What problem does it solve? Firestore applications often hit scaling walls: bloated documents, runaway read costs, slow security rules, and race conditions in checkout flows. This Skill provides concrete patterns for NoSQL data modeling, indexing, security rules, and backend efficiency so your Firebase architecture holds up under growth. ## Core Features & Use Cases - Data Modeling Guidance: Decide between subcollections and arrays based on growth patterns, respecting the 1MB document limit and read-cost tradeoffs. - Security Rules Optimization: Write low-latency rules using custom claims, minimal get()/exists() calls, and strict field type and size validation. - Adversarial Backend Design: Prevent price tampering with server-side re-fetching and eliminate race conditions with transactional inventory updates. - Use Case: When designing a marketplace checkout flow, apply this Skill to model orders as subcollections, enforce idempotent Cloud Functions, and validate prices server-side before payment capture. ## Quick Start Review my Firestore schema and security rules for scalability issues and suggest improvements for indexes, subcollections, and server-side validation.
