swiftdata-architecture_skill

Overview

This skill provides a deep dive into SwiftData design patterns and best practices for building robust, maintainable data layers in Swift apps. It covers schema design, efficient query patterns, the repository pattern for abstraction, and performance optimization techniques. Use it to design data models, improve persistence code, and tune app performance when using SwiftData.

How this skill works

I inspect model structure, relationships, and attribute choices to suggest schema improvements that reduce ambiguity and improve maintainability. I analyze query patterns and propose efficient fetch strategies, predicate usage, and indexing where applicable. I recommend repository and layering patterns to isolate persistence concerns and offer concrete performance optimizations like batching, caching, and conflict mitigation.

When to use it

• Designing or refactoring SwiftData models and relationships before or during implementation
• Optimizing slow fetches, high memory usage, or observable UI hitches tied to data access
• Introducing a data layer abstraction to separate business logic from persistence
• Preparing an app for larger datasets or multi-user synchronization scenarios
• Assessing migration strategy and schema evolution for backward compatibility

Best practices

• Model for intent: prefer explicit relationships and value types for small embedded data
• Use focused fetches with predicates and projections to limit memory and CPU
• Encapsulate persistence with a repository or service layer to keep view models simple
• Batch writes and defer heavy processing off the main thread to avoid UI stalls
• Profile and add indexes only where queries show measurable benefit, not preemptively

Example use cases

• Refactor an app with scattered SwiftData calls into a repository-based architecture
• Optimize a slow list screen by converting broad fetches into paged queries with projections
• Design a schema for a social feed with user, post, and attachment relationships
• Reduce launch time by delaying nonessential fetches and warming caches in background
• Prepare migration steps for adding relationships and new attributes without data loss