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Agent Skill · 研究检索

kostja94-schema-markup(kostja94 架构标记)

kostja94-schema-markup 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。

kostja94-schema-markup 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,985。

总安装 5,821周安装 245GitHub Stars 公开资料未说明下载 2,038核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.3.0

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:kostja94-schema-markup(kostja94 架构标记)
来源仓库:https://github.com/kostja94/kostja94-schema-markup
安装命令:
openclaw skills install kostja94-schema-markup
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 kostja94-schema-markup

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

kostja94-schema-markup 添加或优化 Schema.org 结构化数据(JSON-LD),增强搜索引擎富摘要展示能力。适用于电商、新闻、食谱等内容类型提升 SERP 点击率。自动检测页面元素并生成对应 schema 类型代码块。

错误标记可能导致惩罚,建议通过 Google Rich Results Test 验证后再上线。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install kostja94-schema-markup;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

kostja94-schema-markup 怎么安装?

在终端执行 openclaw skills install kostja94-schema-markup。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

kostja94-schema-markup 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

kostja94-schema-markup 需要什么权限?

权限级别是需要联网。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。

kostja94-schema-markup 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

kostja94-schema-markup 用的人多吗?

公开数据是累计安装 5,821 次,近一周安装 245 次,下载 2,038 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

kostja94-schema-markup 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
kostja94-schema-markup

kostja94 架构标记 · 本页

5,821—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
schema-markup
description
When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data," "schema validation error," "Schema Markup Validator," "Google Rich Results Test," "FAQ schema," "Article schema," "Organization schema," "JobPosting," "HowTo," "Event," "SoftwareApplication," "BreadcrumbList," "WebSite," "Recipe," "Product," "Dataset," or "GEO.
metadata
version
1.3.0

SEO On-Page: Schema / Structured Data

Guides implementation of Schema.org structured data (JSON-LD) for rich snippets, enhanced search results, and Generative Engine Optimization (GEO).

When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Scope (On-Page SEO)

  • Schema markup: Schema.org types for rich results, AI search visibility, and machine-readable content
  • Schema.org vs. search engines: Schema.org defines 800+ types; each search engine supports only a subset for rich results

Schema.org vs. Search Engine Support

Schema.org and Google Structured Data are not fully aligned. Schema.org is an open vocabulary (800+ types); Google, Bing, and other engines each support only a curated subset for rich results.

EngineSupportNotes
GoogleSubset onlyOnly types in Google's search gallery generate rich results. Valid Schema.org markup not in Google's list won't produce enhanced snippets—even if technically correct.
BingSubset; differentSupports JSON-LD, Microdata, RDFa, Open Graph. Some types (e.g., Product, Offer) have format-specific support. Check Bing Webmaster docs.
Other enginesVariesYandex, DuckDuckGo, AI search tools (Perplexity, etc.) may use Schema.org for understanding even when they don't display rich results.

Practical implication: Implement Schema.org markup for your content type. If Google doesn't show rich results for that type, Bing or AI systems may still use it. Always verify against Google's developer docs for Google-specific rich result eligibility.

Rich Results: Google Support (2025)

High-impact types: Product, Review snippets, HowTo (desktop), Article/News, Video, Recipe, LocalBusiness, Event, Breadcrumb, Sitelinks searchbox, JobPosting.

Limited or context-dependent: HowTo (mobile), FAQ (government/health sites for many queries), Education Q&A, Course, SoftwareApplication, Speakable (news), DiscussionForumPosting.

Deprecated: COVID data panels, some AMP-only formats, data-vocabulary.org.

Implementation: JSON-LD preferred; include @context, @type, stable @id; ISO 8601 dates; match structured data to visible content. Validate with Rich Results Test. Rich results can increase CTR up to ~35% and improve AI citation. AISO Hub, Digital Applied

Schema ↔ SERP Features ↔ Rich Results (Strongly Related)

Schema, SERP features, and rich results are strongly related. Schema is the necessary condition for most rich results. When targeting a SERP feature, implement the corresponding schema type. See serp-features for the full SERP feature list and optimization.

