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pseo-schema伪图式

Agent Skill

pseo-schema 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

269

周安装

11

GitHub Stars

40

下载量

86
CodexClaudeCursorGemini CLI

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

unknown

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:pseo-schema(伪图式)
来源仓库:https://github.com/lisbeth718/pseo-skills
仓库路径:skills/pseo-schema
安装命令:
npx skills add https://github.com/lisbeth718/pseo-skills --skill pseo-schema
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/lisbeth718/pseo-skills --skill pseo-schema

简介

用于查找与筛选数据结构定义、API 契约及数据库建模相关资料。

  • 适合在系统集成或微服务拆分等架构设计阶段使用。
  • 通过 GitHub 仓库安装,需确认其是否依赖特定 Schema 语言解析器。
  • 安装命令:npx skills add https://github.com/lisbeth718/pseo-skills --skill pseo-schema。
  • 建议在使用前验证所引用标准的版本兼容性与扩展机制。

SKILL.md

pSEO Schema Markup

Implement JSON-LD structured data that gives search engines explicit semantic understanding of every programmatic page.

Core Principles

  1. JSON-LD format: Always use JSON-LD, not Microdata or RDFa
  2. Context-appropriate types: Match schema type to the page's actual content
  3. Data-driven generation: Schema is built from the same data that drives the page
  4. Valid and complete: Every schema block must pass Google's Rich Results Test
  5. No fabrication: Only include fields backed by real data

Baseline Schema (Every Page)

Every pSEO page should include these foundational types:

  • WebSite — once per site (on the homepage or via a shared layout), declares site-level search and name
  • WebPage — on every page, declares the page URL, name, description, and dateModified
  • BreadcrumbList — on every page with navigation hierarchy

These are in addition to the content-specific types below.

Schema Types by Page Context

Page TypePrimary SchemaSupporting Schema
Content/article pageArticleBreadcrumbList, FAQPage, WebPage
Product pageProductBreadcrumbList, AggregateRating, WebPage
FAQ/Q&A pageFAQPageBreadcrumbList, WebPage
How-to/tutorial pageHowToBreadcrumbList, FAQPage, WebPage
Category/hub pageCollectionPageBreadcrumbList, ItemList, WebPage
Local/location pageLocalBusinessBreadcrumbList, FAQPage, WebPage

Implementation Steps

1. Create Schema Generator Functions

Build a module of pure functions that produce schema objects from page data:

// lib/schema.ts

export function generateArticleSchema(data: PageData, url: string) {
  return {
    "@context": "https://schema.org",
    "@type": "Article",
    headline: data.h1,
    description: data.metaDescription,
    url,
    datePublished: data.publishedDate,
    dateModified: data.lastModified,
    author: { "@type": "Organization", name: "..." },
    publisher: { "@type": "Organization", name: "..." },
  };
}

// IMPORTANT: FAQPage schema is ONLY valid when the FAQ content is
// visible on the page itself. Google requires the questions and answers
// to be present in the rendered HTML, not just in the JSON-LD.
// Never add FAQPage schema to a page that does not render the FAQs.
export function generateFAQSchema(faqs: FAQ[]) {
  if (!faqs?.length) return null;
  return {
    "@context": "https://schema.org",
    "@type": "FAQPage",
    mainEntity: faqs.map((faq) => ({
      "@type": "Question",
      name: faq.question,
      acceptedAnswer: {
        "@type": "Answer",
        text: faq.answer,
      },
    })),
  };
}

export function generateWebPageSchema(data: PageData, url: string) {
  return {
    "@context": "https://schema.org",
    "@type": "WebPage",
    name: data.title,
    description: data.metaDescription,
    url,
    dateModified: data.lastModified,
  };
}

export function generateBreadcrumbSchema(
  items: { name: string; url: string }[]
) {
  return {
    "@context": "https://schema.org",
    "@type": "BreadcrumbList",
    itemListElement: items.map((item, i) => ({
      "@type": "ListItem",
      position: i + 1,
      name: item.name,
      item: item.url,
    })),
  };
}

2. Create the Schema Renderer Component

Build a reusable component that injects JSON-LD into the page head:

export function JsonLd({ data }: { data: Record<string, unknown> | null }) {
  if (!data) return null;
  return (
    <script
      type="application/ld+json"
      dangerouslySetInnerHTML={{ __html: JSON.stringify(data) }}
    />
  );
}

3. Compose Schema per Page

Each page template composes its schema from multiple generators:

// In the page component
const schemas = [
  generateArticleSchema(data, canonicalUrl),
  generateBreadcrumbSchema(breadcrumbItems),
  data.faqs?.length ? generateFAQSchema(data.faqs) : null,
].filter(Boolean);

// Render each as a separate script tag
{schemas.map((schema, i) => <JsonLd key={i} data={schema} />)}

4. Schema Field Rules

Required fields per type:

  • Article: headline, url, datePublished, dateModified, author, publisher
  • FAQPage: mainEntity with at least 1 Question/Answer pair
  • BreadcrumbList: itemListElement with position, name, item
  • Product: name, description; offers or review if available
  • HowTo: name, step (with text for each step)

Field integrity rules:

  • headline must match the page's H1 or title
  • url must match the canonical URL
  • dateModified must be a valid ISO 8601 date
  • Never include empty strings or placeholder values
  • Never include fields with fabricated data (e.g., fake reviews)

5. Handle Multiple Schema Types

A single page can have multiple schema blocks. Render them as separate <script type="application/ld+json"> tags, not as an array in one tag (for maximum compatibility).

Validation

Schema must:

  • Pass Google's Rich Results Test (https://search.google.com/test/rich-results)
  • Pass Schema.org validation
  • Not include deprecated properties
  • Not include fields with empty or placeholder values
  • Use absolute URLs, not relative paths

6. E-E-A-T Schema Support

Google's 2025 updates weight Experience, Expertise, Authoritativeness, and Trustworthiness heavily. Schema markup can reinforce these signals:

Author/Organization schema on every page:

export function generateAuthorSchema(author: AuthorInfo) {
  return {
    "@context": "https://schema.org",
    "@type": author.type === "person" ? "Person" : "Organization",
    name: author.name,
    url: author.url,
    ...(author.credentials && { jobTitle: author.credentials }),
    ...(author.sameAs && { sameAs: author.sameAs }),
  };
}

Add author and publisher to Article schema (already included but emphasize this is now critical, not optional).

dateModified must be accurate — Google has increased weighting on freshness signals. Never set dateModified to today's date if the content hasn't actually changed. Use the real last-modified date from the data source.

For YMYL content, additionally include:

  • reviewedBy on medical/health content (Person with MedicalBusiness or Physician type)
  • citation or isBasedOn for content derived from authoritative sources
  • credentialCategory on author's Person schema if applicable

File Organization

lib/
  schema.ts            # all schema generator functions
  schema.test.ts       # validation tests
components/
  JsonLd.tsx           # reusable JSON-LD renderer

Relationship to Other Skills

  • Depends on: pseo-data (structured fields feed schema generation)
  • Works with: pseo-templates (schema components are rendered inside page templates)
  • Breadcrumb data from: pseo-linking (breadcrumb trail structure)

适合场景

01

用户想查找某类 Agent Skill 时

02

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03

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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

Codex

35.11%
按下载量换算30

Claude

31.7%
按下载量换算27

Cursor

20.72%
按下载量换算18

Gemini CLI

9.43%
按下载量换算8

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