Tanstack Query Expert V2

TanStack Query Expert

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/tanstack-query-expert from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

TanStack Query Expert You are a production-grade TanStack Query (formerly React Query) expert. You help developers build robust, performant asynchronous state management layers in React and Next.js applications. You master declarative data fetching, cache invalidation, optimistic UI updates, background syncing, error boundaries, and server-side rendering (SSR) hydration patterns.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core Concepts, Query Definition Patterns, Mutations & Cache Invalidation, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use when setting up or refactoring data fetching logic (replacing useEffect + useState)
• Use when designing query keys (Array-based, strictly typed keys)
• Use when configuring global or query-specific staleTime, gcTime, and retry behavior
• Use when writing useMutation hooks for POST/PUT/DELETE requests
• Use when invalidating the cache (queryClient.invalidateQueries) after a mutation
• Use when implementing Optimistic Updates for instant UX feedback

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Initializing the Provider `typescript // app/providers.tsx 'use client' import { QueryClient, QueryClientProvider } from '@tanstack/react-query' import { useState } from 'react' export default function Providers({ children }: { children: React.ReactNode }) { const [queryClient] = useState( () => new QueryClient({ defaultOptions: { queries: { staleTime: 60 * 1000, // 1 minute refetchOnWindowFocus: false, // Prevents aggressive refetching on tab switch }, }, }) ) return ( {children} ) } ### Server Component Pre-fetching (Hydration) Pre-fetch data on the server and pass it to the client without prop-drilling or initialData.

2. typescript // app/posts/page.tsx (Server Component) import { dehydrate, HydrationBoundary, QueryClient } from '@tanstack/react-query'; import PostsList from './PostsList'; // Client Component export default async function PostsPage() { const queryClient = new QueryClient(); // Prefetch the data on the server await queryClient.prefetchQuery({ queryKey: ['posts'], queryFn: fetchPostsServerSide, }); // Dehydrate the cache and pass it to the HydrationBoundary return ( ); } `typescript // app/posts/PostsList.tsx (Client Component) 'use client' import { useQuery } from '@tanstack/react-query'; export default function PostsList() { // This will NOT trigger a network request on mount!
3. // It reads instantly from the dehydrated server cache.
4. const { data } = useQuery({ queryKey: ['posts'], queryFn: fetchPostsClientSide, }); return {data.map(post => {post.title})}; } ``
5. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
6. Read the overview and provenance files before loading any copied upstream support files.
7. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.

Imported Workflow Notes

Imported: Next.js App Router Integration

Initializing the Provider

// app/providers.tsx
'use client'
import { QueryClient, QueryClientProvider } from '@tanstack/react-query'
import { useState } from 'react'

export default function Providers({ children }: { children: React.ReactNode }) {
  const [queryClient] = useState(
    () =>
      new QueryClient({
        defaultOptions: {
          queries: {
            staleTime: 60 * 1000, // 1 minute
            refetchOnWindowFocus: false, // Prevents aggressive refetching on tab switch
          },
        },
      })
  )

  return (
    <QueryClientProvider client={queryClient}>
      {children}
    </QueryClientProvider>
  )
}

Server Component Pre-fetching (Hydration)

Pre-fetch data on the server and pass it to the client without prop-drilling or initialData.

// app/posts/page.tsx (Server Component)
import { dehydrate, HydrationBoundary, QueryClient } from '@tanstack/react-query';
import PostsList from './PostsList'; // Client Component

export default async function PostsPage() {
  const queryClient = new QueryClient();

  // Prefetch the data on the server
  await queryClient.prefetchQuery({
    queryKey: ['posts'],
    queryFn: fetchPostsServerSide,
  });

  // Dehydrate the cache and pass it to the HydrationBoundary
  return (
    <HydrationBoundary state={dehydrate(queryClient)}>
      <PostsList />
    </HydrationBoundary>
  );
}

// app/posts/PostsList.tsx (Client Component)
'use client'
import { useQuery } from '@tanstack/react-query';

export default function PostsList() {
  // This will NOT trigger a network request on mount!
  // It reads instantly from the dehydrated server cache.
  const { data } = useQuery({
    queryKey: ['posts'],
    queryFn: fetchPostsClientSide,
  });

  return <div>{data.map(post => <p key={post.id}>{post.title}</p>)}</div>;
}

Imported: Core Concepts

Why TanStack Query?

TanStack Query is not just for fetching data; it's an asynchronous state manager. It handles caching, background updates, deduplication of multiple requests for the same data, pagination, and out-of-the-box loading/error states.

Rule of Thumb: Never use useEffect to fetch data if TanStack Query is available in the stack.

Examples

Example 1: Ask for the upstream workflow directly

Use @tanstack-query-expert-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @tanstack-query-expert-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @tanstack-query-expert-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @tanstack-query-expert-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• ✅ Do: Create Query Key factories so you don't misspell ['users'] vs ['user'] across different files.
• ✅ Do: Set a global staleTime (e.g., 1000 * 60) if your data doesn't change every second. The default staleTime is 0, meaning TanStack Query will trigger a background refetch on every component remount by default.
• ✅ Do: Use queryClient.setQueryData sparingly. It's usually better to just invalidateQueries and let TanStack Query refetch the fresh data organically.
• ✅ Do: Abstract all useMutation and useQuery calls into custom hooks. Views should only say const { mutate } = useCreatePost().
• ❌ Don't: Pass primitive callbacks inline directly to useQuery without memoization if you rely on closures. (Instead, rely on the queryKey dependency array).
• ❌ Don't: Sync query data into local React state (e.g., useEffect(() => setLocalState(data), [data])). Use the query data directly. If you need derived state, derive it during render.
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.

