PluginBench
Skill
Review
Audit score 70

seo-ecommerce

agricidaniel/claude-seo

Analyze product pages, Google Shopping visibility, and marketplace SEO with schema validation and competitor pricing.

What is seo-ecommerce?

Comprehensive e-commerce SEO analysis covering on-page product optimization, Google Shopping and Amazon marketplace intelligence, keyword gap identification, and product schema validation. Use when optimizing product listings, analyzing shopping ads visibility, or comparing marketplace performance.

  • On-page product SEO analysis with checklist covering titles, meta descriptions, images, schema, and content quality
  • Google Shopping competitive analysis including pricing intelligence, seller landscape, and listing quality benchmarks
  • Amazon marketplace cross-comparison and keyword visibility across platforms
  • Keyword gap detection between organic and Shopping visibility to identify optimization opportunities
  • Product schema validation and enhancement with required and recommended properties for rich results
  • Marketplace keyword analysis with pricing, ratings, and seller distribution metrics

How to install seo-ecommerce

npx skills add https://github.com/agricidaniel/claude-seo --skill seo-ecommerce
Prerequisites
  • DataForSEO API key (optional for standalone on-page analysis; required for Shopping and Amazon data)
  • Python 3.x environment with scripts for page rendering and HTML parsing
  • Google Merchant Center feed access (for implementing Shopping recommendations)
Claude Code
Cursor
Windsurf
Cline

How to use seo-ecommerce

  1. 1.Run `/seo ecommerce <url>` on a product page to get on-page SEO analysis with scoring across schema, titles, images, and content
  2. 2.Use `/seo ecommerce products <keyword>` to fetch Google Shopping competitive data including pricing, sellers, and ratings
  3. 3.Execute `/seo ecommerce gaps <domain>` to identify keywords visible organically but missing from Shopping, or vice versa
  4. 4.Run `/seo ecommerce schema <url>` to validate product schema markup and receive enhancement recommendations
  5. 5.Review cost guardrails via `dataforseo_costs.py check` before running Merchant API calls to control spending

Use cases

Good for
  • Optimize a product page for Google Shopping eligibility and organic search ranking
  • Analyze competitor pricing and seller dominance for a product category on Google Shopping and Amazon
  • Identify keywords ranking organically but missing from Google Shopping feed to expand paid visibility
  • Validate and enhance product schema markup to improve rich snippet eligibility
  • Compare marketplace performance across Google Shopping and Amazon for the same product keyword
Who it's for
  • E-commerce product managers optimizing shopping feed performance
  • SEO specialists managing product page rankings and schema markup
  • Marketplace sellers analyzing competitive pricing and visibility
  • Digital marketers running Google Shopping campaigns
  • Content strategists identifying keyword opportunities across channels

seo-ecommerce FAQ

Do I need DataForSEO API to use this skill?

No. On-page product analysis, schema validation, and basic SEO checks work standalone. DataForSEO Merchant API is optional but required for live Google Shopping, Amazon data, and keyword gap analysis.

What's the cost guardrail system?

Before each Merchant API call, the skill checks `dataforseo_costs.py` for approval status. If cost is high, it asks for user confirmation before proceeding. After each call, it logs the cost to prevent budget overruns.

Can I compare Google Shopping and Amazon pricing?

Yes. Use `/seo ecommerce products <keyword> --marketplace amazon` for Amazon data, then use the compare function to see pricing, ratings, and seller distribution across both platforms.

What does the keyword gap analysis show?

It identifies four gap types: Organic Only (create Shopping feed), Shopping Only (create organic content), Both Present (optimize consistency), and Neither (low priority). Includes volume and CPC data for prioritization.

What product schema properties are required vs. recommended?

Required: name, image, description, brand, offers (with price, currency, availability, seller). Recommended: sku, gtin, mpn, aggregateRating for enhanced rich results.

Full instructions (SKILL.md)

Source of truth, from agricidaniel/claude-seo.


name: seo-ecommerce description: > 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". user-invocable: true argument-hint: "<url or keyword>" license: MIT compatibility: "Enhanced with DataForSEO Merchant API (optional)" metadata: author: AgriciDaniel original_author: "Matej Marjanovic (Pro Hub Challenge)" version: "2.2.0" category: seo

E-commerce SEO Analysis

Comprehensive product page optimization, marketplace intelligence, and competitive pricing analysis. Works standalone (on-page + schema) and with DataForSEO Merchant API for live Google Shopping and Amazon data.

Commands

CommandPurposeDataForSEO?
/seo ecommerce <url>Full e-commerce SEO analysis of a product page or storeOptional
/seo ecommerce products <keyword>Google Shopping competitive analysisRequired
/seo ecommerce gaps <domain>Keyword gap: organic vs Shopping visibilityRequired
/seo ecommerce schema <url>Product schema validation and enhancementNo

1. Product Page Analysis (No DataForSEO Needed)

Fetch and parse any product page for on-page SEO quality.

