[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6PRY4DB9D8M910SDQVJSF02":3,"skill-same:01M6PRY4DB9D8M910SDQVJSF02":98},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":34,"publishedAt":55,"linkOnly":56,"markdownContent":57,"markdownBody":58,"frontMatter":59,"refName":68,"commitSha":69,"skillDirectory":70,"forksCount":14,"repositoryHtmlUrl":71,"repositoryHomepageUrl":6,"ownerHtmlUrl":72,"ownerBlogUrl":73,"ownerDescription":6,"updatedAt":74,"install":75,"resources":87},"01M6PRY4DB9D8M910SDQVJSF02","seo-ecommerce",null,"E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace intelligence, product schema validation, competitor pricing analysis, and marketplace keyword gaps. Combines on-page product SEO with marketplace data from DataForSEO Merchant API. Use when user says \"ecommerce SEO\", \"product SEO\", \"Google Shopping\", \"marketplace SEO\", \"product schema\", \"Amazon SEO\", \"product listings\", \"shopping ads\", or \"merchant SEO\".","headmktlucca-ui\u002Fneuroads-lp","headmktlucca-ui","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F247379838?v=4","01M6PDVAV6M1W96D1SR1PDF8CS","NeuroAds","01M6PDVAZ4P281GNDKD45CYTF5",0,"MIT","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fseo-ecommerce\u002FSKILL.md",[18,23,26,31],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000019","营销推广",{"categoryNo":27,"categoryName":28,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",{"categoryNo":32,"categoryName":33,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000035","市场营销",[35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54],"seo","seo ecommerce","ecommerce","shopping","merchant","URL","commerce","seo analysis","e-commerce","google shopping","listings","intelligence","google","challenge","page","ads","api","analysis","data","product","2026-11-10 10:12:30",false,"---\nname: seo-ecommerce\ndescription: >\n  E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace\n  intelligence, product schema validation, competitor pricing analysis, and\n  marketplace keyword gaps. Combines on-page product SEO with marketplace data\n  from DataForSEO Merchant API. Use when user says \"ecommerce SEO\", \"product SEO\",\n  \"Google Shopping\", \"marketplace SEO\", \"product schema\", \"Amazon SEO\",\n  \"product listings\", \"shopping ads\", or \"merchant SEO\".\nuser-invocable: true\nargument-hint: \"\u003Curl or keyword>\"\nlicense: MIT\ncompatibility: \"Enhanced with DataForSEO Merchant API (optional)\"\nmetadata:\n  author: AgriciDaniel\n  original_author: \"Matej Marjanovic (Pro Hub Challenge)\"\n  version: \"2.2.0\"\n  category: seo\n---\n\n# E-commerce SEO Analysis\n\nComprehensive product page optimization, marketplace intelligence, and\ncompetitive pricing analysis. Works standalone (on-page + schema) and with\nDataForSEO Merchant API for live Google Shopping and Amazon data.\n\n## Commands\n\n| Command | Purpose | DataForSEO? |\n|---------|---------|-------------|\n| `\u002Fseo ecommerce \u003Curl>` | Full e-commerce SEO analysis of a product page or store | Optional |\n| `\u002Fseo ecommerce products \u003Ckeyword>` | Google Shopping competitive analysis | Required |\n| `\u002Fseo ecommerce gaps \u003Cdomain>` | Keyword gap: organic vs Shopping visibility | Required |\n| `\u002Fseo ecommerce schema \u003Curl>` | Product schema validation and enhancement | No |\n\n---\n\n## 1. Product Page Analysis (No DataForSEO Needed)\n\nFetch and parse any product page for on-page SEO quality.\n\n### Workflow\n\n```\n1. python3 scripts\u002Frender_page.py \u003Curl> --mode auto → raw\u002Frendered HTML\n2. python3 scripts\u002Fparse_html.py --url \u003Curl>   → SEO elements\n3. Analyze product-specific signals (below)\n```\n\n### Product SEO Checklist\n\n#### Title Tag\n- [ ] Contains primary product keyword\n- [ ] Includes brand name\n- [ ] Under 60 characters (no truncation in SERPs)\n- [ ] Format: `[Product Name] - [Key Feature] | [Brand]`\n\n#### Meta Description\n- [ ] Contains product keyword + benefit\n- [ ] Includes price or \"from $XX\" (triggers rich snippet interest)\n- [ ] Call-to-action present (Shop now, Buy, Free shipping)\n- [ ] Under 155 characters\n\n#### Heading Structure\n- [ ] Single H1 matching primary product name\n- [ ] H2s for: Features, Specifications, Reviews, Related Products\n- [ ] No duplicate