seo-cluster

Cluster seed keywords by shared SERP rankings into hub-and-spoke architectures with link matrices and HTML maps.

8|5|Updated Feb 18, 2026

Search Tags:#content planning #internal linking #keyword research #seo #content architecture #hub and spoke #serp clustering

Ready to run

npx skills add https://github.com/shenxingy/Clade --skill seo-cluster-shenxingy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: seo-cluster
Source: https://github.com/shenxingy/Clade/tree/main/configs/skills/seo-cluster
Command: npx skills add https://github.com/shenxingy/Clade --skill seo-cluster-shenxingy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill turns scattered keywords into a defensible content architecture by clustering them according to what Google ranks together, so you avoid cannibalization and design hub-and-spoke pages that match search intent.

Core Features & Use Cases

SERP-overlap clustering: groups keywords by shared top-10 organic results (not by text similarity).
Hub-and-spoke architecture planning: selects pillar keywords, assigns spoke clusters, and defines templates and word-count targets.
Internal link matrix + interactive visualization: generates a bidirectional link plan and produces an HTML cluster map for review.
Optional execution workflow: can create content automatically if claude-blog is installed, otherwise it outputs detailed briefs.

Quick Start

Use the command "/seo cluster plan <seed-keyword>" to generate a complete clustered content architecture with link requirements and an interactive cluster map.

Frequently Asked Questions about seo-cluster

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

FAQPage Schema

What is SERP overlap clustering for SEO content architecture?▼

SERP overlap clustering groups keywords by shared top-10 organic results rather than text similarity. It transforms scattered keywords into hub-and-spoke content clusters that match how Google ranks pages, preventing keyword cannibalization.

How do I plan hub-and-spoke content clusters from seed keywords?▼

You can generate hub-and-spoke content clusters by running a seed keyword through SERP-based semantic clustering. The process selects pillar keywords, assigns spoke clusters, and defines templates with word-count targets for your content architecture.

Does this keyword clustering approach require DataForSEO or WebSearch data?▼

SERP data collection requires WebSearch or DataForSEO when available. The Skill uses this data to classify search intent and group keywords by actual organic result overlap, ensuring clusters reflect real ranking behavior.

How does internal link matrix generation work for topic clusters?▼

Internal link matrix generation creates a bidirectional link plan between pillar and spoke pages. It maps the hub-and-spoke relationships identified during keyword clustering to define the required internal linking structure for your content architecture.

Can I automatically draft content briefs after SERP clustering?▼

You can output detailed content briefs after SERP clustering, or execute automated drafting if the claude-blog tool is installed. Without it, the Skill provides comprehensive briefs to guide manual content creation.

Why group keywords by SERP overlap instead of text similarity for SEO?▼

Grouping by SERP overlap reflects how Google ranks results together, ensuring your content architecture matches actual search intent. Text similarity grouping often misses semantic relevance, leading to keyword cannibalization and poorly targeted pages.