extract-article-text

To extract article text from a PDF, you can pass the file to this skill to pull the title, author, publish_date, body, and summary. It processes the document and returns clean, structured JSON while ignoring headers, footers, and navigation noise.

Yes, you can extract metadata and body text from webpages and Word documents by providing a URL or file input. The skill consistently returns structured article data including the title, author, publish_date, body, and summary fields.

The best way to get clean article content for a knowledge base is to use a structured extraction tool that filters out sidebars and navigation. This skill outputs consistent JSON with defined fields, making it suitable for archival pipelines.

Yes, the article extraction process supports both URL and file inputs for PDFs, Word documents, and webpages. It accepts these inputs to return consistent JSON containing the title, author, publish_date, body, and summary fields.

When extracting content from mixed sources like PDFs and webpages, the structured fields returned are title, author, publish_date, body, and summary. This ignores headers and navigation noise to provide clean article data.