Schema Markup Online: Free JSON-LD Generator for AI Search

You can create schema markup online for free by choosing a type, filling in facts that already appear on the page, copying the JSON-LD the generator outputs, pasting it into the page and validating it. That takes minutes. Whether AI engines then repeat those facts is a separate question, and this guide shows how to test it.

Key takeaways

• Generate JSON-LD, not microdata: it sits in one block, is easy to edit and is the format Google's documentation favours.
• Four types do most of the work for a brand: Organization, Article, FAQPage and Product. Each one backs a different kind of AI answer.
• Every value in the markup must also be visible on the page. Markup that contradicts the page breaks Google's structured data policies.
• Google says no special schema is needed for its generative AI features. Microsoft says schema helps its LLMs understand content. Treat schema as clarity, not a ranking lever.
• Prove the effect with a fixed prompt set run before and after, not with a validator pass alone.

How do I create schema markup online for free?

Use a generator that outputs JSON-LD and lets you edit the result. Noma's free schema generator prefills Organization, LocalBusiness, Product, FAQ, Article and other types from your site and validates markup you already have. Several other free form-based generators exist, and they all follow the same flow.

1. Pick the page, then the type. One page, one main entity. A product page is Product. Your about or home page is Organization. A blog post is Article.
2. Fill the form from the visible page. Copy the name, description, price or author as they appear on the page. Do not add claims the page does not make.
3. Copy the JSON-LD block. It will start with a script tag of type application/ld+json.
4. Place it in the page. The head or the end of the body both work. In WordPress, Shopify or Next.js use the template or a plugin field so every page of that type gets it.
5. Validate. Run the live URL through Google's Rich Results Test for rich-result eligibility and the Schema Markup Validator at schema.org for general syntax.
6. View the raw HTML. Open view-source on the live page and confirm the block is there without needing JavaScript to run. A crawler that does not execute scripts will only see what is in the delivered HTML.

One recent technical note: a Launchcodex report, August 2026 says Google now unescapes HTML entities in JSON-LD once rather than twice. In practice, write strings with ordinary JSON escapes and do not pre-escape characters such as ampersands as HTML entities. Check any generator output for this.

Which schema types help my brand show up in AI answers?

No schema type is documented to force a mention. What each type does is state a fact in a form a machine can read without guessing. That matters most where an AI answer needs one precise fact: who you are, who wrote something, what a product costs.

Google is explicit about the limit. Its guide to generative AI features says, in a line quoted by Google Search Central, July 2026: "Structured data isn't required for generative AI search, and there's no special schema.org markup you need to add." Microsoft takes a more positive line. Search Engine Roundtable, March 2025 reported that Fabrice Canel of Microsoft Bing confirmed on stage at SMX Munich that schema markup helps Microsoft's LLMs understand content.

A Google engineer has described the appeal in terms of cost. Ryan Levering, speaking at Search Central Live New York in March 2025, said: "A lot of our systems run much better with structured data. It's computationally cheaper." (Analyzify, September 2026, quoting the talk.)

The type-to-answer map

Treat the right-hand column as a hypothesis to test, not a promise. An engine can still draw its answer from a review site or a forum thread instead of your markup.

What should each type contain, and what goes wrong?

Organization: your identity sentence

The Organization block is the structured version of the sentence you want an engine to say about you. Keep the description identical to the one on your about page. Use sameAs for official profiles only, such as your LinkedIn page, Crunchbase entry or Wikipedia article if one exists. The common mistake is a logo URL that returns a redirect or a description written as marketing copy. Name collisions are another risk: if another company shares your name, a clear description and official sameAs links are the cheapest disambiguation you have. Our AEO guide chapter on brand positioning covers writing that sentence.

Article: who wrote it and when

Fill author with a real named person and, where you can, link to an author page. Set datePublished once and update dateModified only when the content changes. Engines that weigh freshness read dates, and a dateModified bumped without edits misleads readers and can look manipulative. Match the headline to the visible H1.

FAQPage: use it for clarity, not for a snippet

Google reduced FAQ rich results in August 2023. Search Engine Journal reported at the time that FAQ results would mostly be limited to well-known government and health sites and that HowTo results would go entirely. A Hoplite Analytics report, 2026 says Google ended FAQ rich results altogether in May 2026. Check Google's current FAQPage documentation before promising anyone a visible snippet. The case for FAQPage now is that it labels question and answer pairs for any machine that reads the page. Only mark up questions that are visible on the page, and copy the answer text exactly.

Product: price and availability must be true today

Product with Offer is where stale data does most damage. If the markup says in stock at one price and the page shows another, engines and shoppers get a contradiction. Generate markup from the same source as the page, ideally the template and not a hand-pasted block. For a Black Friday run, see our ChatGPT Shopping checklist.