H1 tags across product variants\n\n#### Product Images\n- [ ] Alt text includes product name + distinguishing feature\n- [ ] File names are descriptive (not `IMG_001.jpg`)\n- [ ] WebP format served (with JPEG fallback)\n- [ ] At least 3 images per product (hero, detail, lifestyle)\n- [ ] Image dimensions >= 800px for Google Shopping eligibility\n- [ ] Lazy loading on below-fold images only\n\n#### Internal Linking\n- [ ] Breadcrumb navigation: Home > Category > Subcategory > Product\n- [ ] Related products section (cross-sell \u002F upsell)\n- [ ] Link back to category page with keyword-rich anchor\n- [ ] Reviews section links to full review page (if separate)\n\n#### Content Quality\n- [ ] Unique product description (not manufacturer copy-paste)\n- [ ] Word count >= 200 for product description body\n- [ ] Specs table present (not just prose)\n- [ ] User reviews on-page (UGC signals)\n\n### Scoring\n\n| Category | Weight | Criteria |\n|----------|--------|----------|\n| Schema completeness | 25% | Required + recommended Product fields |\n| Title & meta | 15% | Keyword placement, length, format |\n| Image optimization | 20% | Alt text, format, sizing, count |\n| Content quality | 20% | Unique description, specs, reviews |\n| Internal linking | 10% | Breadcrumbs, related products, categories |\n| Technical | 10% | Page speed, mobile rendering, canonical |\n\n---\n\n## 2. Google Shopping Intelligence (DataForSEO Merchant API)\n\nLive competitive analysis from Google Shopping results.\n\n### Cost Guardrail (MANDATORY)\n\nBefore EVERY Merchant API call:\n```bash\npython3 scripts\u002Fdataforseo_costs.py check merchant_google_products_search\n```\n\n- `\"status\": \"approved\"` -- proceed\n- `\"status\": \"needs_approval\"` -- show cost, ask user\n- `\"status\": \"blocked\"` -- stop, inform user\n\nAfter each call:\n```bash\npython3 scripts\u002Fdataforseo_costs.py log merchant_google_products_search \u003Ccost>\n```\n\n### Workflow\n\n```bash\n# Product search: who sells what at what price\npython3 scripts\u002Fdataforseo_merchant.py search \"\u003Ckeyword>\" --marketplace google\n\n# Seller analysis: merchant ratings and dominance\npython3 scripts\u002Fdataforseo_merchant.py sellers \"\u003Ckeyword>\"\n\n# Normalize results for analysis\npython3 scripts\u002Fdataforseo_normalize.py results.json --module merchant\n```\n\n### Analysis Outputs\n\n#### Pricing Intelligence\n- Price distribution: min, max, median, P25, P75\n- Price outliers (> 2 standard deviations from median)\n- Price-to-rating correlation\n- Currency normalization to USD (or user-specified)\n\n#### Seller Landscape\n- Top 10 sellers by listing count\n- Merchant rating distribution\n- Free shipping prevalence\n- New vs established sellers\n\n#### Product Listing Quality\n- Title keyword patterns in top listings\n- Average rating and review count benchmarks\n- Image count per listing\n- Availability status distribution\n\nLoad `references\u002Fmarketplace-endpoints.md` for full API parameter details.\n\n---\n\n## 3. Amazon Marketplace (DataForSEO)\n\nCross-marketplace intelligence comparing Google Shopping and Amazon.\n\n### Cost Guardrail (MANDATORY)\n\n```bash\npython3 scripts\u002Fdataforseo_costs.py check merchant_amazon_products_search\n```\n\nAmazon endpoints are in the `warn_endpoints` set -- always requires user approval.\n\n### Workflow\n\n```bash\n# Amazon product search\npython3 scripts\u002Fdataforseo_merchant.py search \"\u003Ckeyword>\" --marketplace amazon\n\n# Cross-marketplace comparison\npython3 scripts\u002Fdataforseo_merchant.py compare \"\u003Ckeyword>\"\n```\n\n### Cross-Marketplace Report\n\n| Metric | Google Shopping | Amazon |\n|--------|---------------|--------|\n| Avg price | $ | $ |\n| Median rating | X.X | X.X |\n| Avg review count | N | N |\n| Top seller share | % | % |\n| Free shipping % | % | % |\n\n---\n\n## 4. Marketplace Keyword Gaps\n\nIdentify mismatches between organic and Shopping visibility.