AI Search Visibility / FAQ Schema

Generate FAQPage Schema That Gets Your Content Cited by AI

Paste a URL into @vustSEObot. It reads the page, drafts 3-5 suggested FAQ questions grounded in what's actually on it, and hands back the ready FAQPage JSON-LD — free, no signup. A suggestion you review and paste, never a promise you'll get cited.

A drafted FAQ + ready JSON-LD from one pasted URL.Free · 3/day · drafts to review, not guarantees
Open @vustSEObot in Telegram
Ready-to-paste FAQPage JSON-LD3-5 questions grounded in your pageFree · 3/day · no signup

The Honest Frame

A drafted suggestion, not a citation guarantee

The FAQ questions and JSON-LD are drafted by Claude Sonnet from your page's real content — grounded, not templated. But GEO/AEO improves eligibility to be parsed and quoted; nothing, including this tool, can promise ChatGPT or Perplexity will actually cite you. Read the draft, fix anything wrong, then publish it as your own.

Same trust anchor as the full audit: what's deterministic stays labeled deterministic, what's AI-drafted stays labeled a draft.

See the difference

The difference between a product page with zero structured data and one with a grounded, ready-to-paste FAQPage block.

Product page with no FAQ schema

Nothing for an AI engine to lift

A product page: title, price, a paragraph of marketing copy, an image gallery. No JSON-LD in the page source at all — an AI engine has to guess at strap material, water resistance and warranty from prose, if it bothers to at all.

Suggested Q&A + ready JSON-LD

<script type="application/ld+json"> { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [ { "@type": "Question", "name": "What material is the strap made from?", "acceptedAnswer": { "@type": "Answer", "text": "The strap is woven nylon with a matte steel buckle, rated for daily wear." } }, { "@type": "Question", "name": "Is this watch water resistant?", "acceptedAnswer": { "@type": "Answer", "text": "Yes, it is rated to 5 ATM — safe for rain and handwashing, not for diving." } }, { "@type": "Question", "name": "What is the warranty period?", "acceptedAnswer": { "@type": "Answer", "text": "A 2-year manufacturer warranty covers the movement and casing." } } ] } </script>

@vustSEObot reads the page's actual text, drafts 3-5 question/answer pairs a buyer would realistically ask, and outputs the FAQPage JSON-LD for them — you review and edit before publishing.

Generic heading vs question heading

Hard to chunk

"Details" — a heading that tells an AI parser nothing about what's underneath.

Easy to chunk and quote

"Is this watch water resistant?" — a question-style heading maps directly onto what a user actually asks an AI answer engine.

Templated FAQ vs page-grounded FAQ

Generic, easy to spot as filler

"What is your return policy?" / "How do I contact support?" — boilerplate that could sit on any product page in any store.

Specific to this page

"What material is the strap made from?" — drafted from the page's own description, not a generic FAQ template.

02·Practical use cases

Who needs a drafted FAQ + ready JSON-LD

E-commerce PDP owners

Add FAQPage schema to a product page that never had one.

3-5 grounded Q&A pairs plus the ready JSON-LD to paste, drafted from the page's own copy.

Indie site owners without a CMS plugin

Get structured FAQ markup without installing a schema plugin.

A copy-paste <script type="application/ld+json"> block, no plugin required.

Content teams

Turn an existing page into something an AI answer engine can quote accurately.

Question-style headings and direct answers matched to what buyers actually ask.

SEO/GEO consultants

Show a client a concrete before/after instead of a vague 'add structured data' recommendation.

A specific, page-grounded FAQ draft and JSON-LD they can hand off same day.

03·How it works

How @vustSEObot drafts your FAQ schema

01Fetch the page

Paste a URL in Telegram — the bot fetches the page (Bright Data-preferred, SSRF-hardened transport) and reads its visible text, title and meta description.

02Check what's already there

Tier-1 deterministic parsing flags whether FAQPage/Article schema already exists, and whether the page has any FAQ-like structure at all.

03Draft grounded Q&A

Claude Sonnet drafts 3-5 question/answer pairs specific to that page's actual content — not a generic template — labeled as a suggestion, not a fact.

04Emit ready JSON-LD

A typed builder turns the drafted Q&A into valid FAQPage JSON-LD, ready to paste into a <script type="application/ld+json"> tag after you review it.

04·Same tool · in Telegram

Draft your FAQ schema now

@vustSEObot · Paste a URL into @vustSEObot — get 3-5 suggested FAQ Q&A grounded in the page, plus ready FAQPage JSON-LD.

Open in Telegram

05·Quality & trust

Honest about what this is

A draft to review, never auto-publish

The Q&A and JSON-LD are a starting point grounded in your page — read them, fix anything inaccurate, then publish it as your own content.

Grounded in your page, not a template

Questions come from what the page actually says, not a fixed 'shipping/returns/contact' boilerplate — that's what makes them worth publishing.

No citation guarantee

Structured data and a real FAQ improve eligibility to be parsed and quoted by AI answer engines. No tool, including this one, can promise a citation.

Free, with a daily cap

10 free audits/day, fail-open, no signup, no card. No paid tier exists yet.

Frequently asked questions

More AI search visibility tools

AI Search Visibility (GEO/AEO)The general framework — why AI answers cite some sources and not others.Full GEO/AEO AuditThe complete @vustSEObot audit this FAQ draft is one output of.AI Crawler Access CheckerCheck whether PerplexityBot, ClaudeBot, GPTBot and more can even reach your page.AI Shopping Agent VisibilityThe same GEO thinking applied to product pages and shopping agents.All tools

Ready when you are

A drafted FAQ schema, from one pasted URL.

Free, grounded in your page's real content, ready to paste — and honestly labeled as a draft to review, not a citation guarantee.

Open @vustSEObotFull GEO/AEO audit