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GEO Schema & Structured Data

GEO Schema与结构化数据

Purpose

目的

Structured data is the primary machine-readable signal that tells AI systems what an entity IS, what it does, and how it connects to other entities. While schema markup has traditionally been about earning Google rich results, its role in GEO is fundamentally different: structured data is how AI models understand and trust your entity. A complete entity graph in structured data dramatically increases citation probability across all AI search platforms.

结构化数据是告诉AI系统某个实体是什么、做什么以及如何与其他实体关联的主要机器可读信号。虽然Schema标记传统上是为了获取Google富媒体结果，但它在GEO中的作用有着根本不同：结构化数据是AI模型理解并信任你的实体的方式。完整的结构化数据实体图谱能显著提升在所有AI搜索平台上的被引用概率。

How to Use This Skill

如何使用本技能

Fetch the target page HTML using curl or WebFetch
Detect all existing structured data (JSON-LD, Microdata, RDFa)
Validate detected schemas against Schema.org specifications
Identify missing recommended schemas based on business type
Generate ready-to-use JSON-LD code blocks
Output GEO-SCHEMA-REPORT.md

使用curl或WebFetch获取目标页面的HTML
检测所有现有结构化数据（JSON-LD、Microdata、RDFa）
对照Schema.org规范验证检测到的Schema
根据业务类型识别缺失的推荐Schema
生成可直接使用的JSON-LD代码块
输出GEO-SCHEMA-REPORT.md

Step 1: Detection

步骤1：检测

Scan for JSON-LD

扫描JSON-LD

Look for

<script type="application/ld+json">

blocks in the HTML. Parse each block as JSON. A page may contain multiple JSON-LD blocks — collect all of them.

在HTML中查找

<script type="application/ld+json">

代码块。将每个代码块解析为JSON。一个页面可能包含多个JSON-LD代码块——请收集所有代码块。

Scan for Microdata

扫描Microdata

Look for elements with

itemscope

itemtype

, and

itemprop

attributes. Map the hierarchy of nested items. Note: Microdata is harder for AI crawlers to parse than JSON-LD. Flag a recommendation to migrate to JSON-LD if Microdata is the only format found.

查找带有

itemscope

、

itemtype

和

itemprop

属性的元素。映射嵌套项的层级结构。注意：AI爬虫解析Microdata的难度高于JSON-LD。如果仅发现Microdata格式，标记为建议迁移至JSON-LD。

Scan for RDFa

扫描RDFa

Look for elements with

typeof

property

, and

vocab

attributes. Similar to Microdata — recommend migration to JSON-LD.

查找带有

typeof

、

property

和

vocab

属性的元素。与Microdata类似——建议迁移至JSON-LD。

Priority Order

优先级顺序

JSON-LD is the strongly recommended format for GEO. Google, Bing, and AI platforms all process JSON-LD most reliably. If the site uses Microdata or RDFa exclusively, flag this as a high-priority migration.

JSON-LD是GEO的强烈推荐格式。Google、Bing和AI平台都能最可靠地处理JSON-LD。如果网站仅使用Microdata或RDFa，将其标记为高优先级迁移项。

Step 2: Validation

步骤2：验证

For each detected schema block, validate:

Valid JSON: Is the JSON-LD syntactically valid? Check for trailing commas, unquoted keys, malformed strings.
Valid @type: Does the
```
@type
```
match a recognized Schema.org type? Check against https://schema.org/docs/full.html.
Required Properties: Does the schema include all required properties for its type? (See per-type requirements below.)
Recommended Properties: Does the schema include recommended properties that increase AI discoverability?
sameAs Links: Does the schema include
```
sameAs
```
properties linking to other platform presences?
URL Validity: Do all URLs in the schema resolve (not 404)?
Nesting: Is the schema properly nested (e.g., author inside Article, address inside Organization)?
Rendering Method: Is the JSON-LD in the server-rendered HTML or injected via JavaScript? Per Google's December 2025 guidance, JavaScript-injected structured data may face delayed processing. Flag any schema that requires JS execution.