\n\n### Workflow\n\n1. Fetch organic rankings via seo-dataforseo:\n   `dataforseo_labs_google_ranked_keywords` for domain\n2. Fetch Google Shopping presence via Merchant API:\n   `merchant_google_products_search` for top organic keywords\n3. Cross-reference results\n\n### Gap Types\n\n| Gap Type | Meaning | Action |\n|----------|---------|--------|\n| **Organic Only** | Ranks organically but no Shopping ads | Create Google Merchant Center feed, bid on these keywords |\n| **Shopping Only** | Shopping visibility but weak\u002Fno organic | Create content (buying guides, comparison pages) for these keywords |\n| **Both Present** | Visible in both channels | Optimize: ensure price consistency, enhance schema |\n| **Neither** | No visibility in either | Low priority unless high volume |\n\n### Output Format\n\n```\n## Keyword Gap Analysis: example.com\n\n### Opportunities: Organic → Shopping (12 keywords)\n| Keyword | Organic Pos | Volume | CPC | Recommended Action |\n|---------|------------|--------|-----|-------------------|\n\n### Opportunities: Shopping → Organic (8 keywords)\n| Keyword | Shopping Rank | Volume | CPC | Content Type Needed |\n|---------|-------------|--------|-----|-------------------|\n```\n\n---\n\n## 5. Product Schema Enhancement\n\nValidate and generate Product schema following Google's current requirements.\n\n### Required Properties (Google Merchant)\n\n```json\n{\n  \"@context\": \"https:\u002F\u002Fschema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"\",\n  \"image\": [\"\"],\n  \"description\": \"\",\n  \"brand\": { \"@type\": \"Brand\", \"name\": \"\" },\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"\",\n    \"priceCurrency\": \"USD\",\n    \"price\": \"0.00\",\n    \"availability\": \"https:\u002F\u002Fschema.org\u002FInStock\",\n    \"seller\": { \"@type\": \"Organization\", \"name\": \"\" }\n  }\n}\n```\n\n### Recommended Properties (Enhance Rich Results)\n\n- `sku` -- product identifier\n- `gtin13` \u002F `gtin14` \u002F `mpn` -- global trade identifiers\n- `aggregateRating` -- star rating + review count\n- `review` -- individual reviews (minimum 1)\n- `color`, `material`, `size` -- variant attributes\n- `shippingDetails` -- ShippingDetails with rate and delivery time\n- `hasMerchantReturnPolicy` -- MerchantReturnPolicy with type and days\n\n### Validation Rules\n\n1. `price` must be a number string, not \"$29.99\" (no currency symbol)\n2. `availability` must use full Schema.org URL enum\n3. `image` should be array with >= 1 high-res image URL\n4. `priceCurrency` must be ISO 4217 (USD, EUR, GBP)\n5. `brand.name` must not be empty or \"N\u002FA\"\n6. Dates in `priceValidUntil` must be ISO 8601\n7. If `aggregateRating` present: `ratingValue` and `reviewCount` required\n\n### Schema Scoring\n\n| Completeness | Score |\n|-------------|-------|\n| All required fields | 50\u002F100 |\n| + aggregateRating | 65\u002F100 |\n| + sku\u002Fgtin\u002Fmpn | 75\u002F100 |\n| + shippingDetails | 85\u002F100 |\n| + merchantReturnPolicy | 90\u002F100 |\n| + reviews (3+) | 100\u002F100 |\n\n---\n\n## Cross-Skill Integration\n\n| Skill | Integration Point |\n|-------|------------------|\n| **seo-schema** | Delegates Product schema generation; reuses validation logic |\n| **seo-images** | Product image audit (alt text, format, dimensions) — plus `DigitalSourceType: TrainedAlgorithmicMedia` IPTC label for AI-generated product images (Merchant Center requirement) |\n| **seo-content** | Product description E-E-A-T and uniqueness analysis |\n| **seo-dataforseo** | Organic keyword rankings for gap analysis |\n| **seo-technical** | Core Web Vitals for product pages (LCP on hero image) |\n| **seo-google** | Google Merchant Center feed validation via GSC |\n\n## UCP — Universal Commerce Protocol (forward-looking)\n\nGoogle-led standard (co-developed with Shopify, Etsy, Walmart, Wayfair, Visa,\nMastercard, etc.) for letting AI agents discover, negotiate, and transact with\nmerchants without one-off integrations. Already powers direct buying from AI\nMode and Gemini.\n\nMerchants already on **Google Merchant Center** with clean Product schema can\ndeclare a UCP profile at `\u002F.well-known\u002Fucp` listing capabilities\n(`dev.ucp.shopping.checkout`, `.fulfillment`, `.discount`). See\n`references\u002Fucp-universal-commerce-protocol.md` for audit criteria,\ncapability examples, and the relationship to AP2 (Agent Payments Protocol).