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Getting Started

Agent Skills (TanStack Intent)

You're building with TanStack AI and using an AI coding agent — Claude Code, Cursor, GitHub Copilot, or similar. The agent keeps suggesting Vercel-AI-SDK patterns like streamText() or createOpenAI(), or it wires streams manually instead of using toServerSentEventsResponse(). By the end of this guide, your agent will load TanStack AI's bundled skills automatically whenever you work on AI code — and those skills will stay in sync with whichever @tanstack/ai version your project installs.

Looking for runtime skills inside Code Mode? Those are a different feature — see Code Mode with Skills. This page is about agent-authoring skills: markdown files that teach your coding assistant how TanStack AI works.

What are Agent Skills?

Agent Skills are markdown documents (SKILL.md) that ship inside npm packages and tell AI coding agents how to use a library correctly — which functions to use, which patterns to avoid, and when to reach for which module. The format is an open standard supported by Claude Code, Cursor, GitHub Copilot, Codex, and others.

TanStack AI publishes skills inside its packages so the guidance travels with npm update instead of being pinned in a model's training data or copy-pasted into CLAUDE.md manually.

Skills Shipped by TanStack AI

PackageSkillWhat it teaches
@tanstack/aiai-coreChat experience, tool calling, adapters, middleware, structured outputs, media generation, AG-UI protocol, custom backends
@tanstack/ai-code-modeai-code-modeSetting up Code Mode with a sandbox driver and registering server tools

Each skill lives under node_modules/<package>/skills/<skill-name>/SKILL.md once the package is installed.

Step 1: Install TanStack AI

If you haven't already, install @tanstack/ai plus any adapter packages you need. See the Quick Start for a full walkthrough.

sh
pnpm add @tanstack/ai @tanstack/ai-openai
pnpm add @tanstack/ai @tanstack/ai-openai

Step 2: Run intent install

From the root of your project, run:

sh
npx @tanstack/intent@latest install
npx @tanstack/intent@latest install

The CLI walks your agent through the setup. It scans node_modules for every package that ships skills (any package with the tanstack-intent keyword), asks your agent to propose task-to-skill mappings that match your codebase, and writes them into your agent's config file.

By default the mappings land in AGENTS.md. The CLI can also target:

  • CLAUDE.md — Claude Code
  • .cursorrules — Cursor
  • any other agent config file you point it at

Step 3: Review the Generated Mappings

The install command appends (or creates) an intent-skills block that looks like this:

yaml
<!-- intent-skills:start -->
# Skill mappings — when working in these areas, load the linked skill file into context.
skills:
  - task: "Building chat, tool calling, adapters, or streaming with TanStack AI"
    load: "node_modules/@tanstack/ai/skills/ai-core/SKILL.md"
  - task: "Setting up Code Mode with TanStack AI"
    load: "node_modules/@tanstack/ai-code-mode/skills/ai-code-mode/SKILL.md"
<!-- intent-skills:end -->
<!-- intent-skills:start -->
# Skill mappings — when working in these areas, load the linked skill file into context.
skills:
  - task: "Building chat, tool calling, adapters, or streaming with TanStack AI"
    load: "node_modules/@tanstack/ai/skills/ai-core/SKILL.md"
  - task: "Setting up Code Mode with TanStack AI"
    load: "node_modules/@tanstack/ai-code-mode/skills/ai-code-mode/SKILL.md"
<!-- intent-skills:end -->

Check that the task: descriptions match areas you actually work in. Tighten or reword them if needed — they're how your agent decides when to pull the skill into context.

Step 4: Confirm It's Wired Up

Open a fresh session in your coding agent and ask it to build something with TanStack AI — for example: "Add a streaming chat endpoint using @tanstack/ai and the OpenAI adapter."

You should see:

  • The agent uses chat(), not streamText().
  • The adapter is imported as openaiText() from @tanstack/ai-openai, not createOpenAI().
  • The response is wrapped with toServerSentEventsResponse() instead of manual SSE wiring.
  • Middleware is used for lifecycle events (no onFinish callback on chat()).

If the agent still falls back to other-SDK patterns, re-open its config file and confirm the intent-skills block is present and the task: descriptions clearly cover the area you're asking about.

Keeping Skills Current

Skills are versioned with the package. When you bump @tanstack/ai, the SKILL.md files under node_modules update with it — no CLI re-run needed. Re-run npx @tanstack/intent@latest install only when you add a new intent-enabled package (for example, adding @tanstack/ai-code-mode later) or want to refresh the task mappings.

Using Skills Without the CLI

If you'd rather wire skills in yourself, you can reference them directly from node_modules in any agent config file. The minimum your agent needs is a pointer to the file:

markdown
When working on TanStack AI code, read and follow:
node_modules/@tanstack/ai/skills/ai-core/SKILL.md
When working on TanStack AI code, read and follow:
node_modules/@tanstack/ai/skills/ai-core/SKILL.md

The CLI is recommended because it discovers packages automatically and stays consistent with the agent-skills standard, but the underlying file paths are stable.

Learn More