IMPLEMENT · Chapter 4

Schema and passage writing for AI citations.

Two layers decide whether a page gets cited inside an AI answer: the structured-data layer that tells the model what the page is and who owns it, and the prose layer that gives the model a quotable paragraph. Get both right and citation share follows. Get either wrong and the page is invisible to AI surfaces no matter how high it ranks.

KEY TAKEAWAYS

  • Article + Person + Organization is the minimum schema stack. Everything else is situational.
  • FAQPage and HowTo still help AI surfaces — just not the classical SERP. Keep them only on pages with real Q/A or real steps.
  • Passage shape beats word count. A 600-word page of three clean passages can out-cite a 2,500-word page of marketing prose.
  • The @id reference graph is what turns three separate schema blocks into one entity-graph the model can attribute to.

Schema decision matrix for 2026

TypeSERP valueGEO valueSMB verdict
ArticleNo rich result by itself, but powers the article carousel and Top Stories eligibility.Strong — gives AI models headline, author, dateModified, and publisher in one block.Ship on every editorial page. Pair with Person and Organization references via @id.
FAQPageDeprecated as a SERP rich result for all sites on May 7 2026 (Google Search Central).Still useful — AI Overviews, AI Mode, ChatGPT, and Perplexity continue to lift Q/A pairs out of FAQPage-marked content.Keep FAQPage when there is real Q/A on the page. Do not invent Q/A just to add it. Do not add it to pages without genuine Q/A — that risks a spammy structured data manual action.
HowToDeprecated as a SERP rich result in September 2023 (still parsed by some engines).Useful — gives AI models a clean step list with images, durations, tools.Use only for genuine step-by-step procedures. Otherwise prefer a numbered list inside Article.
Person + OrganizationPowers Knowledge Panel resolution. The bedrock entity layer.Critical. AI engines weight author and publisher identity heavily when deciding which sources to cite.Ship Person for every author, Organization for the business, with @id references that link the two. Add sameAs to every credible third-party profile.
SpeakableSpecificationOptional add-on inside Article — no standalone rich result.Hints to voice and AI surfaces which passages to read aloud or extract. Low cost, real upside.Add to the TL;DR or key-takeaways section of pillar pages.
BreadcrumbListReplaces URL display in the SERP with a breadcrumb trail.Helps AI engines understand the site hierarchy and group related pages.Ship on every page that lives inside a hub or category structure.

Source for SERP-side changes: Google Search Central FAQ deprecation announcement (May 7 2026) and the HowTo deprecation from September 2023. GEO value notes are from field testing across AIO, AI Mode, ChatGPT, and Perplexity in 2026.

The passage-shape rules

Four rules for writing paragraphs that AI engines will lift.

  1. Answer first. The first sentence of each passage states the answer. The next two or three sentences support it. A model reading just the first sentence should know what the passage is about.
  2. 40 to 80 words. Shorter and there is not enough context to lift. Longer and the model cherry-picks a fragment that may not represent the page's point.
  3. Name the entities. Use full proper nouns at least once per passage. Pronouns and shorthand confuse the model about who or what the passage is talking about when it is quoted out of context.
  4. One verifiable claim per 100 words. A statistic, a date, a named source, a specific number. Pages that hit this density get cited disproportionately because they are the source of facts other pages might also be quoting.

The @id reference graph in practice

On this site, every Article references a single Person node and a single Organization node by stable @id. The pattern looks like this in shorthand.

  • The Organization lives at https://josecabal.com/#org. Defined once, in the site-wide schema. Carries name, logo, address, telephone, and sameAs to LinkedIn, Wikidata, and every directory profile.
  • The Person lives at https://josecabal.com/#jose. Defined once, carries jobTitle, image, knowsAbout, and sameAs to LinkedIn, Wikidata, certifications, and bylined publications.
  • Every Article references both.author: { "@id": "https://josecabal.com/#jose" } and publisher: { "@id": "https://josecabal.com/#org" }.
  • Result: AI engines see one entity graph for the site instead of three disconnected schema blocks. The attribution that appears next to a citation displays consistently as "José Cabal" and "José Cabal Consulting" instead of varying or being missing.
Best for
  • Sites that have a clear author or expert behind the content — the entity graph compounds.
  • Editorial pages, comparison pages, and pillar pages where citation share is the goal.
  • B2B sites in technical categories where AI engines visibly prefer well-structured sources.
Fails when
  • Schema is shipped without an @id graph — each block is read in isolation.
  • FAQPage is added to pages without genuine Q/A in pursuit of a now-deprecated rich result.
  • Pages are written for keyword density instead of passage extraction.
Verify before
  • Run the Article through the Schema.org validator and the Google Rich Results test.
  • Confirm every Article references author and publisher via @id, not inline.
  • Read the first paragraph of any page out of context — does it stand alone?

