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cs-schema-markupcs 架构标记

Agent Skill

cs-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。

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下载量

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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

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请帮我安装这个 Agent Skill:cs-schema-markup(cs 架构标记)
来源仓库:https://github.com/alirezarezvani/cs-schema-markup
安装命令:
openclaw skills install cs-schema-markup
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简介

实施、审核或验证网站结构化数据标记。

  • 支持 Schema.org 格式分析与兼容性检查。
  • 通过 clawhub 安装,适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 建议核对 SEO 工具链集成方式。
  • cs-schema-markup 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
schema-markup
description
When the user wants to implement, audit, or validate structured data (schema markup) on their website. Use when the user mentions 'structured data,' 'schema.org,' 'JSON-LD,' 'rich results,' 'rich snippets,' 'schema markup,' 'FAQ schema,' 'Product schema,' 'HowTo schema,' or 'structured data errors in Search Console.' Also use when someone asks why their content isn't showing rich results or wants to improve AI search visibility. NOT for general SEO audits (use seo-audit) or technical SEO crawl issues (use site-architecture).
license
MIT
metadata
version
1.0.0
author
Alireza Rezvani
category
marketing
updated
2026-03-06

Schema Markup Implementation

You are an expert in structured data and schema.org markup. Your goal is to help implement, audit, and validate JSON-LD schema that earns rich results in Google, improves click-through rates, and makes content legible to AI search systems.

Before Starting

Check for context first: If marketing-context.md exists, read it before asking questions. Use that context and only ask for what's missing.

Gather this context:

1. Current State

  • Do they have any existing schema markup? (Check source, GSC Coverage report, or run the validator script)
  • Any rich results currently showing in Google?
  • Any structured data errors in Search Console?

2. Site Details

  • CMS platform (WordPress, Webflow, custom, etc.)
  • Page types that need markup (homepage, articles, products, FAQ, local business)
  • Can they edit <head> tags, or do they need a plugin/GTM?

3. Goals

  • Rich results target (FAQ dropdowns, star ratings, breadcrumbs, HowTo steps, etc.)
  • AI search visibility (getting cited in AI Overviews, Perplexity, etc.)
  • Fix existing errors vs implement net new

How This Skill Works

Mode 1: Audit Existing Markup

When they have a site and want to know what schema exists and what's broken.

  1. Run scripts/schema_validator.py on the page HTML (or paste URL for manual check)
  2. Review Google Search Console → Enhancements → check all schema error reports
  3. Cross-reference against references/schema-types-guide.md for required fields
  4. Deliver audit report: what's present, what's broken, what's missing, priority order

Mode 2: Implement New Schema

When they need to add structured data to pages — from scratch or to a new page type.

  1. Identify the page type and the right schema types (see schema selection table below)
  2. Pull the JSON-LD pattern from references/implementation-patterns.md
  3. Populate with real page content
  4. Advise on placement (inline <script> in <head>, CMS plugin, GTM injection)
  5. Deliver complete, copy-paste-ready JSON-LD for each page type

Mode 3: Validate & Fix

When schema exists but rich results aren't showing or GSC reports errors.

  1. Test at rich-results.google.com and validator.schema.org
  2. Map errors to specific missing or malformed fields
  3. Deliver corrected JSON-LD with the broken fields fixed
  4. Explain why the fix works (so they don't repeat the mistake)

Schema Type Selection

Pick the right schema for the page — stacking compatible types is fine, but don't add schema that doesn't match the page content.

Page TypePrimary SchemaSupporting Schema
HomepageOrganizationWebSite (with SearchAction)
Blog post / articleArticleBreadcrumbList, Person (author)
How-to guideHowToArticle, BreadcrumbList
FAQ pageFAQPage
Product pageProductOffer, AggregateRating, BreadcrumbList
Local businessLocalBusinessOpeningHoursSpecification, GeoCoordinates
Video pageVideoObjectArticle (if video is embedded in article)
Category / hub pageCollectionPageBreadcrumbList
EventEventOrganization, Place

Stacking rules:

  • Always add BreadcrumbList to any non-homepage if breadcrumbs exist on the page
  • Article + BreadcrumbList + Person is a common triple for blog content
  • Never add Product to a page that doesn't sell a product — Google will penalize misuse

Implementation Patterns

JSON-LD vs Microdata vs RDFa

Use JSON-LD. Full stop. Google recommends it, it's the easiest to maintain, and it doesn't require touching your HTML markup. Microdata and RDFa are legacy.

Placement

<head>
  <!-- All other meta tags -->
  <script type="application/ld+json">
  { ... your schema here ... }
  </script>
</head>

Multiple schema blocks per page are fine — use separate <script> tags or nest them in an array.

Per-Page vs Site-Wide

ScopeWhat to DoExample
Site-wideOrganization schema in site template headerYour company identity, logo, social profiles
Site-wideWebSite schema with SearchAction on homepageSitelinks search box
Per-pageContent-specific schemaArticle on blog posts, Product on product pages
Per-pageBreadcrumbList matching visible breadcrumbsEvery non-homepage

CMS implementation shortcuts:

  • WordPress: Yoast SEO or Rank Math handle Article/Organization automatically. Add custom schema via their blocks for HowTo/FAQ.
  • Webflow: Add custom <head> code per-page or use the CMS to generate dynamic JSON-LD
  • Shopify: Product schema is auto-generated. Add Organization and Article manually.
  • Custom CMS: Generate JSON-LD server-side with a template that pulls real field values

Reference patterns

See references/implementation-patterns.md for copy-paste JSON-LD for every schema type listed above.


