openui-forge-anthropic: Design & UI for AI Agents | OpenAgentSkill

Overview

OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.

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OpenUI Forge — Anthropic

Build generative UI apps with OpenUI + Anthropic Claude. Converts Anthropic streaming events to OpenAI-compatible NDJSON.

Activation Triggers

"openui anthropic", "openui claude", "openui sonnet"
"generative ui claude", "claude streaming ui"

Prerequisites

Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
ANTHROPIC_API_KEY environment variable set
Next.js project (App Router recommended)

Quick Start

Install dependencies:

npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @anthropic-ai/sdk

Add the CSS import to app/layout.tsx:

import "@openuidev/react-ui/components.css";

Create the API route and frontend page below
Run npm run dev and test

Full Code

Backend: `app/api/chat/route.ts`

The backend streams from Anthropic and converts each event into OpenAI-compatible SSE chunks that openAIAdapter() expects (data: {json}\n\n lines, terminated by data: [DONE]).

import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs.",
    additionalRules: ["Always use Stack as root when combining multiple components."],
  });

  // ANTHROPIC_MODEL alternatives: claude-opus-4-8, claude-haiku-4-5, claude-fable-5
  const stream = client.messages.stream({
    model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
    max_tokens: 4096,
    system: systemPrompt,
    messages,
  });

  const encoder = new TextEncoder();
  const readableStream = new ReadableStream({
    async start(controller) {
      const id = `chatcmpl-${Date.now()}`;
      for await (const event of stream) {
        if (
          event.type === "content_block_delta" &&
          event.delta.type === "text_delta"
        ) {
          const chunk = {
            id,
            object: "chat.completion.chunk",
            choices: [
              {
                index: 0,
                delta: { content: event.delta.text },
                finish_reason: null,
              },
            ],
          };
          controller.enqueue(
            encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`)
          );
        }
      }
      const done = {
        id,
        object: "chat.completion.chunk",
        choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
      };
      controller.enqueue(encoder.encode(`data: ${JSON.stringify(done)}\n\n`));
      controller.enqueue(encoder.encode("data: [DONE]\n\n"));
      controller.close();
    },
  });

  return new Response(readableStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}

Frontend: `app/chat/page.tsx`

"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="/api/chat"
    />
  );
}

The backend emits SSE (data: {json}\n\n). Pair it with openAIAdapter() on the frontend — openAIReadableStreamAdapter() is for NDJSON (no data: prefix) and will silently produce no output here.

Component Creation

import { defineComponent } from "@openuidev/react-lang";
import { z } from "zod";

export const StatusCard = defineComponent({
  name: "StatusCard",
  description: "Displays a status with label and color indicator",
  props: z.object({
    label: z.string().describe("Status label text"),
    status: z.enum(["ok", "warning", "error"]).describe("Current status level"),
  }),
  component: ({ props }) => {
    const colors = { ok: "#22c55e", warning: "#eab308", error: "#ef4444" };
    return (
      <div style={{ display: "flex", alignItems: "center", gap: 8 }}>
        <span style={{ width: 10, height: 10, borderRadius: "50%", background: colors[props.status] }} />
        <span>{props.label}</span>
      </div>
    );
  },
});

System Prompt Generation

npx @openuidev/cli generate ./src/lib/library.ts --out src/generated/system-prompt.txt

Or at runtime: openuiChatLibrary.prompt({ preamble: "...", additionalRules: [...] }).

Validation Checklist

ANTHROPIC_API_KEY is set in .env.local
CSS import present in root layout
Backend converts Anthropic content_block_delta events to OpenAI-compatible SSE chunks
Final chunk has finish_reason: "stop" and ends with data: [DONE]
Frontend uses streamProtocol={openAIAdapter()} and openAIMessageFormat
componentLibrary={openuiChatLibrary} prop passed to FullScreen

Error Patterns

Error	Cause	Fix
401 from Anthropic	Missing or invalid API key	Set `ANTHROPIC_API_KEY` in `.env.local`
Stream hangs	Missing `[DONE]` sentinel or `controller.close()`	Ensure final chunk and `[DONE]` are sent
Garbled output	Not wrapping in `data: ...` SSE format	Each chunk must be `data: {json}\n\n`
Components render as text	Library not passed to FullScreen	Add `componentLibrary={openuiChatLibrary}` prop
Nothing renders, no error	Used `openAIReadableStreamAdapter()` (NDJSON) on SSE stream, or `adapter=` prop (silently ignored)	Use `streamProtocol={openAIAdapter()}`
`max_tokens` required	Anthropic API requires explicit max_tokens	Always set `max_tokens` (e.g., 4096)

View source ↗

File metadata

name: openui-forge-anthropic
description: OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.
version: 1.2.0
author: OthmanAdi

View original text

---
name: openui-forge-anthropic
description: OpenUI generative UI with Anthropic Claude SDK backend. Stream conversion to OpenAI NDJSON format.
version: 1.2.0
author: OthmanAdi
---

# OpenUI Forge — Anthropic

Build generative UI apps with OpenUI + Anthropic Claude. Converts Anthropic streaming events to OpenAI-compatible NDJSON.

## Activation Triggers

- "openui anthropic", "openui claude", "openui sonnet"
- "generative ui claude", "claude streaming ui"

## Prerequisites

- Node.js >= 22 (24 LTS recommended), React >= 18.3.1 (19+ recommended)
- `ANTHROPIC_API_KEY` environment variable set
- Next.js project (App Router recommended)

## Quick Start

1. Install dependencies:
```bash
npm install @openuidev/react-ui @openuidev/react-headless @openuidev/react-lang lucide-react zod @anthropic-ai/sdk
```
2. Add the CSS import to `app/layout.tsx`:
```tsx
import "@openuidev/react-ui/components.css";
```
3. Create the API route and frontend page below
4. Run `npm run dev` and test

## Full Code

### