110 lines
3.7 KiB
Markdown
110 lines
3.7 KiB
Markdown
---
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name: seo-ai-visibility
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description: |
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AI search visibility and brand radar monitoring. Tracks how a brand appears
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in AI-generated search answers using our-seo-agent CLI or pre-fetched data.
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Triggers: AI search, AI visibility, brand radar, AI citations,
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share of voice, AI answers, AI mentions.
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---
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# SEO AI Visibility & Brand Radar
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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.
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## Capabilities
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### AI Visibility Tracking
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- **Impressions Overview** - How often the brand appears in AI answers
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- **Mentions Overview** - Brand mention frequency across AI engines
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- **Share of Voice (SOV)** - Brand's share vs competitors in AI search
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- **Historical Trends** - Impressions, mentions, and SOV over time
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- **Competitor Comparison** - Side-by-side AI visibility metrics
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### AI Citation Analysis
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- **AI Response Analysis** - Content and sentiment of AI mentions
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- **Cited Domains** - Which source domains AI engines reference
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- **Cited Pages** - Specific URLs that get cited in AI answers
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- **Citation Ranking** - Frequency-based ranking of citations
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- **Sentiment Analysis** - Positive/neutral/negative distribution
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## Workflow
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1. **Input**: User provides target domain and optional competitors
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2. **Data Collection**: Fetch metrics from our-seo-agent CLI or pre-fetched JSON
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3. **Analysis**: Calculate trends, compare competitors, analyze sentiment
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4. **Recommendations**: Generate actionable Korean-language recommendations
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5. **Output**: JSON report and Notion database entry
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## Data Sources
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| Source | Purpose |
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|--------|---------|
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| `our-seo-agent` CLI | Primary AI visibility data source (future); use `--input` for pre-fetched JSON |
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| WebSearch / WebFetch | Supplementary AI search data |
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| Notion MCP | Save audit report to database |
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## Notion Output
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All reports are saved to the OurDigital SEO Audit Log:
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- **Database ID**: `2c8581e5-8a1e-8035-880b-e38cefc2f3ef`
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- **Category**: AI Search Visibility
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- **Audit ID Format**: AI-YYYYMMDD-NNN
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- **Language**: Korean (technical terms in English)
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## Output Format
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```json
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{
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"domain": "example.com",
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"impressions": {
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"total": 15000,
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"trend": "increasing",
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"period": "30d"
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},
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"mentions": {
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"total": 450,
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"positive": 320,
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"neutral": 100,
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"negative": 30,
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"sentiment_score": 0.72
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},
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"share_of_voice": {
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"domain_sov": 12.5,
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"competitors": {
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"competitor1.com": 18.3,
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"competitor2.com": 15.1
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}
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},
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"cited_pages": [
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{"url": "https://example.com/guide", "citations": 45},
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{"url": "https://example.com/faq", "citations": 28}
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],
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"cited_domains": [
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{"domain": "example.com", "citations": 120},
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{"domain": "competitor1.com", "citations": 95}
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],
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"recommendations": [
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"Create more FAQ-style content for AI citation capture",
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"Add structured data to improve AI answer extraction"
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],
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"audit_id": "AI-20250115-001",
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"timestamp": "2025-01-15T14:30:00"
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}
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```
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## Limitations
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- Requires our-seo-agent CLI or pre-fetched AI visibility data
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- AI search landscape changes rapidly; data may not reflect real-time state
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- Share of Voice metrics are relative to tracked competitor set only
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- Sentiment analysis based on AI-generated text, not user perception
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- Cannot distinguish between different AI engines (ChatGPT, Gemini, Perplexity) without Brand Radar
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## Example Queries
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- "example.com의 AI 검색 가시성을 분석해줘"
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- "AI search visibility for example.com with competitors"
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- "브랜드 레이더 분석: example.com vs competitor.com"
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- "AI 인용 분석 - 어떤 페이지가 AI 답변에서 인용되나요?"
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- "Share of Voice in AI search for our domain"
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