Andrew Yim
a3ff965b87
12 new skills: Keyword Strategy, SERP Analysis, Position Tracking, Link Building, Content Strategy, E-Commerce SEO, KPI Framework, International SEO, AI Visibility, Knowledge Graph, Competitor Intel, and Crawl Budget. ~20K lines of Python across 25 domain scripts. Updated skill 11 pipeline table and repo CLAUDE.md. Enhanced skill 18 local SEO workflow from jamie.clinic audit. Note: Skill 26 hreflang_validator.py pending (content filter block). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
137 lines
4.3 KiB
Markdown
137 lines
4.3 KiB
Markdown
# CLAUDE.md
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## Overview
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E-commerce SEO audit tool for product page optimization, product schema validation, category taxonomy analysis, and marketplace presence checking. Supports Naver Smart Store optimization and Korean marketplace platforms (Coupang, Gmarket, 11번가).
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## Quick Start
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```bash
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pip install -r scripts/requirements.txt
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# E-commerce SEO audit
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python scripts/ecommerce_auditor.py --url https://example.com --json
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# Product schema validation
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python scripts/product_schema_checker.py --url https://example.com/product --json
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```
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## Scripts
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| Script | Purpose | Key Output |
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|--------|---------|------------|
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| `ecommerce_auditor.py` | Full e-commerce SEO audit | Product page issues, category structure, marketplace presence |
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| `product_schema_checker.py` | Validate product structured data | Schema completeness, errors, rich result eligibility |
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| `base_client.py` | Shared utilities | RateLimiter, ConfigManager, BaseAsyncClient |
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## E-Commerce Auditor
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```bash
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# Full audit
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python scripts/ecommerce_auditor.py --url https://example.com --json
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# Product page audit only
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python scripts/ecommerce_auditor.py --url https://example.com --scope products --json
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# Category taxonomy analysis
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python scripts/ecommerce_auditor.py --url https://example.com --scope categories --json
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# Check Korean marketplace presence
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python scripts/ecommerce_auditor.py --url https://example.com --korean-marketplaces --json
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```
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**Capabilities**:
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- Product page SEO audit (titles, meta descriptions, image alt text, H1 structure)
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- Category taxonomy analysis (depth, breadcrumb implementation, faceted navigation)
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- Duplicate content detection (parameter URLs, product variants, pagination)
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- Pagination/infinite scroll SEO validation (rel=prev/next, canonical tags)
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- Internal linking structure for product discovery
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- Naver Smart Store optimization checks
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- Korean marketplace presence (Coupang, Gmarket, 11번가 product listing detection)
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## Product Schema Checker
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```bash
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# Validate single product page
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python scripts/product_schema_checker.py --url https://example.com/product/123 --json
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# Batch validate from sitemap
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python scripts/product_schema_checker.py --sitemap https://example.com/product-sitemap.xml --sample 50 --json
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```
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**Capabilities**:
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- Product schema validation (Product, Offer, AggregateRating, Review, BreadcrumbList)
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- Required property completeness check (name, image, description, offers, price, availability)
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- Optional property recommendations (brand, sku, gtin, mpn, review, aggregateRating)
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- Rich result eligibility assessment
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- Price and availability markup validation
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- Merchant listing schema support
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- Korean market: Naver Shopping structured data requirements
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## Ahrefs MCP Tools Used
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| Tool | Purpose |
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|------|---------|
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| `site-explorer-pages-by-traffic` | Identify top product/category pages |
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| `site-explorer-organic-keywords` | Product page keyword performance |
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## Output Format
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```json
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{
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"url": "https://example.com",
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"product_pages_audited": 50,
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"issues": {
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"critical": [...],
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"high": [...],
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"medium": [...],
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"low": [...]
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},
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"category_structure": {
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"max_depth": 4,
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"breadcrumbs_present": true,
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"faceted_nav_issues": [...]
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},
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"schema_validation": {
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"pages_with_schema": 42,
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"pages_without_schema": 8,
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"common_errors": [...]
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},
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"korean_marketplaces": {
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"naver_smart_store": {"found": true, "url": "..."},
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"coupang": {"found": false},
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"gmarket": {"found": false}
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},
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"score": 65,
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"timestamp": "2025-01-01T00:00:00"
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}
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```
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## Notion Output (Required)
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**IMPORTANT**: All audit reports MUST be saved to the OurDigital SEO Audit Log database.
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### Database Configuration
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| Field | Value |
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|-------|-------|
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| Database ID | `2c8581e5-8a1e-8035-880b-e38cefc2f3ef` |
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| URL | https://www.notion.so/dintelligence/2c8581e58a1e8035880be38cefc2f3ef |
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### Required Properties
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| Property | Type | Description |
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|----------|------|-------------|
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| Issue | Title | Report title (Korean + date) |
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| Site | URL | Audited website URL |
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| Category | Select | E-Commerce SEO |
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| Priority | Select | Based on issue severity |
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| Found Date | Date | Audit date (YYYY-MM-DD) |
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| Audit ID | Rich Text | Format: ECOM-YYYYMMDD-NNN |
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### Language Guidelines
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- Report content in Korean (한국어)
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- Keep technical English terms as-is (e.g., Schema Markup, Product, Offer)
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- URLs and code remain unchanged
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