What problem does it solve? It turns a vague need like "what terms could I rank for on Google" into a structured keyword research deliverable: an audience definition, at least 30 discovered keywords, intent classification, thematic clusters, and a prioritized selection based on real volume and difficulty data. ## Core Features & Use Cases - Audience-first research: Defines the target audience with a 5-axis SEO questionnaire (demographics, interests, online behavior, search intent, pain points) before proposing any keyword. - Four discovery methods: Combines brainstorming, Google Autocomplete, competitor analysis, and AI-generated ideas, with an optional Python script that expands seeds via SerpApi (Autocomplete, Related Searches, People Also Ask). - Selection and execution columns: Classifies intent (informational, commercial, transactional, navigational), groups keywords into clusters, applies the "sweet spot" filter (medium-high volume x low difficulty, long-tail first), and outputs suggested URL, content idea, and H1 per winning keyword. - Use Case: A yoga studio owner in Bogota asks what terms to target; the skill produces a 30+ keyword table clustered by theme, marked with the sweet-spot picks, ready to paste into the Master Template. ## Quick Start Ask the assistant to research keywords for your business niche, country, and language, and it will deliver a classified, clustered keyword table with URLs and H1 suggestions.
