foundation-models
Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.
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Use when implementing on-device AI with Apple's Foundation Models framework (iOS 26+), building summarization/extraction/classification features, or using @Generable for type-safe structured output.
Use when building features with TCA (The Composable Architecture), structuring reducers, managing state, handling effects, navigation, or testing TCA features. Covers @Reducer, Store, Effect, TestStore, reducer...
Use when writing raw SQL with GRDB, complex joins across 4+ tables, window functions, ValueObservation for reactive queries, or dropping down from SQLiteData for performance. Direct SQLite access for iOS/macOS...
Use when implementing Network.framework connections (NWConnection, NetworkConnection), debugging connection failures, migrating from sockets/URLSession streams, or handling network transitions. Covers UDP/TCP p...
Use when working with SQLiteData library (@Table, @FetchAll, @FetchOne macros) for SQLite persistence, queries, writes, migrations, or CloudKit private database sync.
Use when writing async/await code, enabling strict concurrency, fixing Sendable errors, migrating from completion handlers, managing shared state with actors, or using Task/TaskGroup for concurrency.
Use when implementing iOS 17+ SwiftUI patterns: @Observable/@Bindable, MVVM architecture, NavigationStack, lazy loading, UIKit interop, accessibility (VoiceOver/Dynamic Type), async operations (.task/.refreshab...
Design and document statistical algorithms with pseudocode and complexity analysis
Core mathematical concepts and theoretical frameworks for statistics
Numerical algorithms and computational techniques for statistics
Meta-analysis frameworks and methods for mediation studies
Computational methods for statistical inference and optimization
Design and implementation of comprehensive simulation studies
Six-phase protocol for adapting methods across research domains
Field connection mapping and systematic ideation for method transfer
Strategic publication planning and venue selection for research
M-estimation, influence functions, and semiparametric efficiency theory for causal inference
Sensitivity analysis frameworks and assumption-testing methods
Quality assurance and testing protocols for statistical software
Structured methodology for constructing and verifying mathematical proofs in statistical research
Effective communication strategies for statistical methods
Method×Setting matrices and systematic gap identification
JASA/Biometrika manuscript structure with VanderWeele notation standards
DAG and potential outcomes frameworks for causal mediation identification
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