对于每个检测到的Schema代码块，验证以下内容：

有效的JSON：JSON-LD在语法上是否有效？检查是否存在尾随逗号、未加引号的键、格式错误的字符串。
有效的@type：
```
@type
```
是否与Schema.org认可的类型匹配？对照https://schema.org/docs/full.html检查。
必填属性：Schema是否包含其类型的所有必填属性？（见下文各类型的要求。）
推荐属性：Schema是否包含能提升AI可发现性的推荐属性？
sameAs链接：Schema是否包含
```
sameAs
```
属性，链接至其他平台的账号？
URL有效性：Schema中的所有URL是否均可正常访问（非404）？
嵌套结构：Schema是否正确嵌套（例如，Article内包含author，Organization内包含address）？
渲染方式：JSON-LD是在服务器渲染的HTML中，还是通过JavaScript注入？根据Google 2025年12月的指南，通过JavaScript注入的结构化数据可能会延迟处理。标记所有需要JS执行的Schema。

Step 3: Schema Types for GEO

步骤3：适用于GEO的Schema类型

Organization (CRITICAL — every business site)

Organization（关键——所有商业网站必备）

Essential for entity recognition across all AI platforms. This is how AI models identify WHAT the business is.

Required properties:

```
@type
```
: "Organization" (or subtype: Corporation, LocalBusiness, etc.)
```
name
```
: Official business name
```
url
```
: Official website URL
```
logo
```
: URL to logo image (ImageObject preferred)

Recommended properties for GEO:

```
sameAs
```
: Array of ALL platform URLs (see sameAs strategy below)
```
description
```
: 1-2 sentence description of the organization
```
foundingDate
```
: ISO 8601 date
```
founder
```
: Person schema
```
address
```
: PostalAddress schema
```
contactPoint
```
: ContactPoint with telephone, email, contactType
```
areaServed
```
: Geographic area
```
numberOfEmployees
```
: QuantitativeValue
```
industry
```
: Text or DefinedTerm
```
award
```
: Array of awards received
```
knowsAbout
```
: Array of topics the organization is expert in (strong GEO signal)

对所有AI平台的实体识别至关重要。AI模型通过它识别企业的身份。

必填属性：

```
@type
```
: "Organization"（或其子类型：Corporation、LocalBusiness等）
```
name
```
: 企业官方名称
```
url
```
: 企业官方网站URL
```
logo
```
: 标志图片的URL（优先使用ImageObject）

GEO推荐属性：

```
sameAs
```
: 所有平台URL的数组（见下文sameAs策略）
```
description
```
: 1-2句话的企业介绍
```
foundingDate
```
: ISO 8601格式日期
```
founder
```
: Person Schema
```
address
```
: PostalAddress Schema
```
contactPoint
```
: 包含telephone、email、contactType的ContactPoint
```
areaServed
```
: 服务地理区域
```
numberOfEmployees
```
: QuantitativeValue
```
industry
```
: 文本或DefinedTerm
```
award
```
: 所获荣誉的数组
```
knowsAbout
```
: 企业擅长领域的数组（强GEO信号）

LocalBusiness (for businesses with physical locations)

LocalBusiness（适用于有实体门店的企业）

Extends Organization. Critical for local AI search results and Google Gemini.

Additional required properties:

```
address
```
: Full PostalAddress
```
telephone
```
: Phone number
```
openingHoursSpecification
```
: Operating hours

Recommended for GEO:

```
geo
```
: GeoCoordinates (latitude, longitude)
```
priceRange
```
: Price indicator
```
aggregateRating
```
: AggregateRating schema
```
review
```
: Array of Review schemas
```
hasMap
```
: URL to Google Maps

继承自Organization。对本地AI搜索结果和Google Gemini至关重要。

额外必填属性：

```
address
```
: 完整的PostalAddress
```
telephone
```
: 电话号码
```
openingHoursSpecification
```
: 营业时间

GEO推荐属性：

```
geo
```
: GeoCoordinates（纬度、经度）
```
priceRange
```
: 价格区间标识
```
aggregateRating
```
: AggregateRating Schema
```
review
```
: Review Schema数组
```
hasMap
```
: Google Maps的URL

Article + Author (CRITICAL for publishers)

Article + Author（关键——适用于内容发布者）

The Author schema is one of the strongest E-E-A-T signals for AI platforms.

