faq-schemalisted

# faq-schema AI answers are questions-and-answers by nature. A page structured as real Q&A gives the model clean pairs to lift — and the `FAQPage` markup makes the structure explicit. ## Steps 1. **Fetch the page** and understand what it's about and who it's for. 2. **Derive the real questions** a buyer or reader would ask about this topic — not generic filler. Draw them from: what the page implicitly answers, related searches, and how people actually phrase things (use the `buyer-questions` skill for deep mining). Aim for 5–8 genuine questions. 3. **Write each answer** as a self-contained 40–80 word passage, answer-first (see `content-capsule`). Each answer must stand alone. 4. **Generate `FAQPage` JSON-LD** with each question/answer pair. ## Output format First, the human-readable FAQ section (H2 "Frequently asked questions", each question an H3, answer below). Then the JSON-LD: ```html <script type="application/ld+json"> { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "[The question]", "acceptedAnswer": { "@type": "Answer", "text": "[The self-contained answer]" } } ] } </script> ``` ## Honest note for the user Google removed FAQ rich results for most sites in May 2026, so **don't expect the star-studded search snippet.** The value now is different and real: clean Q&A pairs are highly quotable by ChatGPT/Perplexity/Gemini, and the markup helps AI Mode parse them. Ship it for AI