Workflow

1. python3 scripts/render_page.py <url> --mode auto → raw/rendered HTML
2. python3 scripts/parse_html.py --url <url>   → SEO elements
3. Analyze product-specific signals (below)

Product SEO Checklist

Title Tag

  • Contains primary product keyword
  • Includes brand name
  • Under 60 characters (no truncation in SERPs)
  • Format: [Product Name] - [Key Feature] | [Brand]

Meta Description

  • Contains product keyword + benefit
  • Includes price or "from $XX" (triggers rich snippet interest)
  • Call-to-action present (Shop now, Buy, Free shipping)
  • Under 155 characters

Heading Structure

  • Single H1 matching primary product name
  • H2s for: Features, Specifications, Reviews, Related Products
  • No duplicate H1 tags across product variants

Product Images

  • Alt text includes product name + distinguishing feature
  • File names are descriptive (not IMG_001.jpg)
  • WebP format served (with JPEG fallback)
  • At least 3 images per product (hero, detail, lifestyle)
  • Image dimensions >= 800px for Google Shopping eligibility
  • Lazy loading on below-fold images only

Internal Linking

  • Breadcrumb navigation: Home > Category > Subcategory > Product
  • Related products section (cross-sell / upsell)
  • Link back to category page with keyword-rich anchor
  • Reviews section links to full review page (if separate)

Content Quality

  • Unique product description (not manufacturer copy-paste)
  • Word count >= 200 for product description body
  • Specs table present (not just prose)
  • User reviews on-page (UGC signals)

Scoring

CategoryWeightCriteria
Schema completeness25%Required + recommended Product fields
Title & meta15%Keyword placement, length, format
Image optimization20%Alt text, format, sizing, count
Content quality20%Unique description, specs, reviews
Internal linking10%Breadcrumbs, related products, categories
Technical10%Page speed, mobile rendering, canonical

2. Google Shopping Intelligence (DataForSEO Merchant API)

Live competitive analysis from Google Shopping results.

Cost Guardrail (MANDATORY)

Before EVERY Merchant API call:

python3 scripts/dataforseo_costs.py check merchant_google_products_search
  • "status": "approved" -- proceed
  • "status": "needs_approval" -- show cost, ask user
  • "status": "blocked" -- stop, inform user

After each call:

python3 scripts/dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

# Product search: who sells what at what price
python3 scripts/dataforseo_merchant.py search "<keyword>" --marketplace google

# Seller analysis: merchant ratings and dominance
python3 scripts/dataforseo_merchant.py sellers "<keyword>"

# Normalize results for analysis
python3 scripts/dataforseo_normalize.py results.json --module merchant

Analysis Outputs

Pricing Intelligence

  • Price distribution: min, max, median, P25, P75
  • Price outliers (> 2 standard deviations from median)
  • Price-to-rating correlation
  • Currency normalization to USD (or user-specified)

Seller Landscape

  • Top 10 sellers by listing count
  • Merchant rating distribution
  • Free shipping prevalence
  • New vs established sellers

Product Listing Quality

  • Title keyword patterns in top listings
  • Average rating and review count benchmarks
  • Image count per listing
  • Availability status distribution

Load references/marketplace-endpoints.md for full API parameter details.


3. Amazon Marketplace (DataForSEO)

Cross-marketplace intelligence comparing Google Shopping and Amazon.

Cost Guardrail (MANDATORY)

python3 scripts/dataforseo_costs.py check merchant_amazon_products_search

Amazon endpoints are in the warn_endpoints set -- always requires user approval.

Workflow

# Amazon product search
python3 scripts/dataforseo_merchant.py search "<keyword>" --marketplace amazon

# Cross-marketplace comparison
python3 scripts/dataforseo_merchant.py compare "<keyword>"

Cross-Marketplace Report

MetricGoogle ShoppingAmazon
Avg price$$
Median ratingX.XX.X
Avg review countNN
Top seller share%%
Free shipping %%%

4. Marketplace Keyword Gaps

Identify mismatches between organic and Shopping visibility.

Workflow

  1. Fetch organic rankings via seo-dataforseo: dataforseo_labs_google_ranked_keywords for domain
  2. Fetch Google Shopping presence via Merchant API: merchant_google_products_search for top organic keywords
  3. Cross-reference results

Gap Types

Gap TypeMeaningAction
Organic OnlyRanks organically but no Shopping adsCreate Google Merchant Center feed, bid on these keywords
Shopping OnlyShopping visibility but weak/no organicCreate content (buying guides, comparison pages) for these keywords
Both PresentVisible in both channelsOptimize: ensure price consistency, enhance schema
NeitherNo visibility in eitherLow priority unless high volume

Output Format

## Keyword Gap Analysis: example.com

### Opportunities: Organic → Shopping (12 keywords)
| Keyword | Organic Pos | Volume | CPC | Recommended Action |
|---------|------------|--------|-----|-------------------|

### Opportunities: Shopping → Organic (8 keywords)
| Keyword | Shopping Rank | Volume | CPC | Content Type Needed |
|---------|-------------|--------|-----|-------------------|

5. Product Schema Enhancement

Validate and generate Product schema following Google's current requirements.

