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Tanstack Query

OrganizationPopular
exceptionless
tanstack-query

Manage Svelte API queries, mutations, cache updates, and WebSocket invalidation.

Overview

Publisherexceptionless
RepositoryExceptionless
Skill nametanstack-query
Stars
2.5K
Forks
508
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by exceptionless on GitHub. Read the source before you install it.

Installation

Install the Tanstack Query AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/exceptionless/Exceptionless/tree/main/.agents/skills/tanstack-query
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/exceptionless/Exceptionless.git /tmp/Exceptionless
mkdir -p .claude/skills
cp -r /tmp/Exceptionless/.agents/skills/tanstack-query .claude/skills/tanstack-query
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tanstack Query in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tanstack Query on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tanstack Query is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

TanStack Query

Centralize API calls in each feature's api.svelte.ts, using @tanstack/svelte-query and @exceptionless/fetchclient.

Use the current organization and webhook implementations under src/Exceptionless.Web/ClientApp/src/lib/features/ as examples. Preserve their response/error types and signal handling.

  • Share a feature's queryKeys factory across queries, mutations, and invalidation.
  • Name operations get{Resource}Query, post{Resource}Mutation, patch{Resource}Mutation, and delete{Resource}Mutation.
  • Gate queries on required authentication or identifiers.
  • Pass the query cancellation signal through the fetch client.
  • For optimistic updates, cancel competing queries, snapshot the cache, restore on failure, and reconcile with server state after completion.
  • Wire WebSocket changes through the feature's invalidation helper. Match invalidation scope to the message identifiers.

Verify failure recovery and relevant cache interactions, not just the successful response.

Mutation and cache lifecycle

Keep reactive query options in the factory passed to createQuery or createMutation, following the current feature implementation. Include identifiers and relevant query parameters in its key factory so distinct results do not share a cache entry.

For an optimistic mutation, onMutate cancels affected in-flight queries and saves the previous value before updating the cache. onError uses that context to roll back; completion reconciles affected queries with server state, commonly through onSettled. Preserve unrelated cache entries and consider overlapping mutations before restoring an older snapshot.

Await invalidation or refetching when the calling UI depends on it before closing or navigating. Match the existing feature's FetchClientResponse and ProblemDetails handling instead of assuming every request throws or every mutation returns an unwrapped model.

WebSocket invalidation must use the same key factories as queries. Inspect both the feature helper and its caller when changing message handling; verify identifier-specific and collection updates.

Frequently asked questions

What does the Tanstack Query AI skill do?

Manage Svelte API queries, mutations, cache updates, and WebSocket invalidation.

Why use Tanstack Query on TypingMind?

Because you install it once and use it with any model. Tanstack Query is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tanstack Query in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/exceptionless/Exceptionless/tree/main/.agents/skills/tanstack-query. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tanstack Query?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tanstack Query?

As many as you like. As long as a model supports skills, you can use Tanstack Query with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tanstack Query AI skill free?

Yes. It is published on GitHub by exceptionless under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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