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",

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: 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: 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: 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: 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: 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: 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: 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: Type Google Search status Valid entity/context use HowTo No current Google rich result experience Valid schema.org type for genuine how to content Dataset Used by Dataset Search, not general Google Search rich results Valid only for an actual dataset QAPage Supported for one question with user submitted answers Do not use for editorial FAQ content Course Course list remains distinct from the retired Course Info experience Use only when the current Course list documentation and visible content match ClaimReview, SpecialAnnouncement, Course Info, Estimated Salary, Learning Video, Vehicle Listing Former Google Search experiences; support was retired May remain schema.org valid, but never recommend them for Google eligibility PracticeProblem Removed from Google Search and its documentation Do not recommend for Google eligibility Sitelinks Search Box No dedicated Google Search visual element Google 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. @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.

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