Article required:

```
@type
```
: "Article" (or NewsArticle, BlogPosting, TechArticle)
```
headline
```
: Article title
```
datePublished
```
: ISO 8601
```
dateModified
```
: ISO 8601 (critical for freshness signals)
```
author
```
: Person or Organization schema
```
publisher
```
: Organization schema with logo
```
image
```
: Representative image

Author (Person) required for GEO:

```
name
```
: Full name
```
url
```
: Author page URL on the site
```
sameAs
```
: LinkedIn, Twitter, personal site, Google Scholar, ORCID
```
jobTitle
```
: Professional title
```
worksFor
```
: Organization schema
```
knowsAbout
```
: Array of expertise areas
```
alumniOf
```
: Educational institutions
```
award
```
: Professional awards

Author Schema是AI平台最强的E-E-A-T信号之一。

Article必填属性：

```
@type
```
: "Article"（或NewsArticle、BlogPosting、TechArticle）
```
headline
```
: 文章标题
```
datePublished
```
: ISO 8601格式日期
```
dateModified
```
: ISO 8601格式日期（对新鲜度信号至关重要）
```
author
```
: Person或Organization Schema
```
publisher
```
: 带有logo的Organization Schema
```
image
```
: 代表性图片

GEO所需的Author（Person）属性：

```
name
```
: 全名
```
url
```
: 网站上的作者页面URL
```
sameAs
```
: LinkedIn、Twitter、个人网站、Google Scholar、ORCID
```
jobTitle
```
: 职业头衔
```
worksFor
```
: Organization Schema
```
knowsAbout
```
: 专业领域数组
```
alumniOf
```
: 毕业院校
```
award
```
: 所获专业荣誉

Product (for e-commerce)

Product（适用于电商）

Required:

```
name
```
,
```
description
```
,
```
image
```
```
offers
```
: Offer with price, priceCurrency, availability
```
brand
```
: Brand schema
```
sku
```
or
```
gtin
```
/
```
mpn
```

Recommended for GEO:

```
aggregateRating
```
: AggregateRating
```
review
```
: Array of individual reviews
```
category
```
: Product category
```
material
```
,
```
weight
```
,
```
width
```
,
```
height
```
(where applicable)

必填属性：

```
name
```
、
```
description
```
、
```
image
```
```
offers
```
: 包含price、priceCurrency、availability的Offer
```
brand
```
: Brand Schema
```
sku
```
或
```
gtin
```
/
```
mpn
```

GEO推荐属性：

```
aggregateRating
```
: AggregateRating
```
review
```
: 单个Review的数组
```
category
```
: 产品类别
```
material
```
、
```
weight
```
、
```
width
```
、
```
height
```
（适用时）

FAQPage

Status as of 2024: Google restricts FAQ rich results to government and health sites. However, the FAQPage schema still serves GEO purposes — AI platforms parse FAQ structured data for question-answer extraction. Implement it for AI readability even though rich results may not appear.

Structure:

```
@type
```
: "FAQPage"
```
mainEntity
```
: Array of Question schemas, each with
```
acceptedAnswer
```
containing an Answer schema

2024年现状：Google将FAQ富媒体结果限制为政府和医疗网站使用。但FAQPage Schema仍对GEO有用——AI平台会解析FAQ结构化数据以提取问答内容。即使无法获得富媒体结果，也应实现该Schema以提升AI可读性。

结构：

```
@type
```
: "FAQPage"
```
mainEntity
```
: Question Schema数组，每个Question包含带有Answer Schema的
```
acceptedAnswer
```

SoftwareApplication (for SaaS)

