Attribution: Original skill by AgriciDaniel, MIT licensed. Cendis hosts this entry for discovery and install convenience.
What it does
Three modes in one skill:
- Detect — scan a page (or a whole site) for existing JSON-LD, Microdata, and RDFa, and report what’s there.
- Validate — check existing structured data against Schema.org definitions and Google’s rich-result requirements; surface errors and warnings.
- Generate — produce ready-to-paste JSON-LD blocks tailored to the page type (Article, Product, Organization, FAQ, HowTo, etc.).
When to use it
- Adding structured data to a new site or page
- Debugging “Page indexed without rich results” reports in Google Search Console
- Preparing pages for AI Overviews / AI Mode citation
- Auditing a site after a CMS migration that may have stripped schema
Schema types it generates
- Article / NewsArticle / BlogPosting — author, datePublished, image, headline
- Product — offers, aggregateRating, brand, sku, gtin
- Organization — name, logo, sameAs, contactPoint
- LocalBusiness — address, geo, openingHours, priceRange
- FAQPage — Q&A pairs with proper nesting
- HowTo — steps, supplies, tools, totalTime
- BreadcrumbList — full hierarchy with @id linking
- WebSite + WebPage — site-wide knowledge graph wiring with
@idreferences - CollectionPage + ItemList — for index/listing pages
Example
“Add Article schema to /blog/why-typescript and validate the existing Organization schema on the homepage.”
The agent:
- Fetches both pages
- Parses existing JSON-LD
- Reports
Organizationschema validation results (e.g.,logomissing,sameAsshould be an array) - Generates the
Articleblock with author, datePublished, image, headline, andmainEntityOfPagelinking back to the canonical URL - Returns paste-ready JSON-LD for both fixes
Why it matters
Schema.org markup is the most underused SEO win on the modern web. Pages with proper structured data unlock rich results, knowledge panels, and far higher AI citation rates — search engines and LLMs both rely on schema to understand “what is this page about” without having to infer from prose. The friction is that writing JSON-LD by hand is tedious and easy to get wrong; this skill removes that friction.
License
MIT — original work by AgriciDaniel. Attribution preserved.