Ag Ui logo

Ag Ui

Organization
TerminalSkills
ag-ui

You are an expert in AG-UI (Agent-User Interaction Protocol), the open standard by CopilotKit for connecting AI agents to frontend UIs. You help developers stream agent actions, tool calls, state updates, and text generation to React components in real-time — enabling rich agent UIs where users see what the agent is thinking, doing, and can intervene at any step.

Overview

PublisherTerminalSkills
Repositoryskills
Skill nameag-ui
Stars
155
Forks
21
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Ag Ui 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/TerminalSkills/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/ag-ui .claude/skills/ag-ui
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ag Ui 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 Ag Ui 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 Ag Ui 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.

AG-UI — Agent-User Interaction Protocol

You are an expert in AG-UI (Agent-User Interaction Protocol), the open standard by CopilotKit for connecting AI agents to frontend UIs. You help developers stream agent actions, tool calls, state updates, and text generation to React components in real-time — enabling rich agent UIs where users see what the agent is thinking, doing, and can intervene at any step.

Core Capabilities

AG-UI Server (Agent Events)

typescript
// server/agent.ts — Stream agent events to UI
import { AgentServer, EventStream } from "@ag-ui/server";

const server = new AgentServer();

server.onRequest(async (request, stream: EventStream) => {
  const { messages, context } = request;

  // Emit thinking state
  stream.emitStateUpdate({ status: "thinking", progress: 0 });

  // Stream text generation
  stream.emitTextStart();
  for (const word of "I'll analyze your data now.".split(" ")) {
    stream.emitTextDelta(word + " ");
    await sleep(50);
  }
  stream.emitTextEnd();

  // Emit tool call
  stream.emitToolCallStart("search_database", { query: context.userQuery });
  const results = await searchDatabase(context.userQuery);
  stream.emitToolCallEnd("search_database", results);
  stream.emitStateUpdate({ status: "analyzing", progress: 50 });

  // Stream analysis
  stream.emitTextStart();
  const analysis = await generateAnalysis(results);
  for await (const chunk of analysis) {
    stream.emitTextDelta(chunk);
  }
  stream.emitTextEnd();

  // Custom state for UI rendering
  stream.emitStateUpdate({
    status: "complete",
    progress: 100,
    charts: [{ type: "bar", data: results.chartData }],
    suggestions: ["Run deeper analysis", "Export to CSV", "Schedule report"],
  });

  stream.end();
});

AG-UI React Client

tsx
import { useAgent, AgentProvider } from "@ag-ui/react";

function App() {
  return (
    <AgentProvider url="https://api.example.com/agent">
      <AgentChat />
    </AgentProvider>
  );
}

function AgentChat() {
  const { messages, state, sendMessage, isStreaming, toolCalls } = useAgent();

  return (
    <div className="flex flex-col h-screen">
      {/* Agent state visualization */}
      {state.status === "thinking" && (
        <div className="bg-blue-50 p-3 rounded-lg animate-pulse">
          🤔 Agent is thinking... ({state.progress}%)
          <progress value={state.progress} max={100} />
        </div>
      )}

      {/* Tool calls (show what agent is doing) */}
      {toolCalls.map((tc) => (
        <div key={tc.id} className="bg-gray-50 p-2 rounded text-sm">
          🔧 <strong>{tc.name}</strong>: {tc.status === "running" ? "Working..." : "Done"}
          {tc.result && <pre className="mt-1">{JSON.stringify(tc.result, null, 2)}</pre>}
        </div>
      ))}

      {/* Messages */}
      {messages.map((msg) => (
        <div key={msg.id} className={msg.role === "user" ? "text-right" : "text-left"}>
          <p>{msg.content}</p>
        </div>
      ))}

      {/* Dynamic UI from agent state */}
      {state.charts?.map((chart, i) => (
        <Chart key={i} type={chart.type} data={chart.data} />
      ))}

      {state.suggestions && (
        <div className="flex gap-2">
          {state.suggestions.map((s) => (
            <button key={s} onClick={() => sendMessage(s)} className="px-3 py-1 bg-blue-100 rounded">
              {s}
            </button>
          ))}
        </div>
      )}

      {/* Input */}
      <form onSubmit={(e) => { e.preventDefault(); sendMessage(input); }}>
        <input placeholder="Ask anything..." disabled={isStreaming} />
      </form>
    </div>
  );
}

Installation

bash
npm install @ag-ui/react @ag-ui/server

Best Practices

  1. State streaming — Emit state updates for progress, status, UI components; users see agent's thought process
  2. Tool call transparency — Show tool calls in real-time; builds trust, helps debugging
  3. Suggestions — Emit suggestion buttons after responses; guide users to next actions
  4. Custom UI — Use state updates to render charts, tables, forms; richer than plain text
  5. Human-in-the-loop — Emit confirmation requests before destructive actions; users approve or reject
  6. Progress tracking — Emit progress percentages for long tasks; prevent user anxiety
  7. Framework agnostic — AG-UI protocol works with any agent backend (LangGraph, CrewAI, custom)
  8. CopilotKit integration — AG-UI powers CopilotKit; use CopilotKit for higher-level React components

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ag Ui AI skill do?

You are an expert in AG-UI (Agent-User Interaction Protocol), the open standard by CopilotKit for connecting AI agents to frontend UIs. You help developers stream agent actions, tool calls, state updates, and text generation to React components in real-time — enabling rich agent UIs where users see what the agent is thinking, doing, and can intervene at any step.

Why use Ag Ui on TypingMind?

Because you install it once and use it with any model. Ag Ui 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 Ag Ui in TypingMind?

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

Which AI models can use Ag Ui?

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 Ag Ui?

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

Is the Ag Ui AI skill free?

Yes. It is published on GitHub by TerminalSkills 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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