SoftwareApplication（适用于SaaS）

Required:

```
name
```
,
```
description
```
```
applicationCategory
```
: e.g., "BusinessApplication"
```
operatingSystem
```
: Supported platforms
```
offers
```
: Pricing

Recommended for GEO:

```
aggregateRating
```
: User ratings
```
featureList
```
: Array of features (strong citation signal)
```
screenshot
```
: Screenshots
```
softwareVersion
```
: Current version
```
releaseNotes
```
: Link to changelog

必填属性：

```
name
```
、
```
description
```
```
applicationCategory
```
: 例如"BusinessApplication"
```
operatingSystem
```
: 支持的平台
```
offers
```
: 定价信息

GEO推荐属性：

```
aggregateRating
```
: 用户评分
```
featureList
```
: 功能数组（强引用信号）
```
screenshot
```
: 截图
```
softwareVersion
```
: 当前版本
```
releaseNotes
```
: 更新日志链接

WebSite + SearchAction (for sitelinks search box)

WebSite + SearchAction（适用于站点链接搜索框）

Structure:

json

{
  "@type": "WebSite",
  "name": "Site Name",
  "url": "https://example.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": {
      "@type": "EntryPoint",
      "urlTemplate": "https://example.com/search?q={search_term_string}"
    },
    "query-input": "required name=search_term_string"
  }
}

结构：

json

{
  "@type": "WebSite",
  "name": "Site Name",
  "url": "https://example.com",
  "potentialAction": {
    "@type": "SearchAction",
    "target": {
      "@type": "EntryPoint",
      "urlTemplate": "https://example.com/search?q={search_term_string}"
    },
    "query-input": "required name=search_term_string"
  }
}

Person (standalone — for personal brands, authors, thought leaders)

Person（独立使用——适用于个人品牌、作者、意见领袖）

Use as a standalone schema on About/Bio pages. This builds the entity graph for individual expertise.

Required:

name

url

Recommended for GEO:

sameAs

jobTitle

worksFor

knowsAbout

alumniOf

award

description

image

在关于/简介页面作为独立Schema使用。用于构建个人专业领域的实体图谱。

必填属性：

name

、

url

GEO推荐属性：

sameAs

、

jobTitle

、

worksFor

、

knowsAbout

、

alumniOf

、

award

、

description

、

image

speakable Property (for voice/AI assistants)

speakable属性（适用于语音/AI助手）

The

speakable

property marks specific sections of content as particularly suitable for voice and AI assistant consumption. Add to Article or WebPage schemas.

json

{
  "@type": "Article",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".article-summary", ".key-takeaway"]
  }
}

This signals to AI assistants which passages are the best candidates for citation or reading aloud.

speakable

属性标记内容中特别适合语音和AI助手读取的特定部分。添加至Article或WebPage Schema。

json

{
  "@type": "Article",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".article-summary", ".key-takeaway"]
  }
}

该属性向AI助手示意哪些段落是引用或朗读的最佳候选内容。

Step 4: Deprecated/Changed Schemas to Flag

步骤4：需标记的已弃用/变更Schema

Schema	Status	Note
HowTo	Rich results deprecated Aug 2023	Still useful for AI parsing, but do not promise rich results
FAQPage	Restricted to govt/health Aug 2023	Still useful for AI parsing (see above)
SpecialAnnouncement	Deprecated 2023	Was for COVID; remove if still present
CourseInfo	Replaced by Course updates 2024	Use updated Course schema properties
VideoObject `contentUrl`	Changed behavior 2024	Must point to actual video file, not page URL
Review snippet	Stricter enforcement 2024	Self-serving reviews on product pages may not display

Flag any deprecated schemas found and recommend replacements.

Schema	状态	说明
HowTo	富媒体结果于2023年8月弃用	仍对AI解析有用，但无法获得富媒体结果
FAQPage	2023年8月限制为政府/医疗网站使用	仍对AI解析有用（见上文）
SpecialAnnouncement	2023年弃用	原用于新冠疫情相关内容；若仍存在请移除
CourseInfo	2024年被Course更新替代	使用更新后的Course Schema属性
VideoObject `contentUrl`	2024年行为变更	必须指向实际视频文件，而非页面URL
Review摘要	2024年执行更严格	产品页面上的自夸式评论可能不会显示

标记所有检测到的已弃用Schema并建议替换方案。

Step 5: sameAs Strategy (CRITICAL for Entity Recognition)

步骤5：sameAs策略（实体识别的关键）

The

sameAs

property is the single most important structured data property for GEO. It tells AI systems: "This entity on my website is the SAME entity as these profiles elsewhere." This creates the entity graph that AI platforms use to verify, trust, and cite sources.

sameAs

属性是对GEO最重要的结构化数据属性。它告诉AI系统：“我网站上的这个实体与其他平台上的这些账号是同一个实体。”这会构建AI平台用于验证、信任和引用来源的实体图谱。

sameAs Audit Process

sameAs审计流程

Collect all known web presences for the entity
Check that each URL resolves (not 404 or redirected)
Verify the Organization/Person schema includes ALL of them
Check that the information on each platform is consistent (name, description, founding date, etc.)
Flag any platforms where the entity should have a presence but does not

收集该实体的所有已知网络账号
检查每个URL是否可正常访问（非404或重定向）
验证Organization/Person Schema是否包含所有这些链接
检查每个平台上的信息是否一致（名称、介绍、成立日期等）
标记该实体应拥有账号但实际未有的平台

Step 6: JSON-LD Generation

步骤6：JSON-LD生成

Based on the detected business type, generate ready-to-paste JSON-LD blocks. Always generate:

Organization or Person (depending on entity type) — always
WebSite with SearchAction — always for the homepage
Business-type-specific — Article for publishers, Product for e-commerce, LocalBusiness for local, SoftwareApplication for SaaS
BreadcrumbList — for any page deeper than homepage

根据检测到的业务类型，生成可直接粘贴的JSON-LD代码块。始终生成以下内容：

Organization或Person（根据实体类型）——必备
带有SearchAction的WebSite——首页必备
特定业务类型的Schema——内容发布者用Article，电商用Product，本地企业用LocalBusiness，SaaS用SoftwareApplication
BreadcrumbList——所有非首页的页面必备

Generation Rules

生成规则

Use the
```
@graph
```
pattern to include multiple schemas in one JSON-LD block
All URLs must be absolute (not relative)
Include
```
@id
```
properties for cross-referencing between schemas
Use ISO 8601 for all dates
Include
```
speakable
```
on Article schemas with CSS selectors pointing to key content sections
Place JSON-LD in
```
<head>
```
section — NOT injected via JavaScript

使用
```
@graph
```
模式在一个JSON-LD代码块中包含多个Schema
所有URL必须是绝对路径（而非相对路径）
包含
```
@id
```
属性以实现Schema间的交叉引用
所有日期使用ISO 8601格式
在Article Schema中包含
```
speakable
```
，并使用CSS选择器指向关键内容区域
将JSON-LD放置在
```
<head>
```
部分——不要通过JavaScript注入

Template: Organization with Full GEO Signals

模板：带有完整GEO信号的Organization

json

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Company Name",
  "url": "https://example.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://example.com/logo.png",
    "width": 600,
    "height": 60
  },
  "description": "Concise description of what the company does.",
  "foundingDate": "2020-01-15",
  "founder": {
    "@type": "Person",
    "name": "Founder Name",
    "sameAs": "https://www.linkedin.com/in/founder"
  },
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "City",
    "addressRegion": "State",
    "postalCode": "12345",
    "addressCountry": "US"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "telephone": "+1-555-555-5555",
    "contactType": "customer service",
    "email": "support@example.com"
  },
  "sameAs": [
    "https://en.wikipedia.org/wiki/Company_Name",
    "https://www.wikidata.org/wiki/Q12345",
    "https://www.linkedin.com/company/company-name",
    "https://www.youtube.com/@companyname",
    "https://twitter.com/companyname",
    "https://github.com/companyname",
    "https://www.crunchbase.com/organization/company-name"
  ],
  "knowsAbout": [
    "Topic 1",
    "Topic 2",
    "Topic 3"
  ]
}

