Source profileQuality 90/100

AgriciDaniel/claude-blog/skills/blog-schema/SKILL.md

blog-schema

Generate complete JSON-LD schema markup for blog posts with Article/BlogPosting, Person, Organization, BreadcrumbList, ImageObject, and optional FAQPage. Validates against Google requirements and warns about deprecated types. Use when user says "schema", "blog schema", "json-ld", "structured data", "schema markup", "generate schema".

Source repository stars
1,938
Declared platforms
0
Static risk flags
1
Last source update
2026-08-28
Source checked
2026-08-28

Decision brief

What it does: where it fits

Generates complete, validated JSON-LD schema markup for blog posts using the @graph pattern. Combines multiple schema types into a single script tag with stable @id references for entity linking.

Best for

  • Use when user says "schema", "blog schema", "json-ld", "structured data", "schema markup", "generate schema".

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/AgriciDaniel/claude-blog --skill "skills/blog-schema"
Safe inspection promptEditorial

Inspect the Agent Skill "blog-schema" from https://github.com/AgriciDaniel/claude-blog/blob/84f7abf05036bef48e114a710ff52586643fe239/skills/blog-schema/SKILL.md at commit 84f7abf05036bef48e114a710ff52586643fe239. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Workflow

    Read the blog post and extract all schema-relevant data: - Title (headline) - Author (name, job title, social links, credentials) - Dates (datePublished, dateModified / lastUpdated) - Description (meta description) - FAQ section (question and answer pairs) - Images (cover image…

    Title (headline)Author (name, job title, social links, credentials)Dates (datePublished, dateModified / lastUpdated)
  2. 02

    Step 1: Read Content

    Read the blog post and extract all schema-relevant data: - Title (headline) - Author (name, job title, social links, credentials) - Dates (datePublished, dateModified / lastUpdated) - Description (meta description) - FAQ section (question and answer pairs) - Images (cover image…

    Title (headline)Author (name, job title, social links, credentials)Dates (datePublished, dateModified / lastUpdated)
  3. 03

    Step 2: Generate BlogPosting Schema

    Complete BlogPosting with recommended properties when applicable:

    Complete BlogPosting with recommended properties when applicable:Google's Article structured data docs do not define required Article properties. Include headline, datePublished, author, publisher, and image when applicable, validate with the Rich Results Test, and treat missing fiel…
  4. 04

    Step 3: Generate Person Schema

    Author schema with stable @id for cross-referencing:

    alumniOf - Educational institution (Organization type)worksFor - Employer (reference to Organization @id if same entity)Author schema with stable @id for cross-referencing:
  5. 05

    Step 4: Generate Organization Schema

    Blog's parent organization entity:

    Blog's parent organization entity:Logo requirements: use a valid crawlable image URL and follow the active Organization and Article documentation for the target surface. Do not invent hard logo dimensions unless the project or current docs require them.

Permission review

Static risk signals and limitations

Network access

medium · line 67

The documentation includes network, browsing, or remote request actions.

"https://twitter.com/handle",

Network access

medium · line 68

The documentation includes network, browsing, or remote request actions.

"https://linkedin.com/in/handle",

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score90/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars1,938SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
AgriciDaniel/claude-blog
Skill path
skills/blog-schema/SKILL.md
Commit
84f7abf05036bef48e114a710ff52586643fe239
License
MIT
Collected
2026-08-28
Default branch
main
View the original SKILL.md

Blog Schema: JSON-LD Structured Data Generation

Generates complete, validated JSON-LD schema markup for blog posts using the @graph pattern. Combines multiple schema types into a single script tag with stable @id references for entity linking.

Workflow

Step 1: Read Content

Read the blog post and extract all schema-relevant data:

  • Title (headline)
  • Author (name, job title, social links, credentials)
  • Dates (datePublished, dateModified / lastUpdated)
  • Description (meta description)
  • FAQ section (question and answer pairs)
  • Images (cover image URL, dimensions, alt text; inline images)
  • Organization info (site name, URL, logo)
  • Word count (approximate from content length)
  • Tags/categories (for BreadcrumbList category)
  • Slug (from filename or frontmatter)

Step 2: Generate BlogPosting Schema

Complete BlogPosting with recommended properties when applicable:

{
  "@type": "BlogPosting",
  "@id": "{siteUrl}/blog/{slug}#article",
  "headline": "Concise post title",
  "description": "Concise page-specific meta description",
  "datePublished": "YYYY-MM-DD",
  "dateModified": "YYYY-MM-DD",
  "author": { "@id": "{siteUrl}/author/{author-slug}#person" },
  "publisher": { "@id": "{siteUrl}#organization" },
  "image": { "@id": "{siteUrl}/blog/{slug}#primaryimage" },
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "{siteUrl}/blog/{slug}"
  },
  "wordCount": 2400,
  "articleBody": "First 200 characters of content as excerpt..."
}

Google's Article structured data docs do not define required Article properties. Include headline, datePublished, author, publisher, and image when applicable, validate with the Rich Results Test, and treat missing fields as warnings unless the target surface requires them. Recommended properties: description, dateModified, mainEntityOfPage, wordCount, articleBody (excerpt).

