Files
our-claude-skills/custom-skills/28-seo-knowledge-graph/desktop/SKILL.md
Andrew Yim d2d0a2d460 Add SEO skills 33-34 and fix bugs in skills 19-34
New skills:
- Skill 33: Site migration planner with redirect mapping and monitoring
- Skill 34: Reporting dashboard with HTML charts and Korean executive reports

Bug fixes (Skill 34 - report_aggregator.py):
- Add audit_type fallback for skill identification (was only using audit_id prefix)
- Extract health scores from nested data dict (technical_score, onpage_score, etc.)
- Support subdomain matching in domain filter (blog.ourdigital.org matches ourdigital.org)
- Skip self-referencing DASH- aggregated reports

Bug fixes (Skill 20 - naver_serp_analyzer.py):
- Remove VIEW tab selectors (removed by Naver in 2026)
- Add new section detectors: books (도서), shortform (숏폼), influencer (인플루언서)

Improvements (Skill 34 - dashboard/executive report):
- Add Korean category labels for Chart.js charts (기술 SEO, 온페이지, etc.)
- Add Korean trend labels (개선 중 ↑, 안정 →, 하락 중 ↓)
- Add English→Korean issue description translation layer (20 common patterns)

Documentation improvements:
- Add Korean triggers to 4 skill descriptions (19, 25, 28, 31)
- Expand Skill 32 SKILL.md from 40→143 lines (was 6/10, added workflow, output format, limitations)
- Add output format examples to Skills 27 and 28 SKILL.md
- Add limitations sections to Skills 27 and 28
- Update README.md, CLAUDE.md, AGENTS.md for skills 33-34

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-14 00:01:00 +09:00

4.5 KiB

name, description
name description
seo-knowledge-graph Knowledge Graph and entity SEO analysis. Triggers: knowledge panel, entity SEO, knowledge graph, PAA, FAQ schema, Wikipedia, Wikidata, brand entity, 지식 그래프, 엔티티 SEO, 지식 패널, 브랜드 엔티티, 위키데이터.

Knowledge Graph & Entity SEO

Analyze brand entity presence in Google Knowledge Graph, Knowledge Panels, People Also Ask (PAA), and FAQ rich results. Check entity attribute completeness, Wikipedia/Wikidata presence, and Korean equivalents (Naver knowledge iN, Naver encyclopedia).

Capabilities

Knowledge Graph Analysis

  • Knowledge Panel detection and attribute extraction
  • Entity attribute completeness scoring (name, description, logo, type, social profiles, website, founded, CEO)
  • Wikipedia article presence check
  • Wikidata entity presence check (QID lookup)
  • Naver encyclopedia (네이버 백과사전) presence
  • Naver knowledge iN (지식iN) presence

Entity SEO Audit

  • 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

Workflow

Knowledge Graph Analysis

  1. Use WebSearch to search for the entity name on Google
  2. Analyze search results for Knowledge Panel indicators
  3. Use WebFetch to check Wikipedia article existence
  4. Use WebFetch to check Wikidata QID existence
  5. Use WebFetch to check Naver encyclopedia and 지식iN
  6. Score entity attribute completeness
  7. Save report to Notion SEO Audit Log

Entity SEO Audit

  1. Use WebFetch to fetch the website and extract JSON-LD schemas
  2. Validate Organization/Person/LocalBusiness schema completeness
  3. Check sameAs links accessibility
  4. Use WebSearch to search brand name and analyze SERP features
  5. Monitor PAA questions for brand keywords
  6. Use Ahrefs serp-overview for SERP feature detection
  7. Save report to Notion SEO Audit Log

Tools Used

Tool Purpose
WebSearch Search for entity/brand to detect Knowledge Panel
WebFetch Fetch Wikipedia, Wikidata, Naver pages, website schemas
Ahrefs serp-overview SERP feature detection for entity keywords
Notion Save audit reports to SEO Audit Log database

Notion Output

All reports must be saved to the OurDigital SEO Audit Log database.

Field Value
Database ID 2c8581e5-8a1e-8035-880b-e38cefc2f3ef
Category Knowledge Graph & Entity SEO
Audit ID KG-YYYYMMDD-NNN

Report content should be written in Korean (한국어), keeping technical English terms as-is.

Output Format

{
  "entity_name": "OurDigital",
  "knowledge_panel": {
    "present": false,
    "attributes": {}
  },
  "entity_presence": {
    "wikipedia": false,
    "wikidata": false,
    "wikidata_qid": null,
    "naver_encyclopedia": false,
    "naver_knowledge_in": false,
    "google_knowledge_panel": false
  },
  "entity_schema": {
    "organization_count": 2,
    "person_count": 1,
    "same_as_links": ["https://linkedin.com/...", "https://facebook.com/..."],
    "same_as_count": 2,
    "issues": [
      "Duplicate Organization schemas with inconsistent names",
      "Placeholder image in Organization schema",
      "Only 2 sameAs links (recommend 6+)"
    ]
  },
  "paa_questions": [],
  "faq_schema_present": false,
  "entity_completeness_score": 12,
  "recommendations": [
    "Create Wikidata entity for brand recognition",
    "Add 4-6 more sameAs social profile links",
    "Replace placeholder image with actual brand logo",
    "Consolidate duplicate Organization schemas",
    "Add FAQPage schema to relevant pages"
  ],
  "audit_id": "KG-20250115-001",
  "timestamp": "2025-01-15T14:30:00"
}

Limitations

  • Google Knowledge Panel detection via search results is not guaranteed (personalization, location-based)
  • Direct Google scraping may be blocked (403/429); prefer WebSearch tool
  • Wikipedia/Wikidata creation requires meeting notability guidelines
  • PAA questions vary by location and device
  • Entity completeness scoring is heuristic-based

Reference Scripts

Located in code/scripts/:

  • knowledge_graph_analyzer.py — Knowledge Panel and entity presence analysis
  • entity_auditor.py — Entity SEO signals and PAA/FAQ audit
  • base_client.py — Shared async client utilities