install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/TerminalSkills/skills/ag-ui" ~/.claude/skills/comeonoliver-skillshub-ag-ui && rm -rf "$T"
manifest:
skills/TerminalSkills/skills/ag-ui/SKILL.mdsource content
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)
// 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
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
npm install @ag-ui/react @ag-ui/server
Best Practices
- State streaming — Emit state updates for progress, status, UI components; users see agent's thought process
- Tool call transparency — Show tool calls in real-time; builds trust, helps debugging
- Suggestions — Emit suggestion buttons after responses; guide users to next actions
- Custom UI — Use state updates to render charts, tables, forms; richer than plain text
- Human-in-the-loop — Emit confirmation requests before destructive actions; users approve or reject
- Progress tracking — Emit progress percentages for long tasks; prevent user anxiety
- Framework agnostic — AG-UI protocol works with any agent backend (LangGraph, CrewAI, custom)
- CopilotKit integration — AG-UI powers CopilotKit; use CopilotKit for higher-level React components