Add SEO skills 19-28, 31-32 with full Python implementations

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>
2026-02-13 12:05:59 +09:00
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+# CLAUDE.md
+
+## Overview
+
+Knowledge Graph and Entity SEO tool for analyzing brand entity presence in Google Knowledge Graph, Knowledge Panels, People Also Ask (PAA), and FAQ rich results. Checks entity attribute completeness, Wikipedia/Wikidata presence, and Korean equivalents (Naver knowledge iN, Naver encyclopedia). Uses WebSearch and WebFetch for data collection, Ahrefs serp-overview for SERP feature detection.
+
+## Quick Start
+
+```bash
+pip install -r scripts/requirements.txt
+
+# Knowledge Graph analysis
+python scripts/knowledge_graph_analyzer.py --entity "Samsung Electronics" --json
+
+# Entity SEO audit
+python scripts/entity_auditor.py --url https://example.com --entity "Brand Name" --json
+```
+
+## Scripts
+
+| Script | Purpose | Key Output |
+|--------|---------|------------|
+| `knowledge_graph_analyzer.py` | Analyze Knowledge Panel and entity presence | KP detection, entity attributes, Wikipedia/Wikidata status |
+| `entity_auditor.py` | Audit entity SEO signals and PAA/FAQ presence | PAA monitoring, FAQ schema tracking, entity completeness |
+| `base_client.py` | Shared utilities | RateLimiter, ConfigManager, BaseAsyncClient |
+
+## Knowledge Graph Analyzer
+
+```bash
+# Analyze entity in Knowledge Graph
+python scripts/knowledge_graph_analyzer.py --entity "Samsung Electronics" --json
+
+# Check with Korean name
+python scripts/knowledge_graph_analyzer.py --entity "삼성전자" --language ko --json
+
+# Include Wikipedia/Wikidata check
+python scripts/knowledge_graph_analyzer.py --entity "Samsung" --wiki --json
+```
+
+**Capabilities**:
+- Knowledge Panel detection via Google search
+- Entity attribute extraction (name, description, logo, type, social profiles, website)
+- Entity attribute completeness scoring
+- Wikipedia article presence check
+- Wikidata entity presence check (QID lookup)
+- Naver encyclopedia (네이버 백과사전) presence
+- Naver knowledge iN (지식iN) presence
+- Knowledge Panel comparison with competitors
+
+## Entity Auditor
+
+```bash
+# Full entity SEO audit
+python scripts/entity_auditor.py --url https://example.com --entity "Brand Name" --json
+
+# PAA monitoring for brand keywords
+python scripts/entity_auditor.py --url https://example.com --entity "Brand Name" --paa --json
+
+# FAQ rich result tracking
+python scripts/entity_auditor.py --url https://example.com --entity "Brand Name" --faq --json
+```
+
+**Capabilities**:
+- People Also Ask (PAA) monitoring for brand-related queries
+- FAQ schema presence tracking (FAQPage schema -> SERP appearance)
+- Entity markup audit (Organization, Person, LocalBusiness schema on website)
+- Social profile linking validation (sameAs in schema)
+- Brand SERP analysis (what appears when you search the brand name)
+- Entity consistency across web properties
+- Korean entity optimization (Korean Knowledge Panel, Naver profiles)
+
+## Data Sources
+
+| Source | Purpose |
+|--------|---------|
+| WebSearch | Search for entity/brand to detect Knowledge Panel |
+| WebFetch | Fetch Wikipedia, Wikidata, Naver pages |
+| Ahrefs `serp-overview` | SERP feature detection for entity keywords |
+
+## Output Format
+
+```json
+{
+  "entity": "Samsung Electronics",
+  "knowledge_panel": {
+    "detected": true,
+    "attributes": {
+      "name": "Samsung Electronics",
+      "type": "Corporation",
+      "description": "...",
+      "logo": true,
+      "website": true,
+      "social_profiles": ["twitter", "facebook", "linkedin"]
+    },
+    "completeness_score": 85
+  },
+  "wikipedia": {"present": true, "url": "..."},
+  "wikidata": {"present": true, "qid": "Q20710"},
+  "naver_encyclopedia": {"present": true, "url": "..."},
+  "naver_knowledge_in": {"present": true, "entries": 15},
+  "paa_questions": [...],
+  "faq_rich_results": [...],
+  "entity_schema_on_site": {
+    "organization": true,
+    "same_as_links": 5,
+    "completeness": 78
+  },
+  "score": 75,
+  "timestamp": "2025-01-01T00:00:00"
+}
+```
+
+## Notion Output (Required)
+
+**IMPORTANT**: All audit reports MUST be saved to the OurDigital SEO Audit Log database.
+
+### Database Configuration
+
+| Field | Value |
+|-------|-------|
+| Database ID | `2c8581e5-8a1e-8035-880b-e38cefc2f3ef` |
+| URL | https://www.notion.so/dintelligence/2c8581e58a1e8035880be38cefc2f3ef |
+
+### Required Properties
+
+| Property | Type | Description |
+|----------|------|-------------|
+| Issue | Title | Report title (Korean + date) |
+| Site | URL | Entity website URL |
+| Category | Select | Knowledge Graph & Entity SEO |
+| Priority | Select | Based on entity completeness |
+| Found Date | Date | Audit date (YYYY-MM-DD) |
+| Audit ID | Rich Text | Format: KG-YYYYMMDD-NNN |
+
+### Language Guidelines
+
+- Report content in Korean (한국어)
+- Keep technical English terms as-is (e.g., Knowledge Panel, Knowledge Graph, PAA)
+- URLs and code remain unchanged