What problem does it solve? Researching competitors manually means visiting dozens of pages, copying pricing tables, and guessing at their SEO strength. This Skill automates that research by combining live site scraping with quantitative SEO and backlink data, producing consistent, comparable competitor profile documents. ## Core Features & Use Cases - Three-phase research pipeline: Maps and scrapes competitor sites with Firecrawl (homepage, pricing, features, customers, integrations, changelog), pulls SEO and backlink metrics with DataForSEO, then synthesizes everything into a standardized profile template. - Raw data persistence: Saves every scrape, SEO response, and review source to dated folders under competitor-profiles/raw/ so snapshots can be audited, diffed, and re-used without re-running API calls. - Quick scan vs. deep profile modes: Defaults to a fast homepage-plus-pricing scan for large competitor lists, with full deep profiles (reviews, tech stack, keyword intelligence) for three or fewer competitors. - Cross-competitor summary: Builds a _summary.md with a side-by-side comparison table, positioning map, key takeaways, and market gaps after all profiles complete. - Use Case: Given five competitor URLs before a positioning workshop, produce one profile per competitor covering pricing, messaging, SEO strength, and review sentiment, plus a summary comparing all five against your product. ## Quick Start Profile these competitors: https://competitor-a.com and https://competitor-b.com, using a quick scan focused on pricing and positioning.
