Seo Ecommerce logo

Seo Ecommerce

CommunityPopular
AgriciDaniel
seo-ecommerce

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".

Overview

PublisherAgriciDaniel
Repositoryclaude-seo
Skill nameseo-ecommerce
Stars
17.1K
Forks
2.5K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Seo Ecommerce AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgriciDaniel/claude-seo.git /tmp/claude-seo
mkdir -p .claude/skills
cp -r /tmp/claude-seo/skills/seo-ecommerce .claude/skills/seo-ecommerce
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Seo Ecommerce in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Seo Ecommerce on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Seo Ecommerce is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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. "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run render_page.py <url> --mode auto → raw/rendered HTML
2. "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run 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:

bash
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run 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:

bash
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_costs.py log merchant_google_products_search <cost>

Workflow

bash
# Product search: who sells what at what price
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py search "<keyword>" --marketplace google

# Seller analysis: merchant ratings and dominance
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py sellers "<keyword>"

# Normalize results for analysis
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run 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)

bash
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_costs.py check merchant_amazon_products_search

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

Workflow

bash
# Amazon product search
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run dataforseo_merchant.py search "<keyword>" --marketplace amazon

# Cross-marketplace comparison
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run 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.

Confirmed Required Properties (Google Merchant)

Confirmed required fields are name, image, and offers; use Offer, not AggregateOffer, for merchant listings.

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

Recommended Properties (Enhance Rich Results)

  • sku -- product identifier
  • description, brand, offers.seller -- recommended context fields
  • 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 (merchant-level shipping via ShippingService is also supported; shipping/returns can be set in Search Console without a Merchant Center account)
  • hasMerchantReturnPolicy -- MerchantReturnPolicy with type and days
  • hasAdultConsideration -- required for adult-oriented products (added 2026-05-20 to Product variant / Merchant listing); Google Search supports only the value https://schema.org/SexualContentConsideration
  • category -- Text, CategoryCode, or an array mixing both. Use custom text for merchant-defined product types and CategoryCode with Google's taxonomy URL plus codeValue for Google Product Categories.

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. If brand is present, brand.name must not be empty or "N/A"
  6. Sale periods use validFrom plus either validThrough or priceValidUntil, in ISO 8601 format. Include time and timezone when known.
  7. If aggregateRating present: ratingValue and reviewCount required
  8. Do not include fake reviews or undisclosed incentivized reviews in visible content or structured data. Clearly and prominently disclose incentives.

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-hreflangRegion-specific result units: product queries in the EEA, South Africa, and Turkiye can show supplier units and carousels with their own eligibility rules (documented 2026-09-08)
seo-googleGSC indexation + Performance data for product URLs (NOT Merchant Center feed validation, that is done in Merchant Center / the Merchant API; the legacy Content API for Shopping sunsets 2026-08-18)

UCP: Universal Commerce Protocol (live)

Google-initiated open standard (co-developed with Shopify, Etsy, Wayfair, Target, Walmart; payment partners Visa/Mastercard/Stripe/Adyen/Amex) for letting AI agents discover, negotiate, and transact with merchants without one-off integrations. Google confirms a first reference implementation for conversational buying in AI Mode in Search. Broader Universal Cart rollout details are reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source. ucp.dev lists 2026-04-08 as the latest release in its date-based versioning scheme, not 1.0; two integration paths: Native (default) and Embedded (approved merchants). Pairs with AP2 (reportedly moving toward FIDO governance). Canonical: developers.google.com/merchant/ucp and ucp.dev.

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

bash
# Discover and validate the UCP profile
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run ucp_check.py https://store.example.com --json

# With endpoint reachability probes (HEAD each declared capability)
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run 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 itself is live; what's early is broad merchant adoption. Flag a literal "version": "1.0" as invalid (UCP versions are date-based, e.g. 2026-04-08).


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`

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Seo Ecommerce AI skill do?

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".

Why use Seo Ecommerce on TypingMind?

Because you install it once and use it with any model. Seo Ecommerce is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Seo Ecommerce in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-ecommerce. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Seo Ecommerce?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Seo Ecommerce?

As many as you like. As long as a model supports skills, you can use Seo Ecommerce with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Seo Ecommerce AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