Scrape Templates

Extract product details from Amazon product pages — title, price, rating, images, availability, and specifications.

Extract repository metadata from GitHub — stars, forks, description, language, last commit, and README summary.

Extract organic search results from Google — links, titles, snippets, ads, and featured snippets.

Extract thread data from Hacker News — title, score, author, comment count, and top-level comments.

Extract job listing details — title, company, salary range, location, requirements, and application link.

Extract company information from LinkedIn — name, description, employee count, industry, headquarters, and specialties.

Extract article content from news sites — headline, author, publication date, body text, summary, and tags.

Extract multiple product items from a category or search results page — names, prices, ratings, and links.

Extract post data from Reddit — title, score, author, subreddit, and top comments.

Extract structured content from Wikipedia — title, summary, sections, infobox data, categories, and references.