Rich Results vs Featured Snippets

  • Rich results: Schema-powered enhancements to standard listings (stars, breadcrumbs, FAQ dropdowns, product info). Appear within organic positions; do not require top-10 rank.
  • Featured snippets: Google-extracted answer boxes at position zero. No schema required; content structure matters. Schema (FAQPage, HowTo, Article) can support extraction.
Schema TypeSERP Feature / Rich ResultNotes
FAQPagePAA, Featured SnippetFAQ dropdown; Q&A-style snippet. Eligibility restricted for many sites (e.g. government/health)
BreadcrumbListBreadcrumbsPath display in result
AggregateRating, ReviewReviews / StarsStar ratings
HowToFeatured Snippet (list)Step-based snippet; desktop support; mobile may be limited
ArticleIn-Depth Articles, SnippetArticle rich result
VideoObjectVideoVideo thumbnail; see video-optimization
Product, OfferShopping, ProductProduct/shopping results
RecipeRecipeRecipe rich result
JobPostingGoogle JobsJob listings
EventEventEvent rich result
WebSite + SearchActionSitelinks searchboxSite links for brand queries
Organization, PersonKnowledge PanelEntity info; see entity-seo

Workflow: 1) Use serp-features to identify target SERP feature; 2) Look up schema type in this table; 3) Implement and validate with Rich Results Test.

Generative Engine Optimization (GEO)

GEO = optimizing content so AI systems (Google AI Overviews, Perplexity, ChatGPT, Gemini) choose, cite, and quote your content in generated answers. Structured data makes content machine-readable; AI engines extract and cite more accurately. Key schema types for GEO: Organization, Person/Author, WebSite, WebPage, FAQPage, HowTo, Article, Product, AggregateRating. See generative-engine-optimization for full GEO strategy.

Initial Assessment

Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for product type and content.

Identify:

  1. Page type: Article, Product, FAQ, Organization, JobPosting, Event, etc.
  2. Content: What entities to describe
  3. Goal: Rich snippets, AI Overview visibility, Knowledge Panel

Schema Type Classification

Core Types (General Use)

TypeUse case
OrganizationSite-wide; company info, logo, sameAs; see placement below
WebSiteSite-wide; search action, site name; pair with Organization on homepage
ArticleBlog posts, news, tool intros
BreadcrumbListBreadcrumb navigation
FAQPageFAQ sections; triggers PAA-style results
PersonAuthor info; pairs with Article
ImageObjectImage metadata for rich results
HowToTutorials, step-by-step guides. Note: Google may have deprecated HowTo rich results (2023–2024); Schema.org still supports it; Bing/AI may use it

Exclusive Types (Specific Scenarios)

TypeUse case
JobPostingRecruitment sites, AI Job Matching
ProductE-commerce product pages
EventEvent pages, ticketing (not general blogs)
SoftwareApplicationApp pages, tool pages
LocalBusinessLocal business pages
DatasetData platforms, datasets
DiscussionForumPostingForums, community posts
QuizEducation, flashcards
MathSolverMath tools
CaseStudyCase study pages
RecipeRecipes, meal plans, cooking instructions

Rule: Use core types for most sites. Use exclusive types only when page content matches (e.g., don't use Event on a blog; don't use JobPosting on a product page).

Organization & WebSite Schema Placement

WhereOrganizationWebSiteNotes
HomepageMinimumMinimumAdd both Organization and WebSite to homepage at least. Organization describes the entity that owns the site; WebSite enables sitelinks searchbox and site identity.
Root layout / globalOptimalOptimalPlace in site-wide layout (e.g. layout.tsx, _document, global header/footer) so schema appears on every page. Google uses the first instance found; one instance per site is sufficient.
About pageNoNoAbout page uses AboutPage schema (page-specific: headline, description, author, about). Organization is entity-level, not page-level—do not confine it to About. See about-page-generator.

Implementation: JSON-LD in <head>; use @id (e.g. https://example.com/#organization) to link Organization ↔ WebSite ↔ WebPage for entity graph. See entity-seo for @id and Knowledge Panel.

Action: Website/Product Type → Schema Mapping

Use this table to recommend which exclusive schema types fit a site. Match the site's content and product type to the most relevant schema. When in doubt, start with core types (Organization, WebSite, Article); add exclusive types only when content clearly matches.