json

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Company Name",
  "url": "https://example.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://example.com/logo.png",
    "width": 600,
    "height": 60
  },
  "description": "Concise description of what the company does.",
  "foundingDate": "2020-01-15",
  "founder": {
    "@type": "Person",
    "name": "Founder Name",
    "sameAs": "https://www.linkedin.com/in/founder"
  },
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main St",
    "addressLocality": "City",
    "addressRegion": "State",
    "postalCode": "12345",
    "addressCountry": "US"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "telephone": "+1-555-555-5555",
    "contactType": "customer service",
    "email": "support@example.com"
  },
  "sameAs": [
    "https://en.wikipedia.org/wiki/Company_Name",
    "https://www.wikidata.org/wiki/Q12345",
    "https://www.linkedin.com/company/company-name",
    "https://www.youtube.com/@companyname",
    "https://twitter.com/companyname",
    "https://github.com/companyname",
    "https://www.crunchbase.com/organization/company-name"
  ],
  "knowsAbout": [
    "Topic 1",
    "Topic 2",
    "Topic 3"
  ]
}

Scoring Rubric (0-100)

评分标准（0-100分）

Criterion	Points	How to Score
Organization/Person schema present and complete	15	15 if full, 10 if basic, 0 if none
sameAs links (5+ platforms)	15	3 per valid sameAs link, max 15
Article schema with author details	10	10 if full author schema, 5 if name only, 0 if none
Business-type-specific schema present	10	10 if complete, 5 if partial, 0 if missing
WebSite + SearchAction	5	5 if present, 0 if not
BreadcrumbList on inner pages	5	5 if present, 0 if not
JSON-LD format (not Microdata/RDFa)	5	5 if JSON-LD, 3 if mixed, 0 if only Microdata/RDFa
Server-rendered (not JS-injected)	10	10 if in HTML source, 5 if JS but in head, 0 if dynamic JS
speakable property on articles	5	5 if present, 0 if not
Valid JSON + valid Schema.org types	10	10 if no errors, 5 if minor issues, 0 if major errors
knowsAbout property on Organization/Person	5	5 if present with 3+ topics, 0 if missing
No deprecated schemas present	5	5 if clean, 0 if deprecated schemas found

评估项	分值	评分方式
存在完整的Organization/Person Schema	15	完整得15分，基础版得10分，无得0分
sameAs链接（5个及以上平台）	15	每个有效链接得3分，最高15分
带有作者详情的Article Schema	10	包含完整作者Schema得10分，仅含姓名得5分，无得0分
存在特定业务类型的Schema	10	完整得10分，部分完整得5分，缺失得0分
WebSite + SearchAction	5	存在得5分，无得0分
内页包含BreadcrumbList	5	存在得5分，无得0分
JSON-LD格式（非Microdata/RDFa）	5	JSON-LD得5分，混合格式得3分，仅Microdata/RDFa得0分
服务器渲染（非JS注入）	10	在HTML源码中得10分，JS注入但在head中得5分，动态JS得0分
Article包含speakable属性	5	存在得5分，无得0分
有效的JSON + 有效的Schema.org类型	10	无错误得10分， minor问题得5分，重大错误得0分
Organization/Person包含knowsAbout属性	5	包含3个及以上领域得5分，缺失得0分
无已弃用Schema	5	无得5分，存在得0分

Output Format

输出格式

Generate GEO-SCHEMA-REPORT.md with:

markdown

undefined

生成GEO-SCHEMA-REPORT.md，内容如下：

markdown

undefined

GEO Schema & Structured Data Report — [Domain]

GEO Schema与结构化数据报告 —— [域名]

Date: [Date]

日期：[日期]

