web-reader

To extract web page content and metadata for backend content aggregation, you can use this Skill to fetch and parse diverse sites, returning structured data like title, URL, HTML, and publish time. It processes pages at scale for indexing.

Server-side web scraping returns structured article data by invoking the page_reader function via the backend SDK, which fetches the target URL and parses the HTML to extract the title, published time, and metadata.

Yes, you can use this backend page reader to extract article metadata at scale. It is designed for backend workflows that fetch, parse, and process pages from diverse sites, enabling tasks like article extraction and metadata retrieval.

Yes, you need the z-ai-web-dev-sdk to retrieve published time and HTML from URLs. The Skill uses this dependency in server-side code to invoke the page_reader function and return structured results including usage tokens.

The best way to build a content dashboard that ingests multiple online articles is to use a backend content extraction workflow. This Skill fetches varied pages and surfaces titles, HTML, and metadata for aggregation and summarization.

Web content extraction with this Skill provides visibility into API usage costs by returning usage tokens alongside the structured page results. This allows you to monitor the token consumption of your backend page reading operations.