What problem does it solve? Choosing which Amazon-affiliate cat product niches and keywords to target is guesswork without access to paid SEO tools like Ahrefs or Amazon APIs. This Skill provides a structured scoring framework that ranks niches and keywords by expected affiliate commission per 1,000 visitors using LLM-estimated proxies for demand, difficulty, and commission rates. ## Core Features & Use Cases - Category Scoring: Scores candidate cat product niches on five weighted axes (RevenuePotential, DemandClarity, CompetitionPressure, ContentMoat, OpsFriction) to produce a CategoryROI_score with deterministic tie-breaking and exclusion-list handling. - Keyword Ranking: Computes a CommissionOpportunityScore from volume, difficulty, price band, and commission rate proxies to sort buyer-intent keywords like "best X for Y" and "X vs Y". - Worker Prompt Alignment: Keeps scouting and keyword-generation prompts in sync with pipeline code (scout.ts, keywords.ts), including slug uniqueness and affiliate-jargon constraints. - Use Case: When deciding whether "cat GPS trackers" or "cat water fountains" is the better niche for catsluvus.com, apply the scoring rubric to compare commission ceilings, SERP openness, and content moat before committing content resources. ## Quick Start Ask the agent to scout and rank the best Amazon-affiliate cat product niche and generate a buyer-intent keyword list for it.
