gpu-cluster-monitor

Monitors GPU cluster health and usage, providing real-time status, performance metrics, and alerts for efficient resource management.

Skill: deep-scraper

Overview

A high-performance engineering tool for deep web scraping. It uses a containerized Docker + Crawlee (Playwright) environment to penetrate protections on complex websites like YouTube and X/Twitter, providing "interception-level" raw data.

Requirements

1. Docker: Must be installed and running on the host machine.
2. Image: Build the environment with the tag clawd-crawlee.
   • Build command: docker build -t clawd-crawlee skills/deep-scraper/

Integration Guide

Simply copy the skills/deep-scraper directory into your skills/ folder. Ensure the Dockerfile remains within the skill directory for self-contained deployment.

Standard Interface (CLI)

docker run -t --rm -v $(pwd)/skills/deep-scraper/assets:/usr/src/app/assets clawd-crawlee node assets/main_handler.js [TARGET_URL]

Output Specification (JSON)

The scraping results are printed to stdout as a JSON string:

• status: SUCCESS | PARTIAL | ERROR
• type: TRANSCRIPT | DESCRIPTION | GENERIC
• videoId: (For YouTube) The validated Video ID.
• data: The core text content or transcript.

Core Rules

1. ID Validation: All YouTube tasks MUST verify the Video ID to prevent cache contamination.
2. Privacy: Strictly forbidden from scraping password-protected or non-public personal information.
3. Alpha-Focused: Automatically strips ads and noise, delivering pure data optimized for LLM processing.