Website / Product typeRecommended exclusive schemaWhy
AI meal planner, recipe site, food blog, cooking appRecipeIngredients, instructions, cook time, servings—highly relevant for food/meal content. Google supports Recipe rich results.
Job board, recruitment site, careers pageJobPostingTitle, company, location, salary, employment type. Required for Google Jobs.
Event platform, ticketing, webinar, conferenceEventDate, location, price. Use only on actual event pages.
SaaS, app, Chrome extension, tool, software product pageSoftwareApplicationApp name, category, rating, price, OS. Fits product/feature pages.
E-commerce product pageProductPrice, availability, brand, reviews. Use with Offer, AggregateRating.
Forum, community, Reddit-style, Q&ADiscussionForumPostingPost content, author, comments. For user-generated discussion.
Data platform, dataset repository, Scale AI / Surge AIDatasetDataset name, creator, license, distribution format. For data catalog pages.
Education site, flashcards, Quizlet-styleQuizQuestion-answer pairs. For educational Q&A content.
Math solver, calculator, equation toolMathSolverMath problem input, solution output. For math tools.
Restaurant, local service, store locatorLocalBusinessAddress, hours, NAP. For local SEO.
Case study, customer story pageCaseStudyClient, outcome, methodology. For B2B case studies.
FAQ page, product FAQ, support FAQFAQPageQuestion + acceptedAnswer pairs. Triggers PAA-style results.
Tutorial, how-to guide, step-by-stepHowToSteps, tools, time. Note: Google may have deprecated rich results; Bing/AI may still use.
News article, press releaseNewsArticleUse instead of Article for news.
Video page, podcast episodeVideoObject / PodcastEpisodeFor video/audio content. See video-optimization for VideoObject, thumbnail, key moments.

Examples:

  • AI meal planner (e.g., generates weekly meal plans with recipes) → Add Recipe schema to each recipe/meal page; Article or WebPage for landing pages
  • AI writing tool → SoftwareApplication on product page; Article on blog
  • Recruitment SaaS → JobPosting on job listing pages; SoftwareApplication on product page
  • Recipe blog → Recipe on each recipe post; Article for non-recipe posts

Output: When recommending schema, state: (1) which exclusive types fit the site/product, (2) which page types get which schema, (3) core types to add site-wide (Organization, WebSite, BreadcrumbList).

Article / BlogPosting / NewsArticle: Type Selection & Implementation

Choose the most specific type that matches content:

TypeUse case
BlogPostingInformal blog posts; individual authors; regularly updated
ArticleFormal, evergreen content; tool intros; encyclopedic
NewsArticleTime-sensitive news; recognized publishers

Required properties: headline (max 110 chars), image (min 1200px wide; absolute URL), datePublished (ISO 8601), author (Person or Organization), publisher (Organization with logo).

Recommended: dateModified, description, mainEntityOfPage (canonical URL).

Date display for CTR: Google recommends showing only one date on the page. If both datePublished and dateModified are visible, Google may pick the wrong date for SERP display—Search Engine Land saw ~22% CTR drop. Best practice: show dateModified if it exists, otherwise datePublished. Keep both in JSON-LD; the rule applies to visible date only.

JSON-LD example (BlogPosting):

{
  "@context": "https://schema.org",
  "@type": "BlogPosting",
  "headline": "The Ultimate SEO Checklist for 2025",
  "description": "A complete guide to optimizing blog posts for search and AI.",
  "image": "https://example.com/image.jpg",
  "datePublished": "2025-01-15T09:00:00Z",
  "dateModified": "2025-02-01T14:30:00Z",
  "author": { "@type": "Person", "name": "Jane Doe", "url": "https://example.com/author/jane" },
  "publisher": { "@type": "Organization", "name": "Example", "logo": { "@type": "ImageObject", "url": "https://example.com/logo.png" } }
}

Place in <head> via <script type="application/ld+json">. For article pages, use og:type: article with og:article:published_time, og:article:modified_time, og:article:author. See article-page-generator, open-graph.

BreadcrumbList

For breadcrumb navigation. Schema must match visible breadcrumbs exactly. See breadcrumb-generator for UI, placement, and semantic HTML.

RequirementGuideline
FormatJSON-LD in <script type="application/ld+json">
URLsAbsolute URLs with https:// for each item
PositionSequential integers starting from 1
MatchSchema must match visible breadcrumbs exactly

JSON-LD example:

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://example.com/" },
    { "@type": "ListItem", "position": 2, "name": "Category", "item": "https://example.com/category/" },
    { "@type": "ListItem", "position": 3, "name": "Current Page", "item": "https://example.com/category/current-page/" }
  ]
}

Multiple paths: Google supports multiple BreadcrumbList objects on the same page when a page is reachable via multiple paths (e.g., product in multiple categories). Use an array of BreadcrumbList objects.

