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Ai Skills

OrganizationPopular
TanStack
ai-skills

Portable Agent Skills (SKILL.md) for TanStack AI with @tanstack/ai-skills. Renders a skill catalog and a load_skill tool via the withSkills middleware so any tool-calling model loads skills on demand, on any provider. Covers the SkillSource interface, inlineSkill/skillDirectory/staticSkills, the aggregate/ dedupe/filter/cache combinators, read_skill_resource, and the conformance suite. Use for provider-agnostic runtime skills — NOT hosted provider skills (codeExecutionTool/shellTool), which run in a provider sandbox.

Overview

PublisherTanStack
Repositoryai
Skill nameai-skills
Stars
3.1K
Forks
330
Bundled files
Instructions only
LicenseMIT
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 TanStack on GitHub. Read the source before you install it.

Installation

Install the Ai Skills 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.
  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/TanStack/ai.git /tmp/ai
mkdir -p .claude/skills
cp -r /tmp/ai/packages/ai-skills/skills/ai-skills .claude/skills/ai-skills
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ai Skills 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 Ai Skills 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 Ai Skills 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 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

NeedUse
Model loads SKILL.md at runtime, any providerwithSkills (this package)
Hosted skill runs in a provider sandbox by IDcodeExecutionTool / shellTool
Teach a coding assistant how to use TanStack AIShip 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/nodeskillDirectory, skillsCatalogPlugin (node:fs).
  • @tanstack/ai-skills/testingrunSkillSourceConformance.

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

Frequently asked questions

What does the Ai Skills AI skill do?

Portable Agent Skills (SKILL.md) for TanStack AI with @tanstack/ai-skills. Renders a skill catalog and a load_skill tool via the withSkills middleware so any tool-calling model loads skills on demand, on any provider. Covers the SkillSource interface, inlineSkill/skillDirectory/staticSkills, the aggregate/ dedupe/filter/cache combinators, read_skill_resource, and the conformance suite. Use for provider-agnostic runtime skills — NOT hosted provider skills (codeExecutionTool/shellTool), which run in a provider sandbox.

Why use Ai Skills on TypingMind?

Because you install it once and use it with any model. Ai Skills 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 Ai Skills in TypingMind?

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

Which AI models can use Ai Skills?

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 Ai Skills?

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

Is the Ai Skills AI skill free?

Yes. It is published on GitHub by TanStack under the MIT 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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