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ai-core

TanStack AI is a type-safe, provider-agnostic SDK for building AI applications with server-side functions in core packages and client-side hooks in framework-specific packages. Use this skill to understand core concepts, choose between chat streaming, tool calling, media generation, structured outputs, provider configuration, middleware, and custom backend integration patterns.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/TanStack/ai /tmp/ai-core && cp -r /tmp/ai-core/packages/ai/skills/ai-core ~/.claude/skills/ai-core
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# TanStack AI — Core Concepts

TanStack AI is a type-safe, provider-agnostic AI SDK. Server-side functions
live in `@tanstack/ai` and provider adapter packages. Client-side hooks live
in framework packages (`@tanstack/ai-react`, `@tanstack/ai-solid`, etc.).
Always import from the framework package on the client — never from
`@tanstack/ai-client` directly (unless vanilla JS).

## Sub-Skills

| Need to...                                        | Read                                          |
| ------------------------------------------------- | --------------------------------------------- |
| Build a chat UI with streaming                    | ai-core/chat-experience/SKILL.md              |
| Survive a browser reload (no extra package)       | ai-core/client-persistence/SKILL.md           |
| Add tool calling (server, client, or both)        | ai-core/tool-calling/SKILL.md                 |
| Generate images, video, speech, or transcriptions | ai-core/media-generation/SKILL.md             |
| Get typed JSON responses from the LLM             | ai-core/structured-outputs/SKILL.md           |
| Choose and configure a provider adapter           | ai-core/adapter-configuration/SKILL.md        |
| Implement AG-UI streaming protocol server-side    | ai-core/ag-ui-protocol/SKILL.md               |
| Add analytics, logging, or lifecycle hooks        | ai-core/middleware/SKILL.md                   |
| Coordinate multi-instance work with locks         | ai-core/locks/SKILL.md                        |
| Connect to a non-TanStack-AI backend              | ai-core/custom-backend-integration/SKILL.md   |
| Turn on/off debug logging, pipe into pino/winston | ai-core/debug-logging/SKILL.md                |
| Persist chats server-side (history, runs)         | See `@tanstack/ai-persistence` package skills |
| Set up Code Mode (LLM code execution)             | See `@tanstack/ai-code-mode` package skills   |
| Give the model a catalog of SKILL.md skills       | See `@tanstack/ai-skills` package skills      |

## Companion packages

Some capabilities live in their own package and ship their own skills. Install
the package, then read its skills — do not guess the API from this file.

### `@tanstack/ai-persistence` — durable chat state

Makes a conversation survive a reload, a server restart, a second device, or a
paused tool approval. It ships the **store contracts** (`MessageStore`,
`RunStore`, `InterruptStore`, `MetadataStore`), the `withPersistence` /
`withGenerationPersistence` middleware, `reconstructChat` for server-side
hydrate, an in-memory reference backend, and a conformance testkit. Multi-instance
locks are **not** in this package — `LockStore` / `withLocks` ship in
`@tanstack/ai/locks`; see ai-core/locks. The `runs` store contract is typed
against run lifecycle types (`RunStatus`, `RunRecord`, `RunStore`,
`defineRunStore`, `InMemoryRunStore`), which ship in `@tanstack/ai` itself;
see ai-core/middleware.

It does **not** ship a backend for your database — you implement the stores
against Postgres, SQLite, D1, Mongo, or whatever you run, and the package's
skills walk you through it (including Drizzle, Prisma, and Cloudflare recipes).

```bash
pnpm add @tanstack/ai-persistence
npx @tanstack/intent@latest install
```

The skills ship **inside** the package, so they only exist on disk once it is
installed — the second command re-scans `node_modules` and wires them into the
agent config. Until then the paths below resolve to nothing.

Entry point: `node_modules/@tanstack/ai-persistence/skills/ai-persistence/SKILL.md`

| Need to...                                      | Read                                    |
| ----------------------------------------------- | --------------------------------------- |
| Wire server-side chat history, runs, interrupts | ai-persistence/server/SKILL.md          |
| Implement the store interfaces for your DB      | ai-persistence/stores/SKILL.md          |
| Write the adapter for the DB your app runs      | ai-persistence/build-*-adapter/SKILL.md |

Browser-side persistence is **not** in this package — it ships with the
framework packages, so read **ai-core/client-persistence** instead.

### `@tanstack/ai-code-mode` — LLM code execution

See the `ai-code-mode` skill in that package.

### `@tanstack/ai-skills` — portable Agent Skills at runtime

Gives the model a library of `SKILL.md` skills it can load on demand, on any
provider, via the `withSkills` middleware and a `load_skill` tool. Skills come
from `inlineSkill`, `skillDirectory`, or a build-time bundle. This is the
runtime feature for the model **inside your app**, not the coding-assistant
skills this file is part of, and not the hosted `codeExecutionTool` /
`shellTool` skills (those run in a provider sandbox).

```bash
pnpm add @tanstack/ai-skills
npx @tanstack/intent@latest install
```

Entry point: `node_modules/@tanstack/ai-skills/skills/ai-skills/SKILL.md`

## Quick Decision Tree

- Setting up a chatbot? → ai-core/chat-experience
- Adding function calling? → ai-core/tool-calling
- Generating media (images, audio, video)? → ai-core/media-generation
- Need structured JSON output? → ai-core/structured-outputs
- Choosing/configuring a provider? → ai-core/adapter-configuration
- Building a server-only AG-UI backend? → ai-core/ag-ui-protocol
- Adding analytics or post-stream events? → ai-core/middleware
- Surviving reloads / multi-device / durable approvals? → `@tanstack/ai-persistence` skills
- Connecting to a custom backend? → ai-core/custom-backend-integration
- Turning on debug logging to trace chunks/tools/middleware? → ai-core/debug-logging
- Debugging mistakes? → Check Common Mistakes in the relevant sub-skill

## Critical Rules

1. **This is NOT the Vercel AI SDK.** Use `chat()` not `streamText()`. Use `openaiText()` not `createOpenAI()`. Import from `@tanstack/ai`, not `ai`.
2. **Import from framework package on client.** Use `@tanstack/ai-react` (or solid/vue/svelte/preact), not `@tanstack/ai-client`.
3. *