Schema Score: XX/100

Schema评分：XX/100

Detected Schemas

检测到的Schema

Page	Schema Type	Format	Status	Issues
/	Organization	JSON-LD	Valid	Missing sameAs
/blog/post-1	Article	JSON-LD	Valid	No author schema

页面	Schema类型	格式	状态	问题
/	Organization	JSON-LD	有效	缺失sameAs
/blog/post-1	Article	JSON-LD	有效	无作者Schema

Validation Results

验证结果

[List each schema with pass/fail per property]

[列出每个Schema的各属性通过/失败情况]

Missing Recommended Schemas

缺失的推荐Schema

[List schemas that should be present based on business type but are not]

[列出根据业务类型应存在但缺失的Schema]

sameAs Audit

sameAs审计

Platform	URL	Status
Wikipedia	[URL or "Not found"]	Present/Missing
LinkedIn	[URL or "Not found"]	Present/Missing
[Continue for all recommended platforms]

平台	URL	状态
Wikipedia	[URL或"未找到"]	存在/缺失
LinkedIn	[URL或"未找到"]	存在/缺失
[继续列出所有推荐平台]

Generated JSON-LD Code

生成的JSON-LD代码

[Ready-to-paste JSON-LD blocks for each missing or incomplete schema]

[为每个缺失或不完整的Schema提供可直接粘贴的JSON-LD代码块]

Implementation Notes

实施说明

Where to place each JSON-LD block
Server-rendering requirements
Testing with Google Rich Results Test and Schema.org Validator

undefined

每个JSON-LD代码块的放置位置
服务器渲染要求
使用Google Rich Results Test和Schema.org Validator进行测试

undefined

geo-schema

Original

Translation

GEO Schema & Structured Data

GEO Schema与结构化数据

Purpose

目的

How to Use This Skill

如何使用本技能

Step 1: Detection

步骤1：检测

Scan for JSON-LD

扫描JSON-LD

Scan for Microdata

扫描Microdata

Scan for RDFa

扫描RDFa

Priority Order

优先级顺序

Step 2: Validation

步骤2：验证

Step 3: Schema Types for GEO

步骤3：适用于GEO的Schema类型

Organization (CRITICAL — every business site)

Organization（关键——所有商业网站必备）

LocalBusiness (for businesses with physical locations)

LocalBusiness（适用于有实体门店的企业）

Article + Author (CRITICAL for publishers)

Article + Author（关键——适用于内容发布者）

Product (for e-commerce)

Product（适用于电商）

FAQPage

FAQPage

SoftwareApplication (for SaaS)

SoftwareApplication（适用于SaaS）

WebSite + SearchAction (for sitelinks search box)

WebSite + SearchAction（适用于站点链接搜索框）

Person (standalone — for personal brands, authors, thought leaders)

Person（独立使用——适用于个人品牌、作者、意见领袖）

speakable Property (for voice/AI assistants)

speakable属性（适用于语音/AI助手）

Step 4: Deprecated/Changed Schemas to Flag

步骤4：需标记的已弃用/变更Schema

Step 5: sameAs Strategy (CRITICAL for Entity Recognition)

步骤5：sameAs策略（实体识别的关键）

Recommended sameAs Links (in priority order)

推荐的sameAs链接（按优先级排序）

sameAs Audit Process

sameAs审计流程

Step 6: JSON-LD Generation

步骤6：JSON-LD生成

Generation Rules

生成规则

Template: Organization with Full GEO Signals

模板：带有完整GEO信号的Organization

Scoring Rubric (0-100)

评分标准（0-100分）

Output Format

输出格式

GEO Schema & Structured Data Report — [Domain]

GEO Schema与结构化数据报告 —— [域名]

Schema Score: XX/100

Schema评分：XX/100

Detected Schemas

检测到的Schema

Validation Results

验证结果

Missing Recommended Schemas

缺失的推荐Schema

sameAs Audit

sameAs审计

Generated JSON-LD Code

生成的JSON-LD代码

Implementation Notes

实施说明