feat(seo-schema-generator): merge site-extraction + source-to-schema into one skill
Unify the two schema-generation scenarios into a single slot-17 skill, both feeding one claims register -> build -> validate(16) pipeline: - Mode 1 (existing site): NEW scripts/extract_site_claims.py turns URLs / local HTML / a directory into a claims register. Existing JSON-LD -> CONFIRMED; title/OpenGraph -> PENDING (never auto-shipped). + site-extraction-methodology.md and bundled fixtures/site/ demo pages. - Mode 2 (not-yet-published site): land the source-to-schema engine (build_schema_drafts.py, type_templates.json, claims/source registers, 3 refs, sample_claims.csv) from the Desktop builder. - Rewrite SKILL.md (v2.0) around the two-mode framing; the claims register is the shared pivot. Only CONFIRMED, non-conflicting claims become schema; unfilled template slots are pruned, never emitted as placeholders. - Retire the old template-fill generator (code/ + desktop/); update root CLAUDE.md. Self-tested both chains end-to-end: Mode 2 sample -> build -> validate PASS (P0=0); Mode 1 fixtures -> extract -> build -> validate PASS (P0=0), JSON-LD round-trips with nested address intact. Fixed two adapter bugs (nested node promotion; relative-path URI). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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---
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name: seo-schema-generator
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description: |
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JSON-LD structured data generator from templates for various content types.
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Triggers: generate schema, create JSON-LD, schema markup, structured data generator.
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---
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# SEO Schema Generator
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## Purpose
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Generate JSON-LD structured data markup for various content types using templates.
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## Core Capabilities
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1. **Organization** - Company/brand information
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2. **LocalBusiness** - Physical location businesses
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3. **Article** - Blog posts and news articles
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4. **Product** - E-commerce products
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5. **FAQPage** - FAQ sections
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6. **BreadcrumbList** - Navigation breadcrumbs
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7. **WebSite** - Site-level with search action
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## Workflow
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1. Identify content type
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2. Gather required information
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3. Generate JSON-LD from template
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4. Validate output
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5. Provide implementation instructions
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## Schema Templates
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### Organization
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```json
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{
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"@context": "https://schema.org",
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"@type": "Organization",
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"name": "[Company Name]",
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"url": "[Website URL]",
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"logo": "[Logo URL]",
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"sameAs": [
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"[Social Media URLs]"
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]
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}
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```
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### LocalBusiness
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```json
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{
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"@context": "https://schema.org",
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"@type": "LocalBusiness",
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"name": "[Business Name]",
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"address": {
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"@type": "PostalAddress",
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"streetAddress": "[Street]",
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"addressLocality": "[City]",
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"addressRegion": "[State]",
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"postalCode": "[ZIP]",
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"addressCountry": "[Country]"
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},
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"telephone": "[Phone]",
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"openingHours": ["Mo-Fr 09:00-17:00"]
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}
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```
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### Article
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```json
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{
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"@context": "https://schema.org",
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"@type": "Article",
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"headline": "[Title]",
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"author": {
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"@type": "Person",
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"name": "[Author Name]"
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},
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"datePublished": "[YYYY-MM-DD]",
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"dateModified": "[YYYY-MM-DD]",
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"image": "[Image URL]",
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"publisher": {
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"@type": "Organization",
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"name": "[Publisher]",
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"logo": "[Logo URL]"
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}
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}
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```
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### FAQPage
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```json
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{
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"@context": "https://schema.org",
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"@type": "FAQPage",
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"mainEntity": [
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{
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"@type": "Question",
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"name": "[Question]",
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"acceptedAnswer": {
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"@type": "Answer",
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"text": "[Answer]"
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}
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}
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]
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}
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```
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### Product
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```json
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{
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"@context": "https://schema.org",
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"@type": "Product",
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"name": "[Product Name]",
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"image": "[Image URL]",
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"description": "[Description]",
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"offers": {
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"@type": "Offer",
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"price": "[Price]",
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"priceCurrency": "[Currency]",
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"availability": "https://schema.org/InStock"
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}
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}
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```
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## Implementation
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Place generated JSON-LD in `<head>` section:
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```html
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<head>
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<script type="application/ld+json">
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[Generated Schema Here]
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</script>
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</head>
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```
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## Validation
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After generating:
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1. Use schema validator skill (13) to verify
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2. Test with Google Rich Results Test
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3. Monitor in Search Console
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## Limitations
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- Templates cover common types only
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- Complex nested schemas may need manual adjustment
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- Some Rich Results require additional properties
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## Notion Output (Required)
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All audit reports MUST be saved to OurDigital SEO Audit Log:
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- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
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- **Properties**: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
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- **Language**: Korean with English technical terms
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- **Audit ID Format**: [TYPE]-YYYYMMDD-NNN
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