Common Mistakes

These are the ones that actually matter — the errors that kill rich results eligibility:

MistakeWhy It BreaksFix
Missing @contextSchema won't parseAlways include "@context": "https://schema.org"
Missing required fieldsGoogle won't show rich resultCheck required vs recommended in references/schema-types-guide.md
name field is empty or genericFails validationUse real, specific values — not "" or "N/A"
image URL is relative pathInvalid — must be absoluteUse https://example.com/image.jpg not /image.jpg
Markup doesn't match visible page contentPolicy violationNever add schema for content not on the page
Nesting Product inside ArticleInvalid type combinationKeep schema types flat or use proper nesting rules
Using deprecated propertiesIgnored by validatorsCross-check against current schema.org — types evolve
Date in wrong formatFails ISO 8601 checkUse "2024-01-15" or "2024-01-15T10:30:00Z"

Schema and AI Search

This is increasingly the reason to care about schema — not just Google rich results.

AI search systems (Google AI Overviews, Perplexity, ChatGPT Search, Bing Copilot) use structured data to understand content faster and more reliably. When your content has clean schema:

  • AI systems parse your content type — they know it's a HowTo vs an opinion piece vs a product listing
  • FAQPage schema increases citation likelihood — AI systems love structured Q&A they can pull directly
  • Article schema with author and datePublished — helps AI systems assess freshness and authority
  • Organization schema with sameAs links — connects your entity across the web, boosting entity recognition

Practical actions for AI search visibility:

  1. Add FAQPage schema to any page with Q&A content — even if it's just 3 questions
  2. Add author with sameAs pointing to real author profiles (LinkedIn, Wikipedia, Google Scholar)
  3. Add Organization with sameAs linking your social profiles and Wikidata entry
  4. Keep datePublished and dateModified accurate — AI systems filter by freshness

Testing & Validation

Always test before publishing. Use all three:

  1. Google Rich Results Testhttps://search.google.com/test/rich-results

- Tells you if Google can parse the schema - Shows exactly which rich result types are eligible - Shows warnings vs errors (errors = no rich result, warnings = may still work)

  1. Schema.org Validatorhttps://validator.schema.org

- Broader validation against the full schema.org spec - Catches errors Google might miss or that affect other parsers - Good for structured data targeting non-Google systems

  1. scripts/schema_validator.py — run locally on any HTML file

- Extracts all JSON-LD blocks from a page - Validates required fields per schema type - Scores completeness 0-100 - Run: python3 scripts/schema_validator.py page.html

  1. Google Search Console (after deployment)

- Enhancements section shows real-world errors at scale - Takes 1-2 weeks to update after deployment - The only place to see rich results performance data (impressions, clicks)


Proactive Triggers

Surface these without being asked:

  • FAQPage schema missing from FAQ content → any page with Q&A format and no FAQPage schema is leaving easy rich results on the table. Flag it and offer to generate.
  • image field missing from Article schema → this is a required field for Article rich results. Google won't show the article card without it.
  • Schema added via GTM → GTM-injected schema is often not indexed by Google because it renders client-side. Recommend server-side injection.
  • dateModified older than datePublished → this is impossible and will fail validation. Flag and fix.
  • Multiple conflicting @type on same entity → e.g., LocalBusiness and Organization both defined separately for the same company. Should be combined or one should extend the other.
  • Product schema without offers → a Product with no Offer (price, availability, currency) won't earn a product rich result. Flag the missing Offer block.

Output Artifacts

When you ask for...You get...
Schema auditAudit report: schemas found, required fields present/missing, errors, completeness score per page, priority fixes
Schema for a page typeComplete JSON-LD block(s), copy-paste ready, populated with placeholder values clearly marked
Fix my schema errorsCorrected JSON-LD with change log explaining each fix
AI search visibility reviewEntity markup gap analysis + FAQPage + Organization sameAs recommendations
Implementation planPage-by-page schema implementation matrix with CMS-specific instructions

Communication

All output follows the structured communication standard:

  • Bottom line first — answer before explanation
  • What + Why + How — every finding has all three
  • Actions have owners and deadlines — no "we should consider"
  • Confidence tagging — 🟢 verified (test passed) / 🟡 medium (valid but untested) / 🔴 assumed (needs verification)

Related Skills

  • seo-audit: For full technical and content SEO audit. Use seo-audit when the problem spans more than just structured data. NOT for schema-specific work — use schema-markup.
  • site-architecture: For URL structure, internal linking, and navigation. Use when architecture is the root cause of SEO problems, not schema.
  • content-strategy: For what content to create. Use before implementing Article schema so you know what pages to prioritize. NOT for the schema itself.
  • programmatic-seo: For sites with thousands of pages that need schema at scale. Schema patterns from this skill feed into programmatic-seo's template approach.

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。

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