\n\n### Audit command\n\n```bash\n# Discover and validate the UCP profile\npython3 scripts\u002Fucp_check.py https:\u002F\u002Fstore.example.com --json\n\n# With endpoint reachability probes (HEAD each declared capability)\npython3 scripts\u002Fucp_check.py https:\u002F\u002Fstore.example.com --probe-endpoints --json\n```\n\nThe script returns: profile presence, version, declared capabilities,\nstructural issues (missing fields, unknown capability IDs), and (with\n`--probe-endpoints`) per-endpoint reachability. SSRF-blocked endpoints are\nreported explicitly. Missing profile is reported as opportunity, not failure\n— UCP adoption is early.\n\n---\n\n## Error Handling\n\n| Error | Cause | Response |\n|-------|-------|----------|\n| No Product schema found | Page lacks JSON-LD | Analyze page content, generate recommended schema |\n| DataForSEO credentials missing | Env vars not set | Run analysis without marketplace data, note limitation |\n| Cost check blocked | Daily budget exceeded | Inform user, offer free-only analysis |\n| Empty Shopping results | No products for keyword | Suggest broader keyword, check location settings |\n| Amazon API timeout | Network\u002Frate limit | Retry with backoff, fall back to Google-only |\n| Invalid URL | Malformed input | Validate via `google_auth.validate_url()`, show error |\n| Non-product page | URL is category\u002Fhomepage | Detect page type, suggest `\u002Fseo ecommerce schema` instead |\n\n---\n\n## Output Template\n\n```\n## E-commerce SEO Report: [URL or Keyword]\n\n### Overall Score: XX\u002F100\n\n### Product Page SEO\n- Schema Completeness: XX\u002F100\n- Title & Meta: XX\u002F100\n- Image Optimization: XX\u002F100\n- Content Quality: XX\u002F100\n- Internal Linking: XX\u002F100\n\n### Marketplace Intelligence (if DataForSEO available)\n- Google Shopping Listings: N products found\n- Price Range: $XX - $XX (median: $XX)\n- Top Seller: [name] (XX% market share)\n- Amazon Comparison: [available\u002Fnot checked]\n\n### Top Recommendations\n1. [Critical] ...\n2. [High] ...\n3. [Medium] ...\n\nGenerate a PDF report? Use `\u002Fseo google report`\n```\n","# E-commerce SEO Analysis\n\nComprehensive product page optimization, marketplace intelligence, and\ncompetitive pricing analysis. Works standalone (on-page + schema) and with\nDataForSEO Merchant API for live Google Shopping and Amazon data.\n\n## Commands\n\n| Command | Purpose | DataForSEO? |\n|---------|---------|-------------|\n| `\u002Fseo ecommerce \u003Curl>` | Full e-commerce SEO analysis of a product page or store | Optional |\n| `\u002Fseo ecommerce products \u003Ckeyword>` | Google Shopping competitive analysis | Required |\n| `\u002Fseo ecommerce gaps \u003Cdomain>` | Keyword gap: organic vs Shopping visibility | Required |\n| `\u002Fseo ecommerce schema \u003Curl>` | Product schema validation and enhancement | No |\n\n---\n\n## 1. Product Page Analysis (No DataForSEO Needed)\n\nFetch and parse any product page for on-page SEO quality.\n\n### Workflow\n\n```\n1. python3 scripts\u002Frender_page.py \u003Curl> --mode auto → raw\u002Frendered HTML\n2. python3 scripts\u002Fparse_html.py --url \u003Curl>   → SEO elements\n3. Analyze product-specific signals (below)\n```\n\n### Product SEO Checklist\n\n#### Title Tag\n- [ ] Contains primary product keyword\n- [ ] Includes brand name\n- [ ] Under 60 characters (no truncation in SERPs)\n- [ ] Format: `[Product Name] - [Key Feature] | [Brand]`\n\n#### Meta Description\n- [ ] Contains product keyword + benefit\n- [ ] Includes price or \"from $XX\" (triggers rich snippet interest)\n- [ ] Call-to-action present (Shop now, Buy, Free shipping)\n- [ ] Under 155 characters\n\n#### Heading Structure\n- [ ] Single H1 matching primary product name\n- [ ] H2s for: Features, Specifications, Reviews, Related Products\n- [ ] No duplicate H1 tags across product variants\n\n#### Product Images\n- [ ] Alt text includes product name + distinguishing feature\n- [ ] File names are descriptive (not `IMG_001.jpg`)\n- [ ] WebP format served (with JPEG fallback)\n- [ ] At least 3 images per product (hero, detail, lifestyle)\n- [ ] Image dimensions >= 800px for Google Shopping eligibility\n- [ ] Lazy loading on below-fold images only\n\n#### Internal Linking\n- [ ] Breadcrumb navigation: Home > Category > Subcategory > Product\n- [ ] Related products section (cross-sell \u002F upsell)\n- [ ] Link back to category page with keyword-rich anchor\n- [ ] Reviews section links to full review page (if separate)\n\n#### Content Quality\n- [ ] Unique product description (not manufacturer copy-paste)\n- [ ] Word count >= 200 for product description body\n- [ ] Specs table present (not just prose)\n- [ ] User reviews on-page (UGC signals)\n\n### Scoring\n\n| Category | Weight | Criteria |\n|----------|--------|----------|\n| Schema completeness | 25% | Required + recommended Product fields |\n| Title & meta | 15% | Keyword placement, length, format |\n| Image optimization | 20% | Alt text, format, sizing, count |\n| Content quality | 20% | Unique description, specs, reviews |\n| Internal linking | 10% | Breadcrumbs, related products, categories |\n| Technical | 10% | Page speed, mobile rendering, canonical |\n\n---\n\n## 2. Google Shopping Intelligence (DataForSEO Merchant API)\n\nLive competitive analysis from Google Shopping results.\n\n### Cost Guardrail (MANDATORY)\n\nBefore EVERY Merchant API call:\n```bash\npython3 scripts\u002Fdataforseo_costs.py check merchant_google_products_search\n```\n\n- `\"status\": \"approved\"` -- proceed\n- `\"status\": \"needs_approval\"` -- show cost, ask user\n- `\"status\": \"blocked\"` -- stop, inform user\n\nAfter each call:\n```bash\npython3 scripts\u002Fdataforseo_costs.py log merchant_google_products_search \u003Ccost>\n```\n\n### Workflow\n\n```bash\n# Product search: who sells what at what price\npython3 scripts\u002Fdataforseo_merchant.py search \"\u003Ckeyword>\" --marketplace google\n\n# Seller analysis: merchant ratings and dominance\npython3 scripts\u002Fdataforseo_merchant.py sellers \"\u003Ckeyword>\"\n\n# Normalize results for analysis\npython3 scripts\u002Fdataforseo_normalize.py results.json --module merchant\n```\n\n### Analysis Outputs\n\n#### Pricing Intelligence\n- Price distribution: min, max, median, P25, P75\n- Price outliers (> 2 standard deviations from median)\n- Price-to-rating correlation\n- Currency normalization to USD (or user-specified)\n\n#### Seller Landscape\n- Top 10 sellers by listing count\n- Merchant rating distribution\n- Free shipping prevalence\n- New vs established sellers\n\n#### Product Listing Quality\n- Title keyword patterns in top listings\n- Average rating and review count benchmarks\n- Image count per listing\n- Availability status distribution\n\nLoad `references\u002Fmarketplace-endpoints.md` for full API parameter details.\n\n---\n\n## 3. Amazon Marketplace (DataForSEO)\n\nCross-marketplace intelligence comparing Google Shopping and Amazon.\n\n### Cost Guardrail (MANDATORY)\n\n```bash\npython3 scripts\u002Fdataforseo_costs.py check merchant_amazon_products_search\n```\n\nAmazon endpoints are in the `warn_endpoints` set -- always requires user approval.\n\n### Workflow\n\n```bash\n# Amazon product search\npython3 scripts\u002Fdataforseo_merchant.py search \"\u003Ckeyword>\" --marketplace amazon\n\n# Cross-marketplace comparison\npython3 scripts\u002Fdataforseo_merchant.py compare \"\u003Ckeyword>\"\n```\n\n### Cross-Marketplace Report\n\n| Metric | Google Shopping | Amazon |\n|--------|---------------|--------|\n| Avg price | $ | $ |\n| Median rating | X.X | X.X |\n| Avg review count | N | N |\n| Top seller share | % | % |\n| Free shipping % | % | % |\n\n---\n\n## 4. Marketplace Keyword Gaps\n\nIdentify mismatches between organic and Shopping visibility.\n\n### Workflow\n\n1. Fetch organic rankings via seo-dataforseo:\n   `dataforseo_labs_google_ranked_keywords` for domain\n2. Fetch Google Shopping presence via Merchant API:\n   `merchant_google_products_search` for top organic keywords\n3. Cross-reference results\n\n### Gap Types\n\n| Gap Type | Meaning | Action |\n|----------|---------|--------|\n| **Organic Only** | Ranks organically but no Shopping ads | Create Google Merchant Center feed, bid on these keywords |\n| **Shopping Only** | Shopping visibility but weak\u002Fno organic | Create content (buying guides, comparison pages) for these keywords |\n| **Both Present** | Visible in both channels | Optimize: ensure price consistency, enhance schema |\n| **Neither** | No visibility in either | Low priority unless high volume |\n\n### Output Format\n\n```\n## Keyword Gap Analysis: example.com\n\n### Opportunities: Organic → Shopping (12 keywords)\n| Keyword | Organic Pos | Volume | CPC | Recommended Action |\n|---------|------------|--------|-----|-------------------|\n\n### Opportunities: Shopping → Organic (8 keywords)\n| Keyword | Shopping Rank | Volume | CPC | Content Type Needed |\n|---------|-------------|--------|-----|-------------------|\n```\n\n---\n\n## 5. Product Schema Enhancement\n\nValidate and generate Product schema following Google's current requirements.