nod-serp-clusters

Cluster keywords by SERP similarity or semantic analysis using Python.

39|7|Updated Apr 13, 2026
One-click install
npx skills add https://github.com/Senuto/nodeshub-seo-skills --skill nod-serp-clusters
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: nod-serp-clusters
Source: https://github.com/Senuto/nodeshub-seo-skills/tree/main/.claude/skills/nod-serp-clusters
Command: npx skills add https://github.com/Senuto/nodeshub-seo-skills --skill nod-serp-clusters

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nodeshub, openrouter, python, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies keyword clustering by automatically grouping keywords based on their similarity in Google search results, saving time and effort in SEO strategy development.

Core Features & Use Cases

  • SERP-based Clustering: Groups keywords sharing similar Google search results.
  • Semantic Clustering: Groups keywords with similar meanings or intents.
  • Multi-level Clustering: Offers hierarchical clustering at various depths for detailed analysis.
  • LLM Naming: Utilizes Language Learning Models to generate descriptive cluster names.
  • Report Generation: Provides detailed reports with dendrograms and domain visibility for easy interpretation.
  • Use Case: Suppose you have a list of keywords for a new website. Use this Skill to cluster them and generate a report showing how they can be organized into topics or content sections.

Quick Start

Use the nod-serp-clusters skill to cluster your keyword list and generate a report.

Frequently Asked Questions about nod-serp-clusters

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate keyword clustering based on SERP similarity for SEO?

Automate keyword clustering by grouping keywords that share similar Google search results. This Skill uses SERP similarity and semantic analysis to organize your keyword list into structured topics for SEO strategy.

What's the best way to group keywords by search intent for content planning?

Group keywords by search intent using semantic clustering, which analyzes similar meanings across queries. This process organizes keywords into hierarchical, multi-level clusters to guide your content planning and topic structuring.

Do I need Python and API keys to run SERP-based cluster analysis?

Yes, you need Python for execution and environment setup, a NodesHub API for SERP data retrieval, and an OpenRouter API for LLM naming. These dependencies are required to generate clustering reports.

Can I generate visual reports with dendrograms from my keyword clusters?

Yes, you can generate detailed reports with dendrograms and domain visibility metrics. These visual outputs help you interpret cluster relationships and understand competitive analysis for your SEO strategy.

How does LLM naming work for SEO keyword groups?

LLM naming utilizes Language Learning Models via the OpenRouter API to generate descriptive names for keyword clusters. This automatically labels grouped keywords based on their semantic similarity and SERP overlap.

What is the difference between SERP-based clustering and semantic clustering?

SERP-based clustering groups keywords sharing similar Google search results, while semantic clustering groups keywords with similar meanings or intents. This Skill supports both methods for comprehensive SEO keyword strategy.