This article provides a complete, practical walkthrough of the Manual Code 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:
   Transform YouTube Videos into AI-Generated Summaries, Transcripts, and Visual Insights with n8n
   
   Meta Description:
   Discover how to automate YouTube video analysis using this powerful n8n workflow powered by Google's Gemini API. Generate video summaries, transcripts, timestamped dialogues, scene descriptions, and viral clip insights in minutes.
   
   Keywords:
   YouTube transcription automation, AI video summarizer, n8n workflow for YouTube, Gemini API YouTube, AI scene analysis, generate timestamped transcripts, YouTube clip extractor, n8n AI workflows, content repurposing automation, Gemini 1.5 Flash integration, video insights automation
   
   Third-Party APIs Used:
   - Google Gemini API (https://ai.google.dev/)
   
   Article:
   
   Automating Video Intelligence: From YouTube Clips to Actionable Insights with n8n and Gemini
   
   In the fast-paced world of content creation and analysis, manually transcribing and summarizing video content is a time-intensive task. But what if you could streamline that process, parsing entire YouTube videos into structured summaries, verbatim transcripts, shareable clips, and even scene-level visual insights—all with a single automated workflow?
   
   Thanks to an advanced n8n workflow leveraging Google's Gemini 1.5 Flash API, you can do exactly that.
   
   Let’s dive into how this intelligent system operates, what it produces, and why it’s a game-changer for marketers, educators, content creators, and analysts.
   
   The Big Picture: Workflow Purpose
   
   This n8n workflow is designed to analyze public YouTube videos using Google’s Gemini multimodal AI to generate detailed outputs based on your preferred goal.
   
   With just a few variables (like video URL and desired output type), the system can:
   
   - Transcribe spoken dialogue
   - Create timestamped transcripts
   - Produce nested-bulletpoint summaries
   - Generate scene-level visual descriptions
   - Extract viral-worthy social media clips
   
   …all using automated API calls and carefully engineered prompts customized for rich, structured output.
   
   How It Works: Key Workflow Mechanics
   
   This workflow begins with a simple manual trigger but is flexible enough to support webhooks, form inputs, or integration with platforms like Airtable or Notion.
   
   1. Input Collection:
   Using an initial Set node titled “Define Initial Variables,” the user provides:
      - YouTube video URL
      - Google Gemini API key
      - Desired prompt type (e.g., “transcript,” “summary,” “scene”)
   
   2. Decision Logic:
   A Switch node routes the flow based on the promptType value. Each route prepares a relevant request:
      - “transcript” triggers a request for plain dialogue
      - “timestamps” adds exact timing to each line
      - “summary” generates a bulleted recap
      - “scene” describes on-screen visuals
      - “clips” selects short, sharable segments with explanation
   
   3. Prompt Assembly:
   Each branch utilizes a Set node to craft a purpose-specific prompt and define the Gemini model (gemini-1.5-flash). Prompts are carefully worded to avoid extraneous explanations or text.
   
   4. Gemini API Request:
   After setting prompts and model parameters, the flow sends a POST request to the Gemini API’s generateContent endpoint, formatted to include both the prompt and the video URI.
   
   5. Response Handling:
   The returned data is merged with earlier input data to ensure continuity. Then a final Set node filters and renames useful fields like:
      - AI-generated answer (e.g., summary or transcript)
      - Token usage
      - Model version used
   
   6. Ready for Distribution:
   At this stage, the output is ready to be sent via webhooks or other n8n endpoints to Notion, Google Docs, web CMSs, or simply displayed within the n8n interface for manual use.
   
   Smart Features That Stand Out
   
   What makes this workflow especially powerful is the level of detail and flexibility packed into each prompt. For example:
   
   - Scene descriptions don't just identify objects; they cover lighting, camera movement, color palettes, and people’s facial expressions.
   - The viral clip extractor pairs timestamps and transcripts with rationale crafted for social sharing (e.g., “inspiring,” “controversial,” “humorous”).
   
   Moreover, fallback paths, error handling placeholders, and prompt documentation make this a plug-and-play solution adaptable to evolving content needs.
   
   Use Cases Across Industries
   
   1. Content Creators:
      - Rapidly repurpose long-form videos into reels, shorts, or blog summaries.
   2. Educators:
      - Turn lectures into comprehensive notes or scene analyses for classroom use.
   3. Marketing Teams:
      - Mine product demo videos for key value propositions and highlights.
   4. Researchers:
      - Break down interviews and discussions by visual context and dialogue.
   
   Setup Requirements
   
   To get started, you’ll need:
   
   - A Google API Key (from Google Cloud Console or AI Studio)
   - The latest version of n8n (tested on v1.82.3 or later)
   - Public YouTube URLs (private videos are not supported via URI)
   
   Future-Proof and Customizable
   
   This workflow is built around Gemini 1.5 Flash, but the design allows for future model support. Additional HTTP header fields and body formats could easily be adapted for custom endpoints or upgraded APIs.
   
   Prompts can also be expanded or refined, including full content marketing packages (title, description, tags), blog articles, product comparisons, or even debate-style argument analysis using AI.
   
   Conclusion
   
   This AI-powered n8n workflow reshapes how we interact with and extract insights from video content. From auto-generating SEO-friendly summaries to creating cinematic scene descriptions, you can now do in 60 seconds what used to take hours.
   
   Video analysis, content repurposing, and storytelling have officially entered the automation age.
   
   Whether you're a solo content creator, data engineer, marketer, or teacher, this workflow gives you superpowers.
   
   Want to try it live? Check out the sample video and walkthrough at https://www.youtube.com/watch?v=Ovg_KfKxnC8 and bring your next automation to life.
   
   —
   
   
   End of Article

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.