\n\n### Required Properties (Google Merchant)\n\n```json\n{\n  \"@context\": \"https:\u002F\u002Fschema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"\",\n  \"image\": [\"\"],\n  \"description\": \"\",\n  \"brand\": { \"@type\": \"Brand\", \"name\": \"\" },\n  \"offers\": {\n    \"@type\": \"Offer\",\n    \"url\": \"\",\n    \"priceCurrency\": \"USD\",\n    \"price\": \"0.00\",\n    \"availability\": \"https:\u002F\u002Fschema.org\u002FInStock\",\n    \"seller\": { \"@type\": \"Organization\", \"name\": \"\" }\n  }\n}\n```\n\n### Recommended Properties (Enhance Rich Results)\n\n- `sku` -- product identifier\n- `gtin13` \u002F `gtin14` \u002F `mpn` -- global trade identifiers\n- `aggregateRating` -- star rating + review count\n- `review` -- individual reviews (minimum 1)\n- `color`, `material`, `size` -- variant attributes\n- `shippingDetails` -- ShippingDetails with rate and delivery time\n- `hasMerchantReturnPolicy` -- MerchantReturnPolicy with type and days\n\n### Validation Rules\n\n1. `price` must be a number string, not \"$29.99\" (no currency symbol)\n2. `availability` must use full Schema.org URL enum\n3. `image` should be array with >= 1 high-res image URL\n4. `priceCurrency` must be ISO 4217 (USD, EUR, GBP)\n5. `brand.name` must not be empty or \"N\u002FA\"\n6. Dates in `priceValidUntil` must be ISO 8601\n7. If `aggregateRating` present: `ratingValue` and `reviewCount` required\n\n### Schema Scoring\n\n| Completeness | Score |\n|-------------|-------|\n| All required fields | 50\u002F100 |\n| + aggregateRating | 65\u002F100 |\n| + sku\u002Fgtin\u002Fmpn | 75\u002F100 |\n| + shippingDetails | 85\u002F100 |\n| + merchantReturnPolicy | 90\u002F100 |\n| + reviews (3+) | 100\u002F100 |\n\n---\n\n## Cross-Skill Integration\n\n| Skill | Integration Point |\n|-------|------------------|\n| **seo-schema** | Delegates Product schema generation; reuses validation logic |\n| **seo-images** | Product image audit (alt text, format, dimensions) — plus `DigitalSourceType: TrainedAlgorithmicMedia` IPTC label for AI-generated product images (Merchant Center requirement) |\n| **seo-content** | Product description E-E-A-T and uniqueness analysis |\n| **seo-dataforseo** | Organic keyword rankings for gap analysis |\n| **seo-technical** | Core Web Vitals for product pages (LCP on hero image) |\n| **seo-google** | Google Merchant Center feed validation via GSC |\n\n## UCP — Universal Commerce Protocol (forward-looking)\n\nGoogle-led standard (co-developed with Shopify, Etsy, Walmart, Wayfair, Visa,\nMastercard, etc.) for letting AI agents discover, negotiate, and transact with\nmerchants without one-off integrations. Already powers direct buying from AI\nMode and Gemini.\n\nMerchants already on **Google Merchant Center** with clean Product schema can\ndeclare a UCP profile at `\u002F.well-known\u002Fucp` listing capabilities\n(`dev.ucp.shopping.checkout`, `.fulfillment`, `.discount`). See\n`references\u002Fucp-universal-commerce-protocol.md` for audit criteria,\ncapability examples, and the relationship to AP2 (Agent Payments Protocol).\n\n### Audit command\n\n```bash\n# Discover and validate the UCP profile\npython3 scripts\u002Fucp_check.py https:\u002F\u002Fstore.example.com --json\n\n# With endpoint reachability probes (HEAD each declared capability)\npython3 scripts\u002Fucp_check.py https:\u002F\u002Fstore.example.com --probe-endpoints --json\n```\n\nThe script returns: profile presence, version, declared capabilities,\nstructural issues (missing fields, unknown capability IDs), and (with\n`--probe-endpoints`) per-endpoint reachability. SSRF-blocked endpoints are\nreported explicitly. Missing profile is reported as opportunity, not failure\n— UCP adoption is early.