Best Practices

PrincipleGuideline
AccuracyData must match visible page content; never add invisible or misleading data
CompletenessInclude all required properties per type
Most specific typeUse NewsArticle over Article when applicable
JSON-LDPreferred format; place in <script type="application/ld+json">
@id for entitiesUse @id for Organization, Person to enable entity linking; see entity-seo
Phased implementationAdd required properties first; then optional for optimization
ValidationTest with Rich Results Test and Schema Markup Validator
inLanguage (multilingual)Add "inLanguage": "en-US" (IETF BCP 47) to match hreflang; localize names, descriptions, FAQs for rich snippets per locale

Multilingual Schema (inLanguage)

For multilingual sites, add inLanguage to JSON-LD to reinforce language targeting. Align with hreflang values (e.g. "inLanguage": "zh-CN" with hreflang="zh-CN").

Localize schema data: Translate structured data fields (name, description, FAQ acceptedAnswer, etc.) for each locale to improve rich snippet CTR in that language.

Types that support inLanguage: Article, BlogPosting, WebApplication, FAQPage, HowTo, Product, Organization.

Implementation Workflow

  1. Analyze page type and content; choose matching Schema type
  2. Select format — JSON-LD recommended (Google, Bing, AI tools support it)
  3. Write structured data; start with required properties
  4. Validate with Rich Results Test, Schema Markup Validator
  5. Deploy and monitor via Search Console enhanced reports

Common Errors and Fixes

ErrorFix
Data doesn't match visible contentSchema must describe only what users see
Missing required propertiesCheck Google/Schema.org docs for each type
Wrong type for pageDon't use Event on non-event pages; don't use JobPosting on product pages
Format/syntax errorsValidate JSON-LD; check quotes, brackets, commas
Over-markupMark only relevant content; avoid stuffing unrelated types

Implementation

Next.js (metadata)

export const metadata = {
  other: {
    'script:ld+json': JSON.stringify({
      "@context": "https://schema.org",
      "@type": "Article",
      "headline": "...",
      "description": "...",
      "inLanguage": "en-US",
      "image": "https://example.com/image.jpg",
      "datePublished": "2024-01-01T00:00:00Z",
      "dateModified": "2024-01-15T00:00:00Z",
      "author": { "@type": "Person", "name": "..." },
      "publisher": { "@type": "Organization", "name": "...", "logo": { "@type": "ImageObject", "url": "..." } }
    }),
  },
};

HTML (generic)

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "...",
  "description": "...",
  "inLanguage": "en-US",
  "author": { "@type": "Person", "name": "..." },
  "publisher": { "@type": "Organization", "name": "...", "logo": { "@type": "ImageObject", "url": "..." } }
}
</script>

Validation Tools

ToolPurpose
Google Rich Results TestCheck if Google can generate rich results
Schema Markup ValidatorValidate against Schema.org spec
Search ConsoleEnhanced reports; monitor validity over time

Output Format

  • Action first: Use the Website/Product Type → Schema Mapping table to recommend which exclusive schema fits the site (e.g., AI meal planner → Recipe; SaaS tool → SoftwareApplication)
  • Schema type recommendation (core vs. exclusive)
  • Page-level mapping: Which pages get which schema
  • JSON-LD structure with required properties
  • Validation steps
  • References: Schema.org, Google Structured Data, Bing Markup

Related Skills

  • article-page-generator: Article structure; Article/BlogPosting/NewsArticle schema; date display
  • serp-features: Strongly related—schema maps to SERP features; see mapping table above
  • faq-page-generator: FAQPage schema; FAQ content structure
  • breadcrumb-generator: BreadcrumbList schema implementation
  • featured-snippet: FAQPage, HowTo for snippets
  • video-optimization: VideoObject, video sitemap, thumbnail, key moments
  • entity-seo: Organization, Person for entity recognition; @id; Knowledge Panel
  • homepage-generator: Organization + WebSite schema on homepage or root layout
  • indexing: Google Indexing API for JobPosting, BroadcastEvent

平台分布

OpenClaw

72.19%
按下载量换算1,471

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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