Token导航 LogoToken导航TokenDH.com
研究检索需要联网clawhub未标认证来源可访问clear审计提醒

geo-schema-gen地理模式生成

Agent Skill

geo-schema-gen 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

13,448

周安装

566

GitHub Stars

1

下载量

4,709
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:geo-schema-gen(地理模式生成)
来源仓库:https://github.com/geoly-geo/geo-schema-gen
安装命令:
openclaw skills install geo-schema-gen
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install geo-schema-gen

简介

用于生成符合 Schema.org 标准的 JSON-LD 结构化数据,提升 AI 引用率。

  • 支持组织信息、FAQ 页面等多种内容类型的标记创建,增强搜索引擎可读性。
  • 输入内容类型与属性后自动生成验证通过的代码片段,便于嵌入网页。
  • 生成的标记需经实际页面测试以确保正确渲染,避免因格式错误影响 SEO 效果。
  • 注意保护输入数据隐私,尤其涉及用户信息或商业机密时需脱敏处理。

SKILL.md

name
geo-schema-gen
description
Generate complete, validated Schema.org JSON-LD markup for any content type to boost AI citation rates. Creates structured data for Organization, FAQPage, Article, BlogPosting, Product, HowTo, BreadcrumbList, WebSite, VideoObject, and ImageObject schemas. Use whenever the user mentions adding schema markup, generating structured data, creating JSON-LD, implementing Schema.org, optimizing for rich snippets, or wants to improve how AI understands and cites their content. Also trigger for requests about Organization schema, FAQ schema, Article markup, Product schema, or any structured data implementation.

Schema Markup Generator

Methodology by GEOly AI (geoly.ai) — structured data is the language AI uses to understand your brand.

Generate production-ready Schema.org JSON-LD markup for any page type.

Quick Start

Generate schema for your page:

python scripts/generate_schema.py --type <schema-type> [--url <page-url>]

Example:

python scripts/generate_schema.py --type Organization --url example.com
python scripts/generate_schema.py --type FAQPage --file faqs.json

Why Schema Matters for GEO

Structured data helps AI platforms understand:

  • What your content is (entity type)
  • Who created it (author, publisher)
  • When it was published (freshness)
  • How it relates to other content (breadcrumbs)

Without schema, AI systems rely on NLP inference which is less reliable.

Supported Schema Types

TypePriorityBest For
Organization🔴 CriticalHomepage, About page — establishes brand entity
FAQPage🔴 CriticalFAQ/Support pages — feeds AI Q&A answers
Article / BlogPosting🟡 HighBlog posts, news — improves citability
Product🟡 HighProduct/pricing pages — enables shopping citations
HowTo🟡 HighTutorials, guides — feeds step-by-step answers
WebSite🟡 HighHomepage — enables site search in AI
BreadcrumbList🔵 MediumAll pages — improves navigation understanding
VideoObject🔵 MediumVideo pages — enables video citations
ImageObject🔵 MediumImage galleries — enables image citations
LocalBusiness🔵 MediumPhysical locations — local AI search

Full schema reference: See references/schema-types.md

Generation Methods

Method 1: Interactive (Recommended)

python scripts/generate_schema.py --type Organization --interactive

Guided prompts for all required and optional fields.

Method 2: From URL (Auto-Extract)

python scripts/generate_schema.py --type Article --url https://example.com/blog/post

Automatically extracts metadata from the page.

Method 3: From JSON Input

python scripts/generate_schema.py --type FAQPage --file faqs.json

Where faqs.json contains your content data.

Method 4: Batch Generate

python scripts/batch_generate.py sitemap.xml --output schemas/

Generate schemas for all pages in a sitemap.

Validation

Validate generated schema:

python scripts/validate_schema.py schema.json

Checks for:

  • Required fields present
  • Valid Schema.org types
  • Proper JSON-LD syntax
  • Google Rich Results eligibility

Implementation

Add to Your Page

Paste the generated JSON-LD inside your HTML <head>:

<head>
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "Organization",
    ...
  }
  </script>
</head>

Test Before Deploying

  1. Schema.org Validator: https://validator.schema.org
  2. Google Rich Results Test: https://search.google.com/test/rich-results
  3. JSON-LD Playground: https://json-ld.org/playground/

Common Mistakes

Wrong: Multiple conflicting Organization schemas on same page ✅ Right: One comprehensive Organization schema

Wrong: Using http://schema.org (insecure) ✅ Right: Using https://schema.org (secure)

Wrong: Copy-pasting without updating placeholder values ✅ Right: All fields contain actual, accurate data

Advanced Usage

Multiple Schemas per Page

Some pages need multiple schema types. Combine them in an array:

python scripts/generate_schema.py --types Organization,WebSite --url example.com

Nested Entities

Generate related schemas together:

python scripts/generate_schema.py --type Product \
  --with-offer --with-review --with-brand

Custom Properties

Add custom properties not in the generator:

python scripts/generate_schema.py --type Organization \
  --custom '{"knowsAbout": ["SEO", "AI", "Machine Learning"]}'

Output Formats

  • JSON-LD (default): Ready to paste into HTML
  • JSON: Raw structured data
  • HTML: Complete <script> tag
  • Markdown: With explanations

Schema Hierarchy

Understanding how schemas relate:

Organization (top-level entity)
├── WebSite (belongs to Organization)
├── Product (offered by Organization)
│   ├── Offer (pricing for Product)
│   └── Review (of Product)
├── Article (published by Organization)
│   ├── Author (Person or Organization)
│   └── Publisher (Organization)
└── LocalBusiness (subtype of Organization)
    └── Place (physical location)

See Also

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

74.59%
按下载量换算3,512

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills