Cq vs Extractor

“Agents sharing solutions with other agents — this is how agent ecosystems should work. The Mozilla backing gives it credibility and staying power.”

“Schema-driven extraction with LLM fallback is exactly right. Traditional scrapers break on every site redesign — Extractor adapts because it understands the content semantically. The TypeScript-first approach with strong typing on outputs is chef's kiss for building data pipelines.”

“This is the emergence of collective agent intelligence. Individual agents learning from the swarm. Mozilla is building infrastructure for the agentic web.”

“Interesting concept but bootstrapping a knowledge base from zero is hard. Stack Overflow took years to become useful. Agent queries are even more varied.”

“LLM extraction costs add up fast at scale. But for the use cases where you need it — scraping sites with unpredictable layouts, extracting from pages that change frequently — the reliability improvement over CSS selectors easily justifies the token spend.”

“I have been using this to pull structured data from competitor landing pages and product directories. The schema definition is intuitive and the extraction quality is surprisingly consistent even across wildly different page designs.”