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Andrew Yim a3ff965b87 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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name, description

name	description
seo-keyword-strategy	Keyword strategy and research for SEO campaigns. Triggers: keyword research, keyword analysis, keyword gap, search volume, keyword clustering, intent classification.

SEO Keyword Strategy & Research

Purpose

Expand seed keywords, classify search intent, cluster topics, and identify competitor keyword gaps for comprehensive keyword strategy development.

Core Capabilities

Keyword Expansion - Matching terms, related terms, search suggestions
Korean Market - Suffix expansion, Naver autocomplete, Korean intent patterns
Intent Classification - Informational, navigational, commercial, transactional
Topic Clustering - Group keywords into semantic clusters
Gap Analysis - Find competitor keywords missing from target site

MCP Tool Usage

Ahrefs for Keyword Data

mcp__ahrefs__keywords-explorer-overview: Get keyword metrics
mcp__ahrefs__keywords-explorer-matching-terms: Find keyword variations
mcp__ahrefs__keywords-explorer-related-terms: Discover related keywords
mcp__ahrefs__keywords-explorer-search-suggestions: Autocomplete suggestions
mcp__ahrefs__keywords-explorer-volume-by-country: Country volume comparison
mcp__ahrefs__site-explorer-organic-keywords: Competitor keyword rankings

Web Search for Naver Discovery

WebSearch: Naver autocomplete and trend discovery

Workflow

1. Seed Keyword Expansion

Input seed keyword (Korean or English)
Query Ahrefs matching-terms and related-terms
Get search suggestions for long-tail variations
Apply Korean suffix expansion if Korean market
Deduplicate and merge results

2. Intent Classification & Clustering

Classify each keyword by search intent
Group keywords into topic clusters
Identify pillar topics and supporting terms
Calculate cluster-level metrics (total volume, avg KD)

3. Gap Analysis

Pull organic keywords for target and competitors
Identify keywords present in competitors but missing from target
Score opportunities by volume/difficulty ratio
Prioritize by intent alignment with business goals

Output Format

## Keyword Strategy Report: [seed keyword]

### Overview
- Total keywords discovered: [count]
- Topic clusters: [count]
- Total search volume: [sum]

### Top Clusters
| Cluster | Keywords | Total Volume | Avg KD |
|---------|----------|-------------|--------|
| ... | ... | ... | ... |

### Top Opportunities
| Keyword | Volume | KD | Intent | Cluster |
|---------|--------|-----|--------|---------|
| ... | ... | ... | ... | ... |

### Keyword Gaps (vs competitors)
| Keyword | Volume | Competitor Position | Opportunity Score |
|---------|--------|-------------------|-------------------|
| ... | ... | ... | ... |

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: KW-YYYYMMDD-NNN

3.0 KiB Raw Blame History