TrendScout is a lightweight AI-powered assistant that analyzes YouTube video titles to uncover packaging patterns, emotional hooks, and formatting styles used in top-performing content.

This tool was designed to test whether simple, repeatable workflows could help creators generate title insights without manually reviewing dozens of videos. It forms the first proof-of-concept (POC) for a larger visual analysis tool, ThumbScout, which will later include GPT-4 Vision.

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• 🔍 Scrapes titles using SERP API (Google → YouTube engine)
• 🧠 Analyzes titles for emotional appeal, formatting, and clarity
• 📬 Compiles results into a CSV + emails the report to the user
• ✅ Fully automated workflow via n8n, including error handling

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• Project Name: TrendScout
• Creator: Ros Talbot
• Date: July 31, 2025
• Version: MVP v0.1
• Build Time: ~2 hours

TrendScout successfully ran a complete agent-style pipeline:

• Live search → LLM analysis → CSV conversion → automated email delivery

It’s designed for:

• YouTube creators
• Content strategists
• Thumbnail/title testers

🟢 Low-lift, high-utility, and ready for iterative upgrades.

View full evaluation notes ▶ (linked if broken out later)

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• Automation: n8n
• LLM: GPT-3.5 and GPT-4 (via OpenAI node)
• Data Source: SERP API (YouTube via Google)
• Delivery: Native email node (SMTP)
• Output: CSV + Markdown

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• Add structured parsing (Markdown, JSON)
• Include original video links, publish dates, and views
• Batch analyze multiple queries at once
• Add scheduled triggers (e.g. weekly trend pull)
• Expand into GPT Vision for full ThumbScout build

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• ThumbScout → [FUTURE PROJECT LINK]

  TrendScout served as the prototype for title analysis inside this larger vision-based agent.

• Vibe Agent Series → [Parent Page Coming Soon]

  TrendScout is part of a micro-agent portfolio exploring creative, lightweight AI tools built without traditional dev teams.

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DM @RosTalbot or fork this agent and make it your own!