What problem does it solve?
This Skill solves the problem of getting reliable article text and metadata from inconsistent web pages, including JS-heavy sites, without dumping raw HTML or guessing blindly.
Core Features & Use Cases
- Multi-strategy extraction cascade: starts with lightweight static fetching and escalates to Playwright rendering only when needed.
- News detection + structured metadata: detects news/articles via URL patterns, Schema.org/og tags, and content heuristics, then extracts title/author/date/section/tags and paywall signals.
- Clean-text comprehension and optional entity extraction: extracts and normalizes main content first, then optionally runs LLM entity extraction only on clean text to produce people/organizations/locations/events/relationships.
- Output-ready JSON with quality metadata: produces structured JSON results including method, paywall type, provenance fields, and data-quality assessment.
- Use Case: Process a list of 500 blog/news URLs, validate which ones are articles, extract cleaned content and entities, and generate JSON outputs for downstream analysis.
Quick Start
Use the web-scraper skill to extract article text and structured metadata from a set of news URLs, detect paywalls, and output JSON with quality and provenance fields.