What problem does it solve? Keyword lists built on text similarity often produce overlapping pages that cannibalize each other in search results. This Skill clusters keywords by actual Google SERP overlap, so each page targets a distinct ranking opportunity and the whole set forms a coherent content architecture. ## Core Features & Use Cases - SERP-Overlap Clustering: Expands a seed keyword into 30-50 variants, then groups them by shared top-10 Google results rather than text similarity, with intent classification and cannibalization checks. - Hub-and-Spoke Architecture: Designs a pillar page plus 2-5 spoke clusters with template selection, word count targets, and a bidirectional internal link matrix exported as JSON. - Interactive Visualization & Execution: Generates an interactive cluster-map.html, produces content briefs, or executes the plan through the claude-blog skill with resume support and a quality scorecard. - Use Case: A content marketer enters a seed keyword like "crm software" and receives a full cluster plan: one pillar guide, several spoke posts with assigned templates and keywords, an internal linking matrix, and a visual map to share with stakeholders. ## Quick Start Ask the AI to run a topic cluster plan for your seed keyword, for example: create a content cluster plan for "email marketing automation".
