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Found 25 Skills
Writes and audits data loading in a TanStack Start and TanStack Query app, removing request waterfalls and wasted requests from route loaders, suspense queries, mutations and server functions. Use when writing or reviewing a loader, useSuspenseQuery, useMutation or createServerFn, when a TanStack route loads slowly, fetches the same data twice or a save stays pending, or when the user says "audit data loading", "find waterfalls". Not for bundle size, HTTP caching, or apps without TanStack Query.
Route loader option, loaderDeps for cache keys, staleTime/gcTime/ defaultPreloadStaleTime SWR caching, pendingComponent/pendingMs/ pendingMinMs, errorComponent/onError/onCatch, beforeLoad, router context and createRootRouteWithContext DI pattern, router.invalidate, Await component, deferred data loading with unawaited promises.
Debug distributed training failures (NeMo, Megatron, PyTorch) from worker stderr logs and optional AIStore daemon logs. Finds root cause across NCCL timeouts, data loading errors, and storage failures.
TanStack Router best practices for type-safe routing, file-based routing, data loading, search params, and navigation in React. Use when building React SPAs with complex routing, implementing type-safe search params, setting up route loaders, integrating with TanStack Query, or configuring code splitting and preloading.
Reviews React Router code for proper data loading, mutations, error handling, and navigation patterns. Use when reviewing React Router v6.4+ code, loaders, actions, or navigation logic.
Load automatically when planning, researching, or implementing Medusa Admin dashboard UI (widgets, custom pages, forms, tables, data loading, navigation). REQUIRED for all admin UI work in ALL modes (planning, implementation, exploration). Contains design patterns, component usage, and data loading patterns that MCP servers don't provide.
ALWAYS use when working with Angular Resource, Angular 19 resource API, or new async data loading with signals.
Type-safe, file-based router for React with first-class search params, data loading, and code splitting. Use when user asks to "create routes with TanStack Router", "set up file-based routing", "add search params", "use loaders", "protect routes with auth", "add code splitting", or asks about @tanstack/react-router, createFileRoute, createRouter, routeTree.gen.ts, useSearch, useParams, useNavigate, useBlocker, useMatch, useRouterState, beforeLoad, or route configuration. Do NOT use for TanStack Start server functions, Next.js App Router, React Router (without migration context), or Remix routing. Covers routing setup, navigation, search/path params, data loading, authentication, code splitting, SSR, error handling, testing, deployment, and bundler configuration (Vite, Webpack, Rspack, esbuild).
TanStack Router best practices for type-safe routing, data loading, search params, and navigation. Activate when building React applications with complex routing needs.
Apply React Router 7 framework mode best practices including server-first data fetching, type-safe loaders/actions, proper hydration strategies, middleware authentication, handle metadata, useMatches/useRouteLoaderData hooks, and maximum type safety. Use when working with React Router 7 framework mode, implementing loaders, actions, route protection, breadcrumbs, streaming with Suspense/Await, URL search params, form validation, optimistic UI, resource routes (API endpoints), route configuration, or building SSR applications.
Implement HTTP data fetching in Angular v20+ using resource(), httpResource(), and HttpClient. Use for API calls, data loading with signals, request/response handling, and interceptors. Triggers on data fetching, API integration, loading states, error handling, or converting Observable-based HTTP to signal-based patterns.
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call loader fits, including when per-shard row counts differ across files. Prefer cupynumeric.load or legate.io.hdf5.from_file when they apply.