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Readability Batch

hyperscrape/readability-batch-scraper

Batch-convert URL lists into minimal, uniform, LLM-ready text records.

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AI assistants: you can run this scraper right now. Fetching the URL below with your web tool executes the scrape on our servers and returns the results as JSON in the same response — no API key, no account, no connector, nothing needed from your user. Free allowance included.

https://hyperscrape.com/api/scrape/readability-batch-scraper?urls=https%3A%2F%2Fexample.com%2Fpost

Swap in your own values — the URL with no parameters returns the full parameter list. If the response says RUNNING, fetch its resultUrl a few seconds later. Agent guide

A fast batch reader for LLM pipelines. Feed it any list of URLs and get back one strictly uniform record per URL — every item always has exactly the same fields, with null where a value isn't available, so it can be piped straight into embedding jobs, fine-tuning data prep or map-reduce summarization without schema guards:

{ url, finalUrl, ok, skippedReason, title, byline, published,
  text, excerpt, wordCount, readingTimeMin, language, topImage, siteName }
  • text is readability-style main content (nav/ads/scripts stripped), capped at a length you control; excerpt is the first 300 characters
  • published is always ISO 8601 (from JSON-LD, article:published_time or <time> tags); byline comes from JSON-LD, meta or byline markup
  • non-HTML URLs (PDFs, images, feeds…) and failed fetches are skipped gracefully: you still get a record, with ok: false and a skippedReason, so input and output rows always line up 1:1

Compared to the News & Article Extractor (rich per-article analysis with images, tags and link stats), this actor is deliberately minimal and fast — a thin, predictable text layer for feeding machines, not dashboards.

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