seomachine: Command for Claude Code

Cluster Command

Build a complete topic cluster strategy with pillar page definition, 8-12 supporting articles, internal linking map, and creation sequence.

Usage

/cluster [topic]

Examples:

• /cluster "content marketing"
• /cluster "podcast monetization"
• /cluster "remote team management"

Process

Step 1: Gather Existing Data

Check for existing research that informs this cluster:

1. Search research/ for any existing /research-topics output:

   Glob: research/topic-clusters-*.md
   

2. Search for any existing research on this topic:

   Glob: research/*[topic-slug]*.md
   

3. If found, extract:
   • Authority score for this topic area
   • Keywords already ranking
   • Coverage gaps identified
   • Any SERP analysis already done

Document what exists vs. what needs fresh research.

Step 2: Keyword Research

Build the complete keyword landscape for this topic.

1. DataForSEO Keyword Ideas

   python3 -c "
   import sys; sys.path.insert(0, 'data_sources/modules')
   from dataforseo import DataForSEOClient
   client = DataForSEOClient()
   results = client.get_keyword_ideas('$ARGUMENTS')
   for kw in sorted(results, key=lambda x: x.get('search_volume', 0), reverse=True)[:30]:
       print(f\"{kw.get('keyword', 'N/A')} | Vol: {kw.get('search_volume', 'N/A')} | Diff: {kw.get('keyword_difficulty', 'N/A')} | CPC: {kw.get('cpc', 'N/A')}\")
   "
   

2. DataForSEO Questions

   python3 -c "
   import sys; sys.path.insert(0, 'data_sources/modules')
   from dataforseo import DataForSEOClient
   client = DataForSEOClient()
   results = client.get_questions('$ARGUMENTS')
   for q in results[:15]:
       print(f\"{q.get('keyword', 'N/A')} | Vol: {q.get('search_volume', 'N/A')}\")
   "
   

3. WebSearch for Additional Keywords

   WebSearch: "[topic] guide" site:ahrefs.com OR site:semrush.com OR site:moz.com
   WebSearch: "[topic] related keywords" OR "[topic] subtopics"
   

4. Group Keywords into Tiers

   • Pillar-level: Broad, high-volume (1000+ searches/mo), competitive
   • Supporting-level: Specific subtopics, medium volume (100-1000/mo)
   • Long-tail: Very specific queries, low volume (<100/mo), low competition