Required Properties (Google Merchant)

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "",
  "image": [""],
  "description": "",
  "brand": { "@type": "Brand", "name": "" },
  "offers": {
    "@type": "Offer",
    "url": "",
    "priceCurrency": "USD",
    "price": "0.00",
    "availability": "https://schema.org/InStock",
    "seller": { "@type": "Organization", "name": "" }
  }
}

Recommended Properties (Enhance Rich Results)

  • sku -- product identifier
  • gtin13 / gtin14 / mpn -- global trade identifiers
  • aggregateRating -- star rating + review count
  • review -- individual reviews (minimum 1)
  • color, material, size -- variant attributes
  • shippingDetails -- ShippingDetails with rate and delivery time
  • hasMerchantReturnPolicy -- MerchantReturnPolicy with type and days

Validation Rules

  1. price must be a number string, not "$29.99" (no currency symbol)
  2. availability must use full Schema.org URL enum
  3. image should be array with >= 1 high-res image URL
  4. priceCurrency must be ISO 4217 (USD, EUR, GBP)
  5. brand.name must not be empty or "N/A"
  6. Dates in priceValidUntil must be ISO 8601
  7. If aggregateRating present: ratingValue and reviewCount required

Schema Scoring

CompletenessScore
All required fields50/100
+ aggregateRating65/100
+ sku/gtin/mpn75/100
+ shippingDetails85/100
+ merchantReturnPolicy90/100
+ reviews (3+)100/100

Cross-Skill Integration

SkillIntegration Point
seo-schemaDelegates Product schema generation; reuses validation logic
seo-imagesProduct image audit (alt text, format, dimensions) — plus DigitalSourceType: TrainedAlgorithmicMedia IPTC label for AI-generated product images (Merchant Center requirement)
seo-contentProduct description E-E-A-T and uniqueness analysis
seo-dataforseoOrganic keyword rankings for gap analysis
seo-technicalCore Web Vitals for product pages (LCP on hero image)
seo-googleGoogle Merchant Center feed validation via GSC

UCP — Universal Commerce Protocol (forward-looking)

Google-led standard (co-developed with Shopify, Etsy, Walmart, Wayfair, Visa, Mastercard, etc.) for letting AI agents discover, negotiate, and transact with merchants without one-off integrations. Already powers direct buying from AI Mode and Gemini.

Merchants already on Google Merchant Center with clean Product schema can declare a UCP profile at /.well-known/ucp listing capabilities (dev.ucp.shopping.checkout, .fulfillment, .discount). See references/ucp-universal-commerce-protocol.md for audit criteria, capability examples, and the relationship to AP2 (Agent Payments Protocol).

Audit command

# Discover and validate the UCP profile
python3 scripts/ucp_check.py https://store.example.com --json

# With endpoint reachability probes (HEAD each declared capability)
python3 scripts/ucp_check.py https://store.example.com --probe-endpoints --json

The script returns: profile presence, version, declared capabilities, structural issues (missing fields, unknown capability IDs), and (with --probe-endpoints) per-endpoint reachability. SSRF-blocked endpoints are reported explicitly. Missing profile is reported as opportunity, not failure — UCP adoption is early.


Error Handling

ErrorCauseResponse
No Product schema foundPage lacks JSON-LDAnalyze page content, generate recommended schema
DataForSEO credentials missingEnv vars not setRun analysis without marketplace data, note limitation
Cost check blockedDaily budget exceededInform user, offer free-only analysis
Empty Shopping resultsNo products for keywordSuggest broader keyword, check location settings
Amazon API timeoutNetwork/rate limitRetry with backoff, fall back to Google-only
Invalid URLMalformed inputValidate via google_auth.validate_url(), show error
Non-product pageURL is category/homepageDetect page type, suggest /seo ecommerce schema instead

Output Template

## E-commerce SEO Report: [URL or Keyword]

### Overall Score: XX/100

### Product Page SEO
- Schema Completeness: XX/100
- Title & Meta: XX/100
- Image Optimization: XX/100
- Content Quality: XX/100
- Internal Linking: XX/100

### Marketplace Intelligence (if DataForSEO available)
- Google Shopping Listings: N products found
- Price Range: $XX - $XX (median: $XX)
- Top Seller: [name] (XX% market share)
- Amazon Comparison: [available/not checked]

### Top Recommendations
1. [Critical] ...
2. [High] ...
3. [Medium] ...

Generate a PDF report? Use `/seo google report`