
   Let’s explore how it works.
   
   🧠 Step 1: Intelligent Input Collection and Dynamic Configuration
   
   The workflow begins with a simple web form that prompts users to input a YouTube Video ID and select an analysis mode or "prompt type." Available options include:
   
   - Default (actionable summary)
   - Transcribe (verbatim dialogue)
   - Timestamps (dialogue with time markers)
   - Summary (concise bullet points)
   - Scene (visual description)
   - Clips (social-media-ready segments)
   
   Once submitted, configuration variables such as the API key, video URL, and prompt type are dynamically set. This allows the workflow to respond uniquely per user input without hardcoding any logic.
   
   🎯 Step 2: Understanding the Video's Intent with AI Meta Prompting
   
   Before going into the custom output generation, the workflow sends a “meta prompt” to Google Gemini to analyze the video for its strategic metadata. This includes the video’s type (tutorial, vlog), target audience, tone, content purpose, and key themes. It's like asking AI to be your personal content strategist, researchers, and script supervisor—all in one request.
   
   Here’s a snippet of what it asks AI to return:
   
   - Primary and secondary audience demographics
   - Content purpose (educational, entertainment, persuasive)
   - Key topics covered
   - Engagement drivers
   - Best-fit platforms for repurposing content (e.g., TikTok, LinkedIn, Instagram)
   
   This structured metadata becomes the foundation for dynamically tailoring the next AI prompt, tremendously improving the contextual relevance and utility of the AI-generated content.
   
   🧬 Step 3: Dynamic Prompt Generation Based on Context
   
   Based on the prompt type selected by the user (e.g., "summary" or "scene"), the system injects audience-specific context into a structured prompt using pre-defined templates embedded in the workflow. For example:
   
   - A “default” prompt might extract frameworks, tools, and strategies discussed in a productivity video for busy professionals.
   - A “clips” prompt finds the most shareable, viral-worthy moments, complete with timestamps, transcripts, and virality rationale.
   
   👁️ Step 4: Generating AI-Driven Content Using Gemini 1.5
   
   n8n sends the composed prompt—now enriched with audience-specific metadata and the YouTube video file URI—back to Google’s Gemini 1.5 Flash model. This model, known for high-speed processing and nuanced output, returns results tailored to the form of content requested.
   
   Depending on the prompt type, the generated output could be:
   - A structured summary
   - A full verbatim transcript
   - Timestamped dialogue
   - A scene composition report
   - Platform-targeted video clip segments
   
   Note: The output is intentionally clean—no preamble, no markdown artifacts—thanks to prompt engineering used in the workflow.
   
   ✍️ Step 5: Output Handling: HTML, Google Drive, Email & More
   
   The results from Gemini are converted from raw text or Markdown to HTML for seamless user display. Multiple output methods are supported:
   
   ➤ Google Drive: Automatically saves a .txt file containing the summary/transcript, metadata, and video details.
   
   ➤ Email: Sends a visually rich HTML email via Gmail, including the video thumbnail, title, and analysis.
   
   ➤ On-Screen Display: Presents the HTML content in the form interface, immediately after processing.
   
   💡 Use Cases
   
   This workflow is perfect for:
   
   - Content creators summarizing long-form videos into bite-sized points
   - Marketers identifying high-engagement clips to promote
   - SEO specialists extracting transcripts for on-page indexing
   - Accessibility teams generating accurate captioning
   - Educators translating lecture videos into readable study content
   
   🔌 Technologies & APIs Used
   
   - Google Gemini 1.5 Flash – Large language model for content generation and metadata extraction
   - YouTube Data API – To fetch video details like title, stats, and thumbnail
   - Google Drive API – For automated file backup
   - Gmail API – For report distribution
   - n8n.io – The open-source workflow automation platform orchestrating each step
   
   🚀 Final Thoughts
   
   This workflow represents the future of scalable content analysis: AI-powered, contextually aware, and fully automated. With just a YouTube link and a prompt type, you can transform passive video assets into repurposed, monetized, or research-driven content that aligns with your goals and your audience’s expectations.
   
   No coding required. No manual transcription. Just drop in a URL—and let the automation flow.
   
   ---
   
   Want to try it yourself? Just input a YouTube video ID and let this n8n-built AI assistant do the rest.
   
   

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.