A powerful AI utility that transforms YouTube video content into structured, SEO-friendly Markdown articles using Gemini 2.5 Pro.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lovtrip-video2article
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install lovtrip-video2article using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is lovtrip-video2article?
lovtrip-video2article is a professional-grade tool designed to automate the conversion of video content into high-quality written articles. By leveraging the advanced multimodal capabilities of Google Gemini 2.5 Pro, it analyzes YouTube videos to extract key insights and generate a complete editorial package including titles, author attribution, and formatted Markdown text. This skill is particularly effective for content creators and developers looking to expand their Openclaw Skills library with robust media processing capabilities.
Originally developed for the LovTrip travel platform to turn Vlogs into travel guides, this skill is versatile enough for any niche. It supports multiple languages and offers custom prompt overrides, allowing users to fine-tune the output style from first-person narratives to technical tutorials. Its seamless integration via MCP server or CLI makes it an essential tool for automated content pipelines.
lovtrip-video2article Use Cases
- Converting travel Vlogs into detailed, searchable travel guides and itineraries.
- Repurposing technical video tutorials into structured documentation and blog posts.
- Generating quick text-based summaries of educational YouTube content for easier consumption.
- Automating the creation of newsletters based on recent video uploads.
How lovtrip-video2article Works
- The user provides a public YouTube URL and specifies the target language (defaults to Simplified Chinese).
- The tool utilizes the Gemini 2.5 Pro model to analyze the video's visual and audio data.
- The AI extracts the YouTube channel name to populate the author field and creates a compelling title.
- A 2-4 sentence summary is generated to provide a high-level overview of the video content.
- The model generates a comprehensive Markdown body, using first-person perspective by default, complete with headers, lists, and bold text.
- The structured data is returned as a JSON object, ready for publication or further processing within your Openclaw Skills workflow.
lovtrip-video2article Setup
Method 1: MCP Server (Recommended)
Add the following configuration to your MCP settings file:
{
"mcpServers": {
"lovtrip": {
"command": "npx",
"args": ["-y", "lovtrip@latest", "mcp"],
"env": {
"GEMINI_API_KEY": "your-gemini-api-key"
}
}
}
}
Method 2: Standalone Script
You can run the conversion directly using Node.js without full installation:
GEMINI_API_KEY=your-key node scripts/video2article.mjs "https://www.youtube.com/watch?v=VIDEO_ID"
lovtrip-video2article Data Schema & Taxonomy
The skill returns a structured JSON object with the following schema:
| Key | Type | Description |
|---|---|---|
title |
string | The generated headline for the article. |
author |
string | Automatically extracted YouTube channel name. |
summary |
string | A concise 2-4 sentence summary of the video. |
body |
string | Full article content in Markdown format including headers and lists. |
lovtrip-video2article Advanced Features
- Multi-Language Support: Generate articles in English, Simplified Chinese, Japanese, Korean, Spanish, French, or German.
- Custom Prompting: Provide specific instructions to the AI to change the focus or tone of the generated article.
- Channel Extraction: Automatically attributes content to the original YouTube creator.
- Zero-Dependency CLI: Execute tasks via
npxor local scripts for lightweight integration into existing Openclaw Skills environments.
SKILL.md
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