Frequently asked

Is FAQPage schema still worth shipping after May 2026?

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FAQPage schema is still worth shipping after May 2026, but only when the page actually contains real, user-facing questions and answers. Google deprecated FAQPage as a search results rich result for all sites on May 7, 2026, but the markup itself still helps AI surfaces directly: AI Overviews, AI Mode, ChatGPT, and Perplexity all continue to lift question-and-answer pairs out of FAQPage-marked content when composing an answer. The real mistake is keeping FAQPage schema on a page that has no genuine question-and-answer content behind it, since that now risks a spammy structured data manual action from Google without any corresponding upside left to justify the risk.

What is a passage in GEO terms?

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A passage, in GEO terms, is a self-contained paragraph that answers one specific question and would still make complete sense if an AI engine quoted it entirely on its own, with no surrounding context. A typical passage runs 40 to 80 words: it states the direct answer first, then gives the reasoning behind that answer, then adds any qualifiers or exceptions that matter. The opening paragraph of a page and the first paragraph under each H2 heading should both be written as a passage in this sense, since those are the spots an AI engine is most likely to quote directly.

Does SpeakableSpecification matter for AI search?

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SpeakableSpecification functions as a low-cost hint for AI search rather than a confirmed ranking factor. Adding speakable schema to the summary and key-takeaways sections of a pillar page signals to voice assistants and AI surfaces which specific paragraphs are the best candidates to read aloud or extract preferentially when composing an answer. The implementation cost is minimal, just one small JSON-LD block added to the page, and while the upside is modest rather than dramatic, it is a real, measurable signal rather than a purely theoretical one.

Should every page have HowTo schema for any list of steps?

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Not every page with a list of steps needs HowTo schema. Google deprecated HowTo as a search results rich result back in September 2023, which already removed most of the direct incentive to add it broadly. HowTo schema should be reserved for genuine step-by-step procedures, such as a cooking recipe, a physical repair process, or a software setup sequence, where the steps are the entire point of the content. For most editorial pages that simply include a numbered list as part of a longer explanation, a plain numbered list inside standard Article schema is the right choice, and misapplying HowTo more broadly is a structured-data warning waiting to happen during an audit.

How important is the @id reference graph?

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The @id reference graph is the difference between schema markup that technically exists on a page and schema markup that AI engines and search engines can actually use to compose a clean attribution. Linking Article to its author through an @id reference to a Person entity, and separately linking Article to its publisher through an @id reference to an Organization entity, lets an AI engine understand all three pieces as one connected whole. Without those @id references in place, a search engine or AI crawler sees three separate, disconnected schema blocks on the page; with them properly linked, it sees a single coherent entity graph describing exactly who wrote and published the content.

What is the fastest way to check if my schema is valid?

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The fastest way to check schema validity is to paste the page URL or the raw JSON-LD directly into two separate tools: Google's Rich Results Test, and the general Schema Markup Validator at validator.schema.org. The first tool checks specifically for Google rich result eligibility, which is a narrower standard, while the second checks general Schema.org compliance that applies regardless of which specific search engine or AI system ends up reading the markup. Running both tools matters because a schema block can genuinely pass one of these checks while still failing the other for a different reason.

Should every page carry BreadcrumbList schema?

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Every page should carry BreadcrumbList schema, with essentially no real exception worth making. BreadcrumbList costs almost nothing to add to a page template, helps Google render a visible breadcrumb trail directly inside the search results listing, and gives AI engines a cheap, clearly structured signal of exactly where a given page sits within the site's overall information hierarchy. For these reasons, BreadcrumbList should be built into the base template that every page on a site inherits automatically, rather than something a content author has to remember to add individually, page by page, as new content gets published.

What happens if I mark up FAQPage schema but the questions are not visible on the page?

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Google's structured data guidelines treat hidden FAQPage content as a genuine policy violation rather than a stylistic preference, and this specific mismatch can trigger a manual action for spammy structured data against the whole site, not just the one page. The rule followed on this site is strict: any FAQPage JSON-LD on a page must mirror text a visitor can actually read directly on that page, rendered open by default rather than hidden behind a click-to-expand accordion, so the schema never claims to contain content the page does not genuinely and visibly display.

Official sources

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