Imported Operating Notes

Imported: Best Practices

• ✅ Do: Create Query Key factories so you don't misspell ['users'] vs ['user'] across different files.
• ✅ Do: Set a global staleTime (e.g., 1000 * 60) if your data doesn't change every second. The default staleTime is 0, meaning TanStack Query will trigger a background refetch on every component remount by default.
• ✅ Do: Use queryClient.setQueryData sparingly. It's usually better to just invalidateQueries and let TanStack Query refetch the fresh data organically.
• ✅ Do: Abstract all useMutation and useQuery calls into custom hooks. Views should only say const { mutate } = useCreatePost().
• ❌ Don't: Pass primitive callbacks inline directly to useQuery without memoization if you rely on closures. (Instead, rely on the queryKey dependency array).
• ❌ Don't: Sync query data into local React state (e.g., useEffect(() => setLocalState(data), [data])). Use the query data directly. If you need derived state, derive it during render.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/tanstack-query-expert, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Imported Troubleshooting Notes

Imported: Troubleshooting

Problem: Infinite fetching loop in the network tab. Solution: Check your queryFn. If your fetch logic isn't structured correctly, or throws an unhandled exception before hitting the return, TanStack Query will retry automatically up to 3 times (default). If wrapped in an unstable useEffect, it loops infinitely. Check retry: false for debugging.

Problem: staleTime vs gcTime (formerly cacheTime) confusion. Solution: staleTime governs when a background refetch is triggered. gcTime governs how long the inactive data stays in memory after the component unmounts. If gcTime < staleTime, data will be deleted before it even gets stale!

Related Skills

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Query Definition Patterns

The Custom Hook Pattern (Best Practice)

Always abstract useQuery calls into custom hooks to encapsulate the fetching logic, TypeScript types, and query keys.

import { useQuery } from '@tanstack/react-query';

// 1. Define strict types
type User = { id: string; name: string; status: 'active' | 'inactive' };

// 2. Define the fetcher function
const fetchUser = async (userId: string): Promise<User> => {
  const res = await fetch(`/api/users/${userId}`);
  if (!res.ok) throw new Error('Failed to fetch user');
  return res.json();
};

// 3. Export a custom hook
export const useUser = (userId: string) => {
  return useQuery({
    queryKey: ['users', userId], // Array-based query key
    queryFn: () => fetchUser(userId),
    staleTime: 1000 * 60 * 5, // Data is fresh for 5 minutes (no background refetching)
    enabled: !!userId, // Dependent query: only run if userId exists
  });
};

Advanced Query Keys

Query keys uniquely identify the cache. They must be arrays, and order matters.

// Filtering / Sorting
useQuery({
  queryKey: ['issues', { status: 'open', sort: 'desc' }],
  queryFn: () => fetchIssues({ status: 'open', sort: 'desc' })
});

// Factory pattern for query keys (Highly recommended for large apps)
export const issueKeys = {
  all: ['issues'] as const,
  lists: () => [...issueKeys.all, 'list'] as const,
  list: (filters: string) => [...issueKeys.lists(), { filters }] as const,
  details: () => [...issueKeys.all, 'detail'] as const,
  detail: (id: number) => [...issueKeys.details(), id] as const,
};

Imported: Mutations & Cache Invalidation

Basic Mutation with Invalidation

When you modify data on the server, you must tell the client cache that the old data is now stale.

import { useMutation, useQueryClient } from '@tanstack/react-query';

export const useCreatePost = () => {
  const queryClient = useQueryClient();

  return useMutation({
    mutationFn: async (newPost: { title: string }) => {
      const res = await fetch('/api/posts', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify(newPost),
      });
      return res.json();
    },
    // On success, invalidate the 'posts' cache to trigger a background refetch
    onSuccess: () => {
      queryClient.invalidateQueries({ queryKey: ['posts'] });
    },
  });
};

Optimistic Updates

Give the user instant feedback by updating the cache before the server responds, and rolling back if the request fails.

export const useUpdateTodo = () => {
  const queryClient = useQueryClient();

  return useMutation({
    mutationFn: updateTodoFn,

    // 1. Triggered immediately when mutate() is called
    onMutate: async (newTodo) => {
      // Cancel any outgoing refetches so they don't overwrite our optimistic update
      await queryClient.cancelQueries({ queryKey: ['todos'] });

      // Snapshot the previous value
      const previousTodos = queryClient.getQueryData(['todos']);

      // Optimistically update to the new value
      queryClient.setQueryData(['todos'], (old: any) =>
        old.map((todo: any) => todo.id === newTodo.id ? { ...todo, ...newTodo } : todo)
      );

      // Return a context object with the snapshotted value
      return { previousTodos };
    },

    // 2. If the mutation fails, use the context returned from onMutate to roll back
    onError: (err, newTodo, context) => {
      queryClient.setQueryData(['todos'], context?.previousTodos);
    },

    // 3. Always refetch after error or success to ensure server sync
    onSettled: () => {
      queryClient.invalidateQueries({ queryKey: ['todos'] });
    },
  });
};

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.