web-scraper

Extract structured data from websites with sanitized Markdown output.

Updated Mar 25, 2026
One-click install
npx skills add https://github.com/ouakar/ubinarys-dental --skill web-scraper-ouakar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: web-scraper
Source: https://github.com/ouakar/ubinarys-dental/tree/main/skills/forgewright/skills/web-scraper
Command: npx skills add https://github.com/ouakar/ubinarys-dental --skill web-scraper-ouakar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Web Scraper — Security-First Data Extraction Specialist addresses the challenge of obtaining clean, structured data from websites without compromising security or data integrity. It enforces strict safeguards (library-mode only, URL validation, SSRF protection, output sanitization, and non-persistent browser state) to prevent data leakage and prompt injection while enabling reliable downstream ingestion.

Core Features & Use Cases

  • Library-mode only web crawling to avoid Docker API exposure and reduce security risk.
  • CSS/XPath-based extraction for structured data, Markdown extraction when structure is unknown, with sanitized Markdown output suitable for RAG workflows.
  • Reduces risk of prompt injection and data exfiltration while supporting reproducible data pipelines for research, analytics, and knowledge extraction.
  • Use Case: A data team collects product specs from supplier sites and prepares a clean JSON feed for a recommendation system, with sanitized content ready for NotebookLM or LLM synthesis.

Quick Start

Run a secure crawl against a target URL and produce sanitized output ready for downstream processing.

Frequently Asked Questions about web-scraper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I securely extract structured data from websites for AI workflows?

Secure web scraping extracts structured content using library-mode crawling, enforcing URL validation and output sanitization to prevent data leakage. It produces clean, sanitized Markdown or JSON feeds ready for RAG workflows and downstream LLM synthesis.

What is library-mode web crawling and why use it instead of Docker APIs?

Library-mode web crawling operates without Docker API exposure, reducing security risks by running crawlers directly in the environment. This approach enforces strict browser isolation and hardened config defaults to prevent prompt injection and data exfiltration during data extraction.

How does web scraping prevent SSRF and prompt injection attacks?

Web scraping prevents SSRF and prompt injection through strict URL validation, output sanitization, and non-persistent browser state. These security constraints ensure that malicious content from target sites cannot execute arbitrary commands or access internal network resources.

Can I extract unstructured web content into Markdown for RAG pipelines?

Yes, web scraping supports Markdown extraction when site structure is unknown, delivering sanitized Markdown output optimized for RAG workflows. CSS and XPath-based extraction are also available for pulling structured data like product specs into clean JSON feeds.

Does secure web scraping enforce rate limiting and browser isolation?

Secure web scraping enforces rate limiting and hardened browser isolation by default to ensure reproducible data pipelines. Non-persistent browser state guarantees that each crawl session remains isolated, preventing cross-session data contamination and ensuring stable data extraction.

What are the limitations of library-only web crawling for data extraction?

Library-only web crawling limitations include reliance on strict URL validation and rate limiting, which may restrict aggressive crawling. It avoids Docker API usage entirely, meaning all extraction must conform to library-mode constraints without bypassing security boundaries for high-volume scraping.