Fabio Biocchetti

SchemaSense automatically scans your WordPress posts and pages to identify question and answer pairs, then generates proper FAQ schema markup (FAQPage JSON-LD). This structured data helps AI systems and Large Language Models (LLMs) better understand and surface your content in AI-generated responses, while also improving search engine visibility (SEO) with rich snippets in search results.
The plugin also optionally formats existing FAQ blocks as minimalistic accordions (collapsible/expandable), providing an improved user experience for visitors browsing your Q&A content.
<h3>Key Features</h3>
<ul>
<li>GEO, AIO & SEO Ready – Structured data optimized for AI systems, LLMs and traditional SEO</li>
<li>Automatic Detection – Intelligently identifies Q&A patterns in your content</li>
<li>Universal Compatibility – Works with Classic Editor, Gutenberg, and all page builders (Elementor, Beaver Builder, Divi, WPBakery, etc.)</li>
<li>Multiple Formats – Supports headings, paragraphs (including bold), HTML5 details/summary accordions, and Q:/A: format</li>
<li>Multilingual Support – Works with 15+ languages (Latin-based question marks)</li>
<li>Smart Exclusions – Won’t interfere with Yoast or other FAQ plugins that add their own schema</li>
<li>Automatic for Posts – Posts auto-process on save; pages require manual scanning</li>
<li>Separate Batch Processing – Individual scan buttons for posts and pages</li>
<li>Optional Collapsible UI – Enhance Q&A with expand/collapse functionality</li>
<li>Performance Optimized – Schema cached in post meta, not regenerated on every load</li>
</ul>
<h3>How It Works</h3>
The plugin uses multiple detection strategies:
1. FAQ Section Detection (standard HTML – works with all editors/builders) 
* Looks for headings containing FAQ keywords (e.g., “FAQ”, “Frequently Asked Questions”, “Common Questions”) 
* Scans headings and paragraphs within that section for Q&A pairs 
* Works with Classic Editor, Gutenberg, and all page builders
2. HTML5 Details/Summary Detection (modern page builders) 
* Detects accordion widgets using <code><details></code> and <code><summary></code> elements 
* Commonly used by Elementor, Beaver Builder, and other modern page builders
3. Gutenberg Block Detection 
* Native support for WordPress blocks 
* Parses block structure directly for optimal accuracy
<h3>What schema types does the plugin support?</h3>
Currently, the plugin supports FAQ (FAQPage) schema only. It generates JSON-LD structured data with the <code>@type: "FAQPage"</code> format, which includes <code>Question</code> and <code>Answer</code> entities. Support for additional schema types (HowTo, Recipe, Product, etc.) may be added in future versions.
<h3>Does this work with Gutenberg?</h3>
Yes! The plugin supports both Classic Editor and Gutenberg (Block Editor). It can parse both Gutenberg blocks and HTML content.
<h3>How does the plugin detect questions and answers?</h3>
The plugin uses intelligent pattern detection with strict scoping to avoid false positives:
FAQ Section Detection: 
* Looks for headings containing FAQ keywords (e.g., “FAQ”, “FAQs”, “Frequently Asked Questions”, “Common Questions”) 
* Supports 15+ languages with multilingual FAQ heading recognition 
* Once an FAQ section is detected, the plugin scans content within that section only
Question Detection (within FAQ sections only): 
* Heading-based questions: Sub-headings at deeper levels than the FAQ heading (e.g., h3/h4 under an h2 FAQ heading) are treated as questions 
 – No punctuation required 
 – Minimum 5 characters 
* Paragraph-based questions: Paragraphs ending with “?” 
 – Must be between 5-250 characters 
 – Automatically handles bold (<code></code>), italic (<code></code>), or plain text formatting 
 – Example: <code>What is this?</code>
Answer Detection: 
* Any paragraph following a detected question is treated as the answer 
* Multiple consecutive paragraphs are combined into a single answer
Section Boundaries: 
* FAQ section ends when a heading at the same level or higher than the FAQ heading is encountered 
* This prevents false detection of questions in subsequent sections 
* Example: If FAQ section starts with <code><h2></code>, any other <code><h2></code> or <code><h1></code> ends the FAQ section
Additional Format: 
* Q:/A: Format: Explicit “Q:” and “A:” patterns are supported anywhere in content (not limited to FAQ sections)
<h3>Which languages are supported?</h3>
The plugin supports 15+ languages including English, Spanish, French, German, Italian, Portuguese, Dutch, Polish, Russian, Swedish, Danish, Norwegian, Finnish, Czech, and Turkish. All supported languages use the standard Latin question mark (?) for question detection.
<h3>Will it conflict with Yoast SEO or other FAQ plugins?</h3>
No. The plugin automatically detects and skips content managed by Yoast FAQ blocks, Elementor FAQ widgets, and other popular FAQ plugins to prevent duplicate schema markup.
<h3>Can I customize the styling?</h3>
Yes. Override the <code>.ssd-*</code> CSS classes in your theme to customize the collapsible FAQ appearance.
<h3>Which languages are supported for FAQ detection?</h3>
The plugin supports 15+ languages (all use standard Latin question mark <code>?</code> for paragraph-based questions):
<ul>
<li>English</li>
<li>Spanish (Español)</li>
<li>French (Français)</li>
<li>German (Deutsch)</li>
<li>Italian (Italiano)</li>
<li>Portuguese (Português)</li>
<li>Dutch (Nederlands)</li>
<li>Polish (Polski)</li>
<li>Russian (Русский)</li>
<li>Swedish (Svenska)</li>
<li>Danish (Dansk)</li>
<li>Norwegian (Norsk)</li>
<li>Finnish (Suomi)</li>
<li>Czech (Čeština)</li>
<li>Turkish (Türkçe)</li>
</ul>
Note: Languages using non-Latin question marks (Arabic, Greek, Hebrew, CJK languages) are not currently supported for paragraph-based question detection.

