data-fetching

Optimistic updates provide immediate UI feedback by updating the local cache before server confirmation during data mutations. This Skill implements these patterns using TanStack Query to ensure smooth user experiences without full page reloads.

The best way to structure data fetching logic is by centralizing it in dedicated queries and hooks directories. This Skill uses a hook-based architecture with TanStack Query to manage asynchronous operations and reduce boilerplate.

Query invalidation synchronizes asynchronous data by marking cached queries as stale and triggering automatic refetching. This Skill leverages query keys and invalidation strategies within TanStack Query to ensure efficient UI responsiveness.

Yes, you can dynamically adjust data fetching intervals through conditional polling. This Skill implements conditional polling to automatically refetch related data based on changing application state using React hooks.

TanStack Query works seamlessly with a hook-based architecture to manage React state and asynchronous data operations. This Skill implements structured hooks to handle queries, mutations, and data synchronization efficiently.

You should use TanStack Query over standard hooks to reduce boilerplate code and improve performance. It provides built-in caching, structured query management, and automated invalidation strategies for complex data fetching operations.