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web-reader

Extract structured content and metadata from web pages via URLs.

Updated Jun 1, 2026
Search Tags:#web scraping#metadata#content extraction#article extraction#html parsing#page reader
One-click install
npx skills add https://github.com/atro2829-hub/APPLE-NET-NEW --skill web-reader-atro2829-hub
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: web-reader
Source: https://github.com/atro2829-hub/APPLE-NET-NEW/tree/main/skills/web-reader
Command: npx skills add https://github.com/atro2829-hub/APPLE-NET-NEW --skill web-reader-atro2829-hub

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z-ai-web-dev-sdk, and includes scripts (resource) components.

What problem does it solve?

This Skill removes the manual work of copying content out of web pages by turning URLs into structured article data, page metadata, and clean HTML or text that applications can use directly.

Core Features & Use Cases

  • Web page extraction: Read a URL and return title, HTML content, plain text, publication time, and metadata.
  • Content processing workflows: Build news readers, research tools, SEO analyzers, monitoring jobs, and content aggregation pipelines around consistent page extraction.
  • Backend integration: Use the z-ai-web-dev-sdk in server-side code for deterministic page reading, batching, caching, and error handling.
  • Use case: A product team can automatically collect article content and metadata from a set of source pages, normalize it, and feed it into a downstream analysis pipeline.

Quick Start

Ask the skill to read a web page from a URL and return the extracted article title, content, and publication metadata.

Frequently Asked Questions about web-reader

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

FAQPage Schema
How do I extract article content and metadata from web pages?▼

Extracting article content and metadata from web pages involves parsing URLs to return structured data including titles, HTML, plain text, and publication times. This approach automates reading and collecting page information for downstream applications.

What is the best way to automate news aggregation and content monitoring from multiple URLs?▼

Automating news aggregation and content monitoring is best achieved by building extraction pipelines that fetch and normalize page data from multiple URLs. This creates consistent structured content for analysis without manual copying.

Does web page extraction work with backend SDKs for server-side content processing?▼

Web page extraction works with backend SDKs like z-ai-web-dev-sdk for server-side content processing. It enables deterministic page reading, batching, and caching directly within backend code for automated workflows.

Can I use HTML parsing to get clean text and publication time for SEO analysis?▼

HTML parsing can retrieve clean text and publication time for SEO analysis by extracting structured metadata from web pages. This provides normalized article data necessary for evaluating search performance and content trends.

What are the limitations of using automated page readers for research collection?▼

Limitations of automated page readers for research collection include dependency on consistent HTML structures for accurate extraction and the need for backend integration to handle batching, caching, and error handling effectively.

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