SchemaSense – Smart Structured Data

Auto-detects FAQ content and generates valid JSON-LD schema for LLMs, GEO (Generative Engine Optimization), and SEO.

Steve Grunwell

Structured data allows developers and publishers to mark up content in a way that it’s easy for machines to understand. Proper use of structured data <a href="https://developers.google.com/search/docs/guides/intro-structured-data" rel="nofollow ugc">enables third-parties like Google to parse reviews, event data, and contact information in meaningful ways</a>, ensuring you’re getting the most “bang” out of your publishing buck.
Fortunately, the major players in the Search game, including Google, Microsoft, Yahoo!, and Yandex) came together in the early 2010s to form <a href="http://schema.org/docs/about.html" rel="nofollow ugc">Schema.org</a>, a collaborative, community-driven standard for structured data.
With the major search engines and communities behind it, we’re all marking up everything with appropriate structured data now, right?
Unfortunately, the process of implementing Schema.org in a site — especially one driven by dynamic content — is less than straightforward. <a href="https://wordpress.org" rel="ugc">WordPress</a>, for instance, <a href="https://ma.tt/2015/11/seventy-five-to-go/" rel="nofollow ugc">powers roughly a quarter of the web</a>, but implementing structured data across hundreds of thousands of themes would be a nightmare.
Or, at least it would be, if it weren’t for Schemify.
<h4>What does Schemify do?</h4>
There are two approaches to adding structured data to a website: via the markup or <a href="http://json-ld.org/" rel="nofollow ugc">JSON for Linking Data (JSON-LD)</a>.
Consider the following author information, which might appear at the bottom of a blog post:
<pre><code> 
 
 <a href="https://stevegrunwell.com" rel="author nofollow ugc">Steve Grunwell</a>
 Steve is the Director of Technology at Growella. When he's not working, you can find him speaking at conferences, roasting coffee, or spending time with his wife and daughter
 
</code></pre>
If I wanted this information to use Schema.org markup, it would look something like this:
<pre><code> 
 
 <a href="https://stevegrunwell.com" rel="author nofollow ugc">Steve Grunwell</a>
 Steve is the Director of Technology at Growella. When he's not working, you can find him speaking at conferences, roasting coffee, or spending time with his wife and daughter
 
</code></pre>
While that may not seem like a lot of work, that’s still a lot of extra markup being added. Even worse, a lot of that markup might normally be generated by WordPress helper functions like <a href="https://developer.wordpress.org/reference/functions/get_avatar/" rel="nofollow ugc"><code>get_avatar()</code></a>, which means extra work to get the necessary <code>itemprop</code> attribute in place.
Fortunately, the other approach for adding structured data is much more straight-forward in a theme, as it’s simply a JSON-LD object:
<pre><code> 
 {
 "@context": "http://schema.org",
 "@type": "Person",
 "name": "Steve Grunwell",
 "url": "https://stevegrunwell.com",
 "image": "https://secure.gravatar.com/avatar/88ea4e10ed968136228545d7112d82cb?s=200",
 "description": "Steve is the Director of Technology at Growella. When he's not working, you can find him speaking at conferences, roasting coffee, or spending time with his wife and daughter"
 }
 
</code></pre>
We simply generate this JSON-LD object and append it to our document’s <code><body></code>. When Google or anyone else who supports JSON-LD structured data parses our page, they can immediately understand that Steve Grunwell is a person and determine his website, avatar, and biography.
The best part? There’s no need to change the markup within our theme!
Schemify aims to automate the generation of JSON-LD objects for content within WordPress. Its flexible structure and reasonable defaults enables drop-in support for structured data, regardless of the WordPress theme.

Schemify

Adding schema to a site no longer has to be an afterthought. This plugin took our structured data game to the next level and I look forward to seeing how it helps improve our search ranking!

As advertised

Automatically generate Schema.org JSON-LD markup for WordPress content.

SchemaSense – Smart Structured Data vs Schemify