our-claude-skills/custom-skills/27-seo-ai-visibility/desktop/SKILL.md

name, description

name	description
seo-ai-visibility	AI search visibility and brand radar monitoring. Tracks how a brand appears in AI-generated search answers using our-seo-agent CLI or pre-fetched data. Triggers: AI search, AI visibility, brand radar, AI citations, share of voice, AI answers, AI mentions.

SEO AI Visibility & Brand Radar

Monitor and analyze brand visibility in AI-generated search results. This skill uses our-seo-agent CLI or pre-fetched data to track impressions, mentions, share of voice, cited domains, cited pages, and AI response content.

Capabilities

AI Visibility Tracking

• Impressions Overview - How often the brand appears in AI answers
• Mentions Overview - Brand mention frequency across AI engines
• Share of Voice (SOV) - Brand's share vs competitors in AI search
• Historical Trends - Impressions, mentions, and SOV over time
• Competitor Comparison - Side-by-side AI visibility metrics

AI Citation Analysis

• AI Response Analysis - Content and sentiment of AI mentions
• Cited Domains - Which source domains AI engines reference
• Cited Pages - Specific URLs that get cited in AI answers
• Citation Ranking - Frequency-based ranking of citations
• Sentiment Analysis - Positive/neutral/negative distribution

Workflow

1. Input: User provides target domain and optional competitors
2. Data Collection: Fetch metrics from our-seo-agent CLI or pre-fetched JSON
3. Analysis: Calculate trends, compare competitors, analyze sentiment
4. Recommendations: Generate actionable Korean-language recommendations
5. Output: JSON report and Notion database entry

Data Sources

Source	Purpose
our-seo-agent CLI	Primary AI visibility data source (future); use --input for pre-fetched JSON
WebSearch / WebFetch	Supplementary AI search data
Notion MCP	Save audit report to database

Notion Output

All reports are saved to the OurDigital SEO Audit Log:

• Database ID: 2c8581e5-8a1e-8035-880b-e38cefc2f3ef
• Category: AI Search Visibility
• Audit ID Format: AI-YYYYMMDD-NNN
• Language: Korean (technical terms in English)

Output Format

{
  "domain": "example.com",
  "impressions": {
    "total": 15000,
    "trend": "increasing",
    "period": "30d"
  },
  "mentions": {
    "total": 450,
    "positive": 320,
    "neutral": 100,
    "negative": 30,
    "sentiment_score": 0.72
  },
  "share_of_voice": {
    "domain_sov": 12.5,
    "competitors": {
      "competitor1.com": 18.3,
      "competitor2.com": 15.1
    }
  },
  "cited_pages": [
    {"url": "https://example.com/guide", "citations": 45},
    {"url": "https://example.com/faq", "citations": 28}
  ],
  "cited_domains": [
    {"domain": "example.com", "citations": 120},
    {"domain": "competitor1.com", "citations": 95}
  ],
  "recommendations": [
    "Create more FAQ-style content for AI citation capture",
    "Add structured data to improve AI answer extraction"
  ],
  "audit_id": "AI-20250115-001",
  "timestamp": "2025-01-15T14:30:00"
}

Limitations

• Requires our-seo-agent CLI or pre-fetched AI visibility data
• AI search landscape changes rapidly; data may not reflect real-time state
• Share of Voice metrics are relative to tracked competitor set only
• Sentiment analysis based on AI-generated text, not user perception
• Cannot distinguish between different AI engines (ChatGPT, Gemini, Perplexity) without Brand Radar

Example Queries

• "example.com의 AI 검색 가시성을 분석해줘"
• "AI search visibility for example.com with competitors"
• "브랜드 레이더 분석: example.com vs competitor.com"
• "AI 인용 분석 - 어떤 페이지가 AI 답변에서 인용되나요?"
• "Share of Voice in AI search for our domain"