our-claude-skills/custom-skills/20-seo-serp-analysis/desktop/SKILL.md

name, description

name	description
seo-serp-analysis	SERP analysis for Google and Naver search results. Triggers: SERP analysis, search results, featured snippet, SERP features, Naver SERP, 검색결과 분석, SERP 분석.

SEO SERP Analysis

Purpose

Analyze search engine result page composition for Google and Naver. Detect SERP features (featured snippets, PAA, knowledge panels, local pack, video, ads), map competitor positions, score SERP feature opportunities, and analyze Naver section distribution.

Core Capabilities

1. Google SERP Feature Detection - Identify featured snippets, PAA, knowledge panels, local pack, video carousel, ads, image pack, site links, shopping
2. Competitor Position Mapping - Extract domains, positions, content types for top organic results
3. Opportunity Scoring - Score SERP opportunity (0-100) based on feature landscape and competition
4. Search Intent Validation - Infer intent (informational, navigational, commercial, transactional, local) from SERP composition
5. Naver SERP Composition - Detect sections (blog, cafe, knowledge iN, Smart Store, brand zone, books, shortform, influencer), map section priority, analyze brand zone presence

MCP Tool Usage

SEO Data

our-seo-agent CLI: Primary data source (future); use --input for pre-fetched JSON
WebSearch / WebFetch: Live SERP data and keyword metrics

Notion for Report Storage

mcp__notion__notion-create-pages: Save analysis report to SEO Audit Log database
mcp__notion__notion-update-page: Update existing report entries

Web Tools for Naver Analysis

WebSearch: Discover Naver search trends
WebFetch: Fetch Naver SERP HTML for section analysis

Workflow

1. Google SERP Analysis

1. Fetch SERP data via our-seo-agent CLI, --input JSON, or WebSearch for the target keyword and country
2. Detect SERP features (featured snippet, PAA, local pack, knowledge panel, video, ads, images, shopping)
3. Map competitor positions from organic results (domain, URL, title, position)
4. Classify content type for each result (blog, product, service, news, video)
5. Calculate opportunity score (0-100) based on feature landscape
6. Validate search intent from SERP composition
7. Assess SERP volatility

2. Naver SERP Analysis

1. Fetch Naver search page for the target keyword
2. Detect SERP sections (blog, cafe, knowledge iN, Smart Store, brand zone, news, encyclopedia, books, shortform, influencer)
3. Map section priority (above-fold order)
4. Check brand zone presence and extract brand name
5. Count items per section
6. Identify dominant content section

3. Report Generation

1. Compile results into structured JSON
2. Generate Korean-language report
3. Save to Notion SEO Audit Log database

Output Format

{
  "keyword": "치과 임플란트",
  "country": "kr",
  "serp_features": {
    "featured_snippet": true,
    "people_also_ask": true,
    "local_pack": true,
    "knowledge_panel": false,
    "video_carousel": false,
    "ads_top": 3,
    "ads_bottom": 2
  },
  "competitors": [
    {
      "position": 1,
      "url": "https://example.com/page",
      "domain": "example.com",
      "title": "...",
      "content_type": "service_page"
    }
  ],
  "opportunity_score": 72,
  "intent_signals": "commercial",
  "timestamp": "2025-01-01T00:00:00"
}

Common SERP Features

Feature	Impact	Opportunity
Featured Snippet	High visibility above organic	Optimize content format for snippet capture
People Also Ask	Related question visibility	Create FAQ content targeting PAA
Local Pack	Dominates local intent SERPs	Optimize Google Business Profile
Knowledge Panel	Reduces organic CTR	Focus on brand queries and schema
Video Carousel	Visual SERP real estate	Create video content for keyword
Shopping	Transactional intent signal	Product feed optimization

Limitations

• SERP data may have a delay depending on data source (not real-time)
• Naver SERP HTML structure changes periodically
• Brand zone detection depends on HTML class patterns
• Cannot detect personalized SERP results

Notion Output (Required)

All audit reports MUST be saved to OurDigital SEO Audit Log:

• Database ID: 2c8581e5-8a1e-8035-880b-e38cefc2f3ef
• Properties: Issue (title), Site (url), Category, Priority, Found Date, Audit ID
• Language: Korean with English technical terms
• Audit ID Format: SERP-YYYYMMDD-NNN