Step 3: Generate Person Schema

Author schema with stable @id for cross-referencing:

{
  "@type": "Person",
  "@id": "{siteUrl}/author/{author-slug}#person",
  "name": "Author Name",
  "jobTitle": "Role or Title",
  "url": "{siteUrl}/author/{author-slug}",
  "sameAs": [
    "https://twitter.com/handle",
    "https://linkedin.com/in/handle",
    "https://github.com/handle"
  ]
}

Optional properties (include when available):

  • alumniOf - Educational institution (Organization type)
  • worksFor - Employer (reference to Organization @id if same entity)

Step 4: Generate Organization Schema

Blog's parent organization entity:

{
  "@type": "Organization",
  "@id": "{siteUrl}#organization",
  "name": "Organization Name",
  "url": "{siteUrl}",
  "logo": {
    "@type": "ImageObject",
    "url": "{siteUrl}/logo.png",
    "width": 600,
    "height": 60
  },
  "sameAs": [
    "https://twitter.com/org",
    "https://linkedin.com/company/org",
    "https://github.com/org"
  ]
}

Logo requirements: use a valid crawlable image URL and follow the active Organization and Article documentation for the target surface. Do not invent hard logo dimensions unless the project or current docs require them.

Step 5: Generate BreadcrumbList

Navigation breadcrumb schema showing content hierarchy:

{
  "@type": "BreadcrumbList",
  "@id": "{siteUrl}/blog/{slug}#breadcrumb",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "{siteUrl}"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Category Name",
      "item": "{siteUrl}/blog/category/{category-slug}"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "Post Title",
      "item": "{siteUrl}/blog/{slug}"
    }
  ]
}

If no category is available, use "Blog" as the second breadcrumb item with {siteUrl}/blog as the URL.

Step 6: Generate FAQPage Entity Schema (Optional)

Extract Q&A pairs from the blog post's FAQ section:

{
  "@type": "FAQPage",
  "@id": "{siteUrl}/blog/{slug}#faq",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is the question?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "The complete visible answer text."
      }
    }
  ]
}

Google retired FAQ rich results for all sites on 2026-05-07. FAQPage is not a Google rich-result or generative-AI optimization path, and it earns no SEO or AI-readiness credit. Only emit it when a visible FAQ genuinely helps readers, with at least one valid Question and matching visible answer. Do not pad an answer to a target length or add an FAQ solely for markup.

Do not substitute QAPage. Google supports QAPage for a page focused on one question where users can submit answers. Editorial FAQs, support FAQs, and blog Q&A sections do not meet that model.

Step 7: Generate VideoObject (if videos present)

For each YouTube video embedded in the post, generate a VideoObject schema:

{
  "@type": "VideoObject",
  "@id": "{siteUrl}/blog/{slug}#video-{index}",
  "name": "Video title",
  "description": "Video description excerpt (first 200 chars)",
  "thumbnailUrl": "https://img.youtube.com/vi/{videoId}/hqdefault.jpg",
  "uploadDate": "{ISO 8601 date}",
  "contentUrl": "https://www.youtube.com/watch?v={videoId}",
  "embedUrl": "https://www.youtube.com/embed/{videoId}",
  "duration": "PT{M}M{S}S",
  "interactionStatistic": {
    "@type": "InteractionCounter",
    "interactionType": { "@type": "WatchAction" },
    "userInteractionCount": {viewCount}
  }
}

Add each VideoObject to the @graph array. Use #video-1, #video-2 etc. for the @id fragment. Extract video metadata from the embed's noscript fallback or from YouTube Data API if available via blog-google.

Step 7.5: Generate ImageObject

Cover image schema for the post's primary image:

{
  "@type": "ImageObject",
  "@id": "{siteUrl}/blog/{slug}#primaryimage",
  "url": "https://cdn.pixabay.com/photo/.../image.jpg",
  "width": 1200,
  "height": 630,
  "caption": "Descriptive caption matching alt text"
}

Image requirements:

  • URL must be crawlable and publicly accessible
  • Width and height should reflect actual image dimensions
  • Caption should match or closely align with the image alt text
  • Preferred dimensions: 1200x630 (OG-compatible) or 1920x1080

Step 8: Validate & Warn

Check per-surface support before recommending schema types:

