Skill · AI & Development

Schema Markup Generator

Generate valid JSON-LD rich result markup and connected entity graphs tailored for Google Search eligibility. Install in 30 seconds.

Category: AI & Development
Deliverable: 1 .skill bundle
Outputs: —
Last updated: 13 Jun 2026

$8.99 One-time · lifetime updates

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Overview

What Schema Markup Generator does.

Schema Markup Generator analyzes your page content or requirements, runs an eligibility check against current Google rich result criteria, then builds a single connected JSON-LD entity graph for that page — not a flat snippet, but properly nested types (Organization linked to WebSite, Offer nested inside Product, author entity tied to Article) with required and recommended properties filled in. It enforces content-markup parity before generating anything, so you are not shipping markup that could trigger a Search Console manual action.

You tell the skill your page type, share the relevant content (or describe it), and specify any stack constraints. For example: a product detail page on a headless Shopify build, with live price, two customer reviews averaging 4.6 stars, and an existing BreadcrumbList you want extended. The skill checks FAQ and HowTo eligibility status, selects the correct types for that page, and produces paste-ready JSON-LD.

Sample output excerpt for that product page — a structured block distinguishing required from recommended fields, plus a short validation checklist: { "@context": "https://schema.org", "@type": "Product", "name": "[product name]", "offers": { "@type": "Offer", "priceCurrency": "USD", "availability": "https://schema.org/InStock" }, "aggregateRating": { "@type": "AggregateRating", "ratingValue": "4.6", "reviewCount": "2" } } Validation steps: Rich Results Test > Search Console Enhancement report > monitor for warnings on aggregateRating.

Who it's for

Front-end developers and SEO specialists who need production-ready structured data fast and cannot afford 'missing field' warnings or ineligible markup types cluttering their codebase. Particularly useful when a site spans multiple page templates — product, article, local business, FAQ — each requiring a different entity graph.

How it works

Three steps. About two minutes.

Install

Add the .skill file to your Claude app. ~10 seconds.

Run it on your work

Invoke the skill and paste in your material.

Apply the output

Review, keep what works, and use it.

In depth

Why a Claude skill beats a prompt template.

A copy-paste prompt runs one static pass and stops. A skill is a bundled program — instructions, examples, and a workflow Claude runs as a unit: it asks for the right input, applies the same pattern every time, and returns the structured outputs above.

FAQ

Common questions.

What input does the skill actually need from me?

At minimum: the page type (e.g., Product, Article, LocalBusiness) and the visible content or a description of it — name, price, author, address, whatever is on the page. The more detail you provide, the more properties the skill can populate without guessing.

Does it check whether a schema type still qualifies for a rich result before generating markup?

Yes. The eligibility check runs first. If a type you requested no longer earns a rich result under current Google guidelines, or if your content does not support the markup, the skill flags that before outputting any JSON-LD.

Will it handle multiple schema types on a single page?

It produces one connected entity graph per page, which can include several linked types — for example, a Product with nested Offer, AggregateRating, and a BreadcrumbList — rather than isolated, unlinked blocks.

What format is the output delivered in?

Paste-ready JSON-LD with a brief annotation distinguishing required from recommended properties, followed by a short validation workflow pointing to the Rich Results Test and the relevant Search Console enhancement report.

Does this skill work for local business or service-area pages, not just e-commerce?

Yes. LocalBusiness markup — including geo-coordinates, opening hours, and service area — is a supported type, and the same eligibility-first approach applies.