\n\n---\n\n## Error Handling\n\n| Error | Cause | Response |\n|-------|-------|----------|\n| No Product schema found | Page lacks JSON-LD | Analyze page content, generate recommended schema |\n| DataForSEO credentials missing | Env vars not set | Run analysis without marketplace data, note limitation |\n| Cost check blocked | Daily budget exceeded | Inform user, offer free-only analysis |\n| Empty Shopping results | No products for keyword | Suggest broader keyword, check location settings |\n| Amazon API timeout | Network\u002Frate limit | Retry with backoff, fall back to Google-only |\n| Invalid URL | Malformed input | Validate via `google_auth.validate_url()`, show error |\n| Non-product page | URL is category\u002Fhomepage | Detect page type, suggest `\u002Fseo ecommerce schema` instead |\n\n---\n\n## Output Template\n\n```\n## E-commerce SEO Report: [URL or Keyword]\n\n### Overall Score: XX\u002F100\n\n### Product Page SEO\n- Schema Completeness: XX\u002F100\n- Title & Meta: XX\u002F100\n- Image Optimization: XX\u002F100\n- Content Quality: XX\u002F100\n- Internal Linking: XX\u002F100\n\n### Marketplace Intelligence (if DataForSEO available)\n- Google Shopping Listings: N products found\n- Price Range: $XX - $XX (median: $XX)\n- Top Seller: [name] (XX% market share)\n- Amazon Comparison: [available\u002Fnot checked]\n\n### Top Recommendations\n1. [Critical] ...\n2. [High] ...\n3. [Medium] ...\n\nGenerate a PDF report? Use `\u002Fseo google report`\n```\n",{"name":5,"license":15,"metadata":60,"description":64,"argument-hint":65,"compatibility":66,"user-invocable":67},{"author":61,"version":62,"category":35,"original_author":63},"AgriciDaniel","2.2.0","Matej Marjanovic (Pro Hub Challenge)","E-commerce SEO analysis: Google Shopping visibility, Amazon marketplace intelligence, product schema validation, competitor pricing analysis, and marketplace keyword gaps. Combines on-page product SEO with marketplace data from DataForSEO Merchant API. Use when user says \"ecommerce SEO\", \"product SEO\", \"Google Shopping\", \"marketplace SEO\", \"product schema\", \"Amazon SEO\", \"product listings\", \"shopping ads\", or \"merchant SEO\".\n","\u003Curl or keyword>","Enhanced with DataForSEO Merchant API (optional)",true,"main","7a940b8e5af16c95e5c190a524421d32fc7445a9",".claude\u002Fskills\u002Fseo-ecommerce","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui","https:\u002F\u002Fneuroads.com.br","2026-08-12 00:42:44",{"source":8,"skillName":5,"commands":76,"prompt":86,"zipAvailable":67},[77,80,83],{"tool":78,"command":79},"npx","npx skills add headmktlucca-ui\u002Fneuroads-lp --skill seo-ecommerce",{"tool":81,"command":82},"bunx","bunx skills add headmktlucca-ui\u002Fneuroads-lp --skill seo-ecommerce",{"tool":84,"command":85},"pnpm","pnpm dlx skills add headmktlucca-ui\u002Fneuroads-lp --skill seo-ecommerce","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fseo-ecommerce\u002FSKILL.md",[88,94],{"path":89,"resourceType":90,"resourceTypeDesc":91,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fmarketplace-endpoints.md","REFERENCE","参考文档",3801,"https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fseo-ecommerce\u002Freferences\u002Fmarketplace-endpoints.md",{"path":95,"resourceType":90,"resourceTypeDesc":91,"sizeBytes":96,"sourceHtmlUrl":97},"references\u002Fucp-universal-commerce-protocol.md",4948,"https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fseo-ecommerce\u002Freferences\u002Fucp-universal-commerce-protocol.md",[99,123,148,174,191,224],{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":111,"publishedAt":55},"01M6PTDCZTXTGSTX4RFK901YSZ","xunit-skill","Generates xUnit.net tests in C#. Covers Fact\u002FTheory, constructor injection, IClassFixture, and FluentAssertions. Use when user mentions \"xUnit\", \"[Fact]\", \"[Theory]\", \"Assert.Equal\", \"C# xUnit\". Triggers on: \"xUnit\", \"[Fact]\", \"[Theory]\", \"Assert.Equal C#\", \"xUnit.net\".","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fxunit-skill\u002FSKILL.md",[105,108],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":109,"categoryName":110,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[112,113,114,115,116,117,118,119,120,121,122],"xunit","xunit skill","testing","injection","user","use","tests","triggers","unit","unit-testing","C#",{"skillNo":124,"name":125,"nameZh":6,"description":126,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":127,"categories":128,"keywords":131,"publishedAt":55},"01M6PTCB59ZTG5FTMWGPYEMMBP","xcuitest-skill","Generates XCUITest UI tests for iOS\u002FiPadOS apps in Swift. Apple's native testing framework for