TypeGoogle Search statusValid entity/context use
HowToNo current Google rich-result experienceValid schema.org type for genuine how-to content
DatasetUsed by Dataset Search, not general Google Search rich resultsValid only for an actual dataset
QAPageSupported for one question with user-submitted answersDo not use for editorial FAQ content
CourseCourse list remains distinct from the retired Course Info experienceUse only when the current Course list documentation and visible content match
ClaimReview, SpecialAnnouncement, Course Info, Estimated Salary, Learning Video, Vehicle ListingFormer Google Search experiences; support was retiredMay remain schema.org-valid, but never recommend them for Google eligibility
PracticeProblemRemoved from Google Search and its documentationDo not recommend for Google eligibility
Sitelinks Search BoxNo dedicated Google Search visual elementGoogle generates sitelinks algorithmically

Validation checks:

  1. All @id references resolve to entities within the @graph
  2. dateModified is equal to or after datePublished
  3. headline is concise. Warn when it may truncate or becomes unclear
  4. description is concise, page-specific, and not duplicated across posts
  5. All URLs are absolute (not relative)
  6. Image dimensions are positive integers
  7. BreadcrumbList positions are sequential starting from 1
  8. If FAQPage is emitted, visible Q&A content exists and includes at least 1 valid Question

Generative AI note: Structured data is not required for Google generative AI search, and there is no special AI schema. Prioritize accurate, visible-content-consistent Article/BlogPosting, Person, Organization, and BreadcrumbList entities. Add ImageObject or VideoObject when the assets exist. FAQPage remains optional reader-facing markup and adds no Google AI advantage.

Step 9: Output

Combine all schemas into a single <script> tag using the @graph pattern:

Security requirement: build the JSON-LD with a real JSON encoder, never string interpolation. Before embedding in HTML, make the JSON text script-safe by escaping closing script sequences and literal less-than characters, for example replace </ with <\/ and < with \u003c. User-controlled fields such as headline, description, author name, image URL, and breadcrumb labels must only enter the block as JSON-encoded values.

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "BlogPosting", ... },
    { "@type": "Person", ... },
    { "@type": "Organization", ... },
    { "@type": "BreadcrumbList", ... },
    { "@type": "FAQPage", ... },
    { "@type": "VideoObject", ... },
    { "@type": "ImageObject", ... }
  ]
}
</script>

@graph pattern benefits:

  • Single script tag instead of multiple - cleaner HTML
  • Entity linking via stable @id references (e.g., author references Person by @id)
  • Google and AI systems parse @graph arrays correctly
  • Easier to maintain and update as a single block

Output options:

  • Embedded HTML - Ready to paste into <head> or before </body>
  • Standalone JSON - For CMS schema fields or API injection
  • MDX component - If the project uses MDX, wrap in a component

Save the generated schema to the blog post file or to a separate schema file as the user prefers.

Google can process JSON-LD generated by JavaScript when it is present in the rendered DOM. Server-rendered markup is still more portable for non-Google crawlers, but source-only JSON-LD is not a Google requirement. For dynamic markup, validate the rendered URL, confirm the values match visible content, and avoid delayed or failed client requests that leave the rendered DOM empty.

Frequently asked questions

What to verify before installation and use

What does the blog-schema source document cover?

Generates complete, validated JSON-LD schema markup for blog posts using the @graph pattern. Combines multiple schema types into a single script tag with stable @id references for entity linking.

How do I install blog-schema?

The source record exposes this install command: npx skills add https://github.com/AgriciDaniel/claude-blog --skill "skills/blog-schema". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged network in the source; the page lists the matching lines and excerpts.

Alternatives

Compare before choosing

Computed 10029,236

garrytan/gbrain

bulk-ingestion

End-to-end discipline for turning any large data source (audio libraries, email takeouts, document corpora, chat exports, API dumps) into brain pages at scale. The lifecycle spine: SCHEMA → ACCESS → TRIAL → EVALUATE → IMPROVE → CODIFY → TEST → SKILLIFY → BULK → MONITOR. State is tracked in a durable JSON manifest (see MANIFEST-PATTERN.md) so any crash, session boundary, or subagent fan-out resumes from ground truth instead of memory.

Computed 10025,136

alirezarezvani/claude-skills

app-store-optimization

App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklist

Computed 10015,385

wanshuiyin/Auto-claude-code-research-in-sleep

citation-audit

Use it for operations and research tasks; the detail page covers purpose, installation, and practical steps.

Computed 10014,706

prowler-cloud/prowler

postgresql-indexing

PostgreSQL indexing best practices for Prowler: index design, partial indexes, partitioned table indexing, EXPLAIN ANALYZE validation, concurrent operations, monitoring, and maintenance. Trigger: When creating or modifying PostgreSQL indexes, analyzing query performance with EXPLAIN, debugging slow queries, reviewing index usage statistics, reindexing, dropping indexes, or working with partitioned table indexes. Also trigger when discussing index strategies, partial indexes, or index maintenance