seo-keyword-cluster

Cluster seed keywords into pillar and spoke articles with SERP-overlap analysis.

116|28|Updated Apr 24, 2026
One-click install
npx skills add https://github.com/seranking/seo-skills --skill seo-keyword-cluster-seranking
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: seo-keyword-cluster
Source: https://github.com/seranking/seo-skills/tree/main/skills/seo-keyword-cluster
Command: npx skills add https://github.com/seranking/seo-skills --skill seo-keyword-cluster-seranking

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Converts scattered seed keywords into structured, scalable content architectures (pillar pages with spoke articles), enabling efficient planning and execution of long-form SEO strategies.

Core Features & Use Cases

  • Intent-grouped clusters: Organize keywords by search intent and theme into pillars and spokes.
  • H1/H2 planning & internal linking: Generate H1 for pillars and H2s for spokes, plus a detailed internal-link map.
  • Prioritized build plan: Produce a clear sequence for content production with a target build order.
  • Use Case: When building a content calendar from a keyword list, this skill outputs a complete cluster plan ready for content development.

Quick Start

Provide a pillar-and-spokes content plan from the seed keywords for the target country.

Frequently Asked Questions about seo-keyword-cluster

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

FAQPage Schema
What is SERP overlap methodology for keyword clustering?

SERP overlap methodology groups seed keywords into topic-driven content clusters by analyzing shared top-10 URLs in search results. This identifies optimal pillar and spoke articles, ensuring strategic alignment and minimizing content cannibalization.

How do I build a pillar and spoke content plan from seed keywords?

To build a pillar and spoke content plan, provide your seed keywords to generate intent-grouped clusters. The system outputs H1 for pillars, H2s for spokes, and a detailed internal linking map to guide content production.

How do I prevent keyword cannibalization when planning topic clusters?

Prevent keyword cannibalization by applying a SERP-overlap quality scorecard. This validates cluster structures by checking for cannibalization, orphaning, coverage gaps, and anchor diversity to ensure distinct page targeting.

Does this approach generate a prioritized build plan for a content calendar?

Yes, this approach generates a prioritized build plan that produces a clear sequence for content production. It includes a target build order based on volume and KD metrics, ready for content development.

Can I use generated topic clusters to map internal linking between pages?

Yes, you can map internal linking between pillar and spoke articles. The clustering process generates a detailed internal-link map that defines anchor diversity and connects H1 pillar pages with H2 spoke articles.