What are the rules that apply to every type?

Google's general structured data guidelines (as checked on 5 November 2026) require markup to describe content users can see on the page and to be relevant to it. Markup for content that is hidden or invented risks losing rich result eligibility. The rule applies in spirit to AI engines too: an answer built from a fact that the page itself does not show is a fact nobody can verify.

How do I check whether AI engines pick up my schema?

Passing a validator proves the syntax. It does not prove an engine used it. The test below compares answers before and after, and it works with free tools. Do the free AI SEO Checker first: it shows whether ChatGPT, Claude, Perplexity and Google AI Mode can read your page at all, which comes before any schema question.

1. Write 10 to 20 buyer prompts. Include unbranded ones ("best [category] for [use case]") and fact prompts ("what does [brand] cost?", "who founded [brand]?"). The free AI Prompt Finder suggests questions buyers ask in your category.
2. Run each prompt several times on each engine, from fresh sessions. Answers vary between runs. Our write-up of AI citation stability covers the Ahrefs tracking of 37,500 citations and why single runs mislead (Noma, October 2026).
3. Record four things: is the brand named, is the stated fact correct, which URLs are cited, and which rivals appear.
4. Ship the schema, then wait for recrawl. Give it a few weeks. Change nothing else on those pages, or you cannot attribute the change.
5. Re-run the same prompts. Count a change only if it exceeds run-to-run noise.

Engines also disagree with each other. Bluefish data, written up by Noma in Do AI Engines Name the Same Top Brand? (November 2026), found AI engines disagree on the top brand in 35% of buying topics. Read results per engine, not as one average.

A worked example, with illustrative values

Suppose a fictional company, Example Co, finds that an engine gives the wrong founding year. The fix is not only markup. It adds the year to the visible about page, adds foundingDate to the Organization block, makes sure the profiles in sameAs show the same year, and then re-runs the fact prompt "When was Example Co founded?" five times per engine. If the wrong year persists, the engine is relying on a third-party source, so find the cited page and correct it there. Our correction runbook sets out that sequence.

What can schema not do?

Be wary of anyone who sells schema as a shortcut. Three limits are worth stating to your team.

• It does not replace being mentioned elsewhere. In Noma's own count of 2,545 ChatGPT, Gemini, Perplexity and Claude answers, engines named Nurdd in 4 of 2,166 category answers (0.2%) (Noma, November 2026). Markup on a new brand's own site does not change how rarely third parties mention it.
• It does not override blocked crawlers. If GPTBot, OAI-SearchBot or PerplexityBot cannot fetch the page, the markup is invisible. Run the free AI Crawler Checker to see which of them can crawl your site.
• It cannot fix poor content. Markup labels a page. The answer-first writing, quotable passages and evidence still have to be there. The Content AI-Readiness Grader shows which passages of a page are quotable.

Where Noma fits

Noma by Nurdd is an AEO and AI visibility platform. After you ship schema, it asks 13 AI engines, including ChatGPT, Gemini, Perplexity and Claude, your buyers' questions every day. For each engine it reports whether your brand is named, how high, and with what sentiment, and it lists the pages cited. That lets you compare answers before and after a markup change.

See it on your own brand: book a demo or start the 3-day free trial.

Which free generator should I use?

Judge any generator on what it lets you check, not on how many types it lists. Use these questions.

The Noma schema generator covers the first four rows: it generates JSON-LD for those types, prefills from your site and validates existing markup. If you also publish an llms.txt, the llms.txt generator and validator is a separate free check, and our llms.txt guide explains what it can and cannot do.

A one-hour checklist

1. List your five most important pages: home, about, top product, top article, pricing.
2. Assign one type to each.
3. Generate the markup and compare each value with the visible page.
4. Add it through templates, not by hand, wherever pages repeat.
5. Validate each live URL and check view-source.
6. Save your baseline prompt answers before you publish.
7. Re-run after recrawl and log what changed.

How we researched this

We reviewed Google Search Central documentation on structured data and generative AI features, trade reports on Microsoft's and Google's public statements about schema, reports on Google's FAQ and HowTo rich result changes, several free schema generator pages that rank for this topic, and Noma's own published measurements. Facts, dates and tool descriptions were checked on 2026-11-05. Quotations are as reported in the linked pages, and where we relied on a secondary report we say so. We did not run controlled schema experiments, so this guide makes no claim about how much schema moves AI answers.

What to do next

Generate markup for your five key pages with the free schema generator, validate it, and save a baseline of your prompt answers first. To track the result daily across engines, book a demo or start the 3-day free trial. A card is taken at signup so billing can start on day 3, and nothing is charged if you cancel before then. See also how AI engines choose citations.