What problem does it solve? Marketing and content teams struggle to run consistent, high-quality SEO and AI-search (GEO) workflows inside AI coding agents, often lacking structured processes for keyword research, content quality checks, and rank monitoring. ## Core Features & Use Cases - 20 Specialized Skills Across Five Phases: Research (keyword research, competitor analysis, SERP analysis, content gap analysis), Build (SEO content writer, GEO optimizer, meta tags, schema markup), Optimize (on-page audits, technical SEO, internal linking, content refresh), Monitor (rank tracking, backlink analysis, reporting, alerts), and cross-cutting protocol skills. - Built-in Quality Frameworks: CORE-EEAT (80-item content quality benchmark) and CITE (40-item domain authority benchmark) gate content before publication. - Tiered Memory System: HOT/WARM/COLD memory tiers with a wiki layer for compiling and querying project knowledge across sessions. - Use Case: A content marketer runs /aaron:discover to research keywords for a SaaS topic, generates a brief and article with /aaron:write, validates it against the CORE-EEAT checklist with /aaron:publish, then tracks rankings weekly with /aaron:watch. ## Quick Start Ask the agent to research keywords for your product topic and generate an SEO-optimized article brief using the auto-routing command.
