TanStack AI Skills

> Builds on the ai-core skill in @tanstack/ai. Package: @tanstack/ai-skills.

Portable Agent Skills give a tool-calling model a library of SKILL.md skills it can load on demand, on any provider, with no server sandbox. This is separate from hosted Provider Skills (codeExecutionTool / shellTool), which run in the provider's sandbox and are referenced by ID.

Two skill features, do not confuse them

| Need | Use | | ----------------------------------------------- | ------------------------------------- | | Model loads SKILL.md at runtime, any provider | withSkills (this package) | | Hosted skill runs in a provider sandbox by ID | codeExecutionTool / shellTool | | Teach a coding assistant how to use TanStack AI | Ship a SKILL.md, install via Intent |

The portable and hosted paths do not mix in one chat() call: withSkills throws if a code_execution/shell tool in the same call carries skills.

Add skills to a chat

typescript
import { chat, toServerSentEventsResponse } from '@tanstack/ai'
import { anthropicText } from '@tanstack/ai-anthropic'
import { inlineSkill, withSkills } from '@tanstack/ai-skills'

const pptx = inlineSkill({
  name: 'pptx-builder',
  description: 'Build and edit PowerPoint decks with python-pptx.',
  instructions: '# Building a deck\nUse python-pptx. Edit slides, then save.',
})

export async function POST(request: Request) {
  const { messages } = await request.json()

  const stream = chat({
    adapter: anthropicText('claude-sonnet-4-6'),
    messages,
    middleware: [withSkills(pptx)],
  })

  return toServerSentEventsResponse(stream)
}

withSkills adds a catalog to the system prompt and a load_skill tool whose name is constrained to your skill names. It renders <available_skills> XML for Anthropic models and markdown for the rest. Re-loading a skill in the same conversation returns a short "already loaded" marker.

Sources

A SkillSource is bytes only (no filesystem assumption), so the middleware runs on the edge too.

• inlineSkill({ name, description, instructions, resources? }) — one skill in

code or a DB row. Edge-safe.

• skillDirectory(root, { strict? }) — walk a folder for SKILL.md. Import from

@tanstack/ai-skills/node (uses node:fs). Strict by default.

• staticSkills(catalog) — build-time bundle via skillsCatalogPlugin (Vite).

Edge-safe, and .names is a typed union.

Combine with aggregate, dedupe, filter, cache. withSkills([a, b]) is sugar for dedupe(aggregate([a, b])). A single source is never auto-wrapped, so a tenant-scoped source is never cached into a shared bucket.

Resources

To let the model read a skill's bundled files, pass createResourceTool(source) in tools. withSkills detects it and advertises read_skill_resource. Paths that escape the skill root are rejected.

Skills that carry code

withSkills inventories a skill's scripts/ in the load_skill result but does NOT run them (script execution is a later phase). To let a skill run code, pass your own execution tool to chat({ tools }) alongside withSkills and write the skill so it tells the model to call that tool. withSkills composes with any tools you provide.

ts
import { toolDefinition } from '@tanstack/ai'
import { z } from 'zod'
// Your own runner: a provider sandbox, a Code Mode isolate, a remote worker.
import { runSomewhere } from './shell'

const executeShell = toolDefinition({
  name: 'execute_shell',
  description: 'Run a shell command and return its stdout.',
  inputSchema: z.object({ command: z.string() }),
  outputSchema: z.object({ stdout: z.string() }),
}).server(async ({ command }) => ({ stdout: await runSomewhere(command) }))

// chat({ tools: [executeShell], middleware: [withSkills(source)] })

The skill supplies the command; your tool supplies the ability to run it. Swap in a provider sandbox, a Code Mode isolate, or a remote worker without changing the skill. For hosted skills that run in the provider's own sandbox, use codeExecutionTool / shellTool instead (see provider-skills).

Write a custom source

Implement SkillSource (list + load, optional revision/listResources/ readResource), then validate it with the shipped conformance suite:

typescript
import { runSkillSourceConformance } from '@tanstack/ai-skills/testing'
// Your SkillSource implementation, seeded with the `alpha` / `beta` fixture
// skills the suite expects.
import { myS3Source } from './my-s3-source'
import { fixtures } from './fixtures'

runSkillSourceConformance(() => myS3Source(fixtures), 's3')

Entry points

• @tanstack/ai-skills — types, inlineSkill, combinators, withSkills,

createResourceTool, validateSkill, staticSkills, SkillLimitError.

• @tanstack/ai-skills/node — skillDirectory, skillsCatalogPlugin (node:fs).
• @tanstack/ai-skills/testing — runSkillSourceConformance.

Docs

• Portable Agent Skills: docs/skills/agent-skills.md
• Skill sources: docs/skills/skill-sources.md
• Write a skill source: docs/skills/writing-adapters.md
• Provider (hosted) skills: docs/tools/provider-skills.md