reliable, fast UI automation. Supports local simulators and TestMu AI cloud real devices. Use when user mentions \"XCUITest\", \"XCTest\", \"iOS UI test\", \"Swift test\", \"XCUIApplication\". Triggers on: \"XCUITest\", \"XCTest UI\", \"iOS UI test\", \"Swift UI test\", \"XCUIApplication\", \"TestMu\".","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fxcuitest-skill\u002FSKILL.md",[129,130],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":109,"categoryName":110,"taxonomyType":21,"taxonomyTypeDesc":22},[132,133,114,134,135,136,137,138,117,139,140,141,142,143,118,119,144,145,146,147],"xcuitest","xcuitest skill","automation","test","testing framework","ios","devices","mobile","mobile-testing","ui test","local","apple","apps","native","for","objective",{"skillNo":149,"name":150,"nameZh":6,"description":151,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":158,"publishedAt":55},"01M6PTATMNTY9NF4J7KSR76YK6","world-builder","Create and manage generative game zones for Dorothy's Pokemon-style world. Use this skill when creating, updating, or designing game worlds via MCP tools.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fworld-builder\u002FSKILL.md",[154,157],{"categoryNo":155,"categoryName":156,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":109,"categoryName":110,"taxonomyType":21,"taxonomyTypeDesc":22},[159,160,161,162,163,164,165,166,117,167,168,169,170,171,172,146,173],"builder","world","world builder","MCP","create","mcp tools","Tools","game","pokemon","manage","style","via","theme","zone","generative",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":182,"publishedAt":55},"01M6PT9Z92JTSQEHE1QR0NNW5F","webdriverio-skill","Generates WebdriverIO (WDIO) automation tests in JavaScript or TypeScript. Supports local and TestMu AI cloud. Use when user mentions \"WebdriverIO\", \"WDIO\", \"wdio.conf\", \"browser.url\", \"$\", \"$$\". Triggers on: \"WebdriverIO\", \"WDIO\", \"wdio\", \"browser.$\".","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fwebdriverio-skill\u002FSKILL.md",[180,181],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":109,"categoryName":110,"taxonomyType":21,"taxonomyTypeDesc":22},[183,114,184,134,185,186,187,188,116,117,189,142,118,119,40,190],"webdriverio skill","typescript","javascript","browser","cloud","e2e","e2e-testing","conf",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":204,"publishedAt":55},"01M6PT9NVK36ZWCQ69YXK3FR4K","web-design-guidelines","Web platform design and accessibility guidelines. Use when building web interfaces, auditing accessibility, implementing responsive layouts, or reviewing web UI code. Triggers on tasks involving HTML, CSS, web components, WCAG compliance, responsive design, or web performance.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fweb\u002FSKILL.md",[197,200,201],{"categoryNo":198,"categoryName":199,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":155,"categoryName":156,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":202,"categoryName":203,"taxonomyType":29,"taxonomyTypeDesc":30},"01JBSEEDCAT000000000000032","设计师",[205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,119,223],"design","web","guidelines","web design guidelines","web design","css","performance","components","web components","tasks","code","web performance","ui","platform design","html","responsive design","responsive","platform","implementing",{"skillNo":225,"name":226,"nameZh":6,"description":227,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":228,"categories":229,"keywords":232,"publishedAt":55},"01M6PT9A3JKRE3X34276F2FW5R","watchos-design-guidelines","Apple Human Interface Guidelines for Apple Watch. Use when building watchOS apps, complications, or workout features. Triggers on tasks involving Watch UI, Digital Crown, glanceable interfaces, or wrist-based interactions.","https:\u002F\u002Fgithub.com\u002Fheadmktlucca-ui\u002Fneuroads-lp\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fwatchos\u002FSKILL.md",[230,231],{"categoryNo":155,"categoryName":156,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":202,"categoryName":203,"taxonomyType":29,"taxonomyTypeDesc":30},[205,207,233,214,217,117,234,235,143,222,236,119,144,237,146,238,239],"watchos design guidelines","workout","human","watch","interface","platform-design","features"]