SEO Team: the Researcher

Most keyword research ends with a CSV of 500 keywords sorted by volume, which then sits in a Google Drive folder until someone feels guilty enough to open it. This skill does the part that actually matters: it turns that raw list into a clustered, scored, prioritized map that tells you which page to create first, which existing page to optimize, and which keyword isn't worth your time despite looking impressive on paper.

The pipeline is six stages: seed keywords from your topic, domain, or competitors; expand with related terms and long-tail variants; enrich with volume, difficulty, intent, and trend data; cluster into content groups using SERP similarity (so you don't accidentally write three articles competing for the same search); prioritize with an opportunity score that accounts for your domain authority; and map to a final output that tells the Writer, Doctor, and General exactly what to do next.

It's also obsessively cost-aware. It checks for existing research before making API calls, batches aggressively (700 keywords per volume call, 1,000 per difficulty call), reuses SERP data across stages, and asks before running expensive operations. The result is a keyword map that a human strategist would spend a week building, produced in minutes without blowing your API budget.