seo-cluster

Generate SERP-overlap keyword clusters into pillar and spoke content plans.

Updated Mar 22, 2026
One-click install
npx skills add https://github.com/upmarking/fastesthr-20077824 --skill seo-cluster-upmarking
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seo-cluster
Source: https://github.com/upmarking/fastesthr-20077824/tree/main/.agents/skills/seo-cluster
Command: npx skills add https://github.com/upmarking/fastesthr-20077824 --skill seo-cluster-upmarking

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Clustering content topics by SERP overlap enables scalable content architectures, turning search results into a concrete hub-and-spoke plan and improving internal linking and topic authority.

Core Features & Use Cases

  • SERP-overlap driven clustering to group keywords by actual SERP overlap rather than text similarity.
  • Hub-and-spoke architecture design with a pillar page and related spokes to cover subtopics.
  • Interactive cluster map generation and machine-readable cluster-plan outputs for downstream tooling.
  • Strategy import, execution workflow guidance, and compatibility with SEO tooling (e.g., DataForSEO).

Quick Start

Start by providing a seed keyword or URL to begin the clustering and generate a complete cluster plan.

Frequently Asked Questions about seo-cluster

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

FAQPage Schema
What is SERP-overlap based topic clustering for SEO?▼

SERP-overlap topic clustering groups keywords by shared search engine results rather than text similarity. This approach reveals true hub-and-spoke relationships, enabling you to design pillar pages and spokes that build topic authority through targeted internal linking.

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

To create a hub-and-spoke content plan, provide a seed keyword or URL. The system validates inputs, groups keywords into pillar and spoke structures using SERP overlap, and outputs a machine-readable cluster plan with internal-linking guidance for downstream execution.

Why use SERP overlap instead of text similarity for keyword clustering?▼

Using SERP overlap for keyword clustering groups keywords based on actual search intent and ranking pages, not just lexical similarity. This ensures your hub-and-spoke architecture reflects how search engines interpret topics, resulting in more accurate internal linking and topic authority.

Can I import an existing SEO strategy into a topic clustering workflow?▼

Yes, you can import an optional SEO strategy into the topic clustering workflow. The system supports strategy imports to guide the SERP-overlap analysis, ensuring the generated pillar plan and interactive cluster map align with your predefined content architecture goals.

Does this topic clustering approach work with DataForSEO?▼

Yes, the clustering workflow is designed for compatibility with SEO tooling like DataForSEO. It processes SERP data to generate topic clusters and outputs a machine-readable cluster plan, ensuring seamless integration with your existing search data pipelines and execution tools.

What do I need to start generating an interactive cluster map?▼

To start generating an interactive cluster map, you only need to provide a seed keyword or URL. The system validates the input, clusters the keywords by SERP overlap into a pillar plan, and produces the visual map alongside a machine-readable file for downstream tooling.