Keyword Clusterer Skill for Claude
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
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/guia-matthieu/clawfu-skills --skill keyword-clustererWhat comes with it
9 398 bytes besides the instructionThe instruction itself
18 sections, as written by the authorKeyword 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
- content-repurposer - Create content for clusters
- lighthouse-audit - Optimize cluster pages
Skill Metadata
- Mode: centaur
category: seo-tools
subcategory: keyword-research
dependencies: [scikit-learn, sentence-transformers, pandas]
difficulty: intermediate
time_saved: 5+ hours/week
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How to use it
Take guia-matthieu/keyword-clusterer from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip.
Without those the skill loads but fails at the first command.