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keyword-clusterer

Cluster keywords by semantic similarity and intent. Use when: organizing keyword research; creating content pillars; mapping keywords to pages; identifying content gaps; grouping search intent

personAuthor: jakexiaohubgithub
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Keyword Clusterer

Group keywords by semantic similarity using embeddings - turn a keyword list into an organized content strategy.

When to Use This Skill

  • Content planning - Group keywords into topic clusters
  • Site structure - Map keywords to pages
  • Intent analysis - Categorize by search intent
  • Gap analysis - Find missing keyword themes
  • PPC organization - Group keywords for ad groups

What Claude Does vs What You Decide

| Claude Does | You Decide | |-------------|------------| | Structures analysis frameworks | Strategic priorities | | Synthesizes market data | Competitive positioning | | Identifies opportunities | Resource allocation | | Creates strategic options | Final strategy selection | | Suggests implementation approaches | Execution decisions |

Dependencies

pip install scikit-learn sentence-transformers pandas click
# For simpler usage without ML:
pip install click pandas

Commands

Cluster Keywords

python scripts/main.py cluster keywords.csv --n-clusters 10
python scripts/main.py cluster keywords.csv --column keyword --n-clusters 15

Find Similar

python scripts/main.py similar "content marketing" --count 20

Analyze Intent

python scripts/main.py intent keywords.csv --column keyword

Examples

Example 1: Cluster Keyword Research

# Input: keywords.csv with 500 keywords
python scripts/main.py cluster keywords.csv --n-clusters 12 --output clustered.csv

# Output:
# Cluster 1 (45 keywords): "content marketing"
#   - content marketing strategy
#   - content marketing tips
#   - how to do content marketing
#
# Cluster 2 (38 keywords): "email marketing"
#   - email marketing tools
#   - best email marketing software
#   - email campaign tips
# ...

Example 2: Categorize by Intent

python scripts/main.py intent keywords.csv --column keyword

# Output:
# Intent Analysis
# ──────────────────────
# Informational: 234 (47%)
#   - how to, what is, guide, tips
# Commercial: 156 (31%)
#   - best, top, review, compare
# Transactional: 78 (16%)
#   - buy, price, discount, order
# Navigational: 32 (6%)
#   - login, contact, brand names

Search Intent Categories

| Intent | Signals | Content Type | |--------|---------|--------------| | Informational | how, what, why, guide | Blog posts, guides | | Commercial | best, top, review, vs | Comparisons, reviews | | Transactional | buy, price, discount | Product pages | | Navigational | [brand], login, contact | Landing pages |

Clustering Methods

| Method | Best For | Speed | |--------|----------|-------| | semantic | Meaning-based grouping | Slower | | lexical | Word overlap grouping | Faster | | intent | Search intent categories | Fast |

Skill Boundaries

What This Skill Does Well

  • Structuring strategic analysis
  • Identifying market opportunities
  • Creating strategic frameworks
  • Synthesizing competitive data

What This Skill Cannot Do

  • Replace market research
  • Guarantee strategic success
  • Know proprietary competitor info
  • Make executive decisions

Related Skills

Skill Metadata

  • Mode: centaur
category: seo-tools
subcategory: keyword-research
dependencies: [scikit-learn, sentence-transformers, pandas]
difficulty: intermediate
time_saved: 5+ hours/week