[WordPress] 外掛分享: SchemaSense – Smart Structured Data

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WordPress 5.0+ PHP 7.4+ v1.1.5 上架:2026-01-08

內容目錄

內容簡介

<b>外掛介紹總結:</b>
<p>SchemaSense 可自動掃描您的 WordPress 文章和頁面,識別問題和答案對,並生成適當的 FAQ 結構標記(FAQPage JSON-LD)。這種結構化數據有助於 AI 系統和大型語言模型(LLMs)更好地理解和呈現您的內容在 AI 生成的回應中,同時還通過搜尋結果中的豐富摘要來改善搜索引擎的可見性(SEO)。</p>
<p>此外,該插件還可以將現有的問答區塊格式化為極簡的手風琴(折疊/展開),提供給瀏覽您的問答內容的訪客更好的用戶體驗。</p>

<b>問題與答案:</b>
<ul>
<li><b>外掛支援哪些語言?</b></li>
<p>此外掛支援包括英文、西班牙文、法文、德文、義大利文、葡萄牙文、荷蘭文、波蘭文、俄文、瑞典文、丹麥文、挪威文、芬蘭文、捷克文和土耳其文在內的 15 多種語言。所有支援的語言使用標準拉丁字母問號(?)來進行問題檢測。</p>

<li><b>外掛支援哪些模式?</b></li>
<p>目前,此外掛僅支援 FAQ(FAQPage)模式。它以 @type: “FAQPage” 格式生成 JSON-LD 結構化數據,包括問題和答案實體。在未來版本中可能會添加對其他模式類型(如 HowTo、Recipe、Product 等)的支援。</p>

<li><b>此外掛是否與 Gutenberg 相容?</b></li>
<p>是的!此外掛支援經典編輯器和古鐘山(區塊編輯器)。它可以解析古鐘山區塊和 HTML 內容。</p>
</ul>

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⬇ 下載最新版 (v1.1.5) 或搜尋安裝

① 下載 ZIP → 後台「外掛 › 安裝外掛 › 上傳外掛」
② 後台搜尋「SchemaSense – Smart Structured Data」→ 直接安裝(推薦)
📦 歷史版本下載

原文外掛簡介

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.
Key Features

GEO, AIO & SEO Ready – Structured data optimized for AI systems, LLMs and traditional SEO
Automatic Detection – Intelligently identifies Q&A patterns in your content
Universal Compatibility – Works with Classic Editor, Gutenberg, and all page builders (Elementor, Beaver Builder, Divi, WPBakery, etc.)
Multiple Formats – Supports headings, paragraphs (including bold), HTML5 details/summary accordions, and Q:/A: format
Multilingual Support – Works with 15+ languages (Latin-based question marks)
Smart Exclusions – Won’t interfere with Yoast or other FAQ plugins that add their own schema
Automatic for Posts – Posts auto-process on save; pages require manual scanning
Separate Batch Processing – Individual scan buttons for posts and pages
Optional Collapsible UI – Enhance Q&A with expand/collapse functionality
Performance Optimized – Schema cached in post meta, not regenerated on every load

How It Works
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

and

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
What schema types does the plugin support?
Currently, the plugin supports FAQ (FAQPage) schema only. It generates JSON-LD structured data with the @type: "FAQPage" format, which includes Question and Answer entities. Support for additional schema types (HowTo, Recipe, Product, etc.) may be added in future versions.
Does this work with Gutenberg?
Yes! The plugin supports both Classic Editor and Gutenberg (Block Editor). It can parse both Gutenberg blocks and HTML content.
How does the plugin detect questions and answers?
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 (), italic (), or plain text formatting
– Example:

What is this?

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

, any other

or

ends the FAQ section
Additional Format:
* Q:/A: Format: Explicit “Q:” and “A:” patterns are supported anywhere in content (not limited to FAQ sections)
Which languages are supported?
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.
Will it conflict with Yoast SEO or other FAQ plugins?
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.
Can I customize the styling?
Yes. Override the .ssd-* CSS classes in your theme to customize the collapsible FAQ appearance.
Which languages are supported for FAQ detection?
The plugin supports 15+ languages (all use standard Latin question mark ? for paragraph-based questions):

English
Spanish (Español)
French (Français)
German (Deutsch)
Italian (Italiano)
Portuguese (Português)
Dutch (Nederlands)
Polish (Polski)
Russian (Русский)
Swedish (Svenska)
Danish (Dansk)
Norwegian (Norsk)
Finnish (Suomi)
Czech (Čeština)
Turkish (Türkçe)

Note: Languages using non-Latin question marks (Arabic, Greek, Hebrew, CJK languages) are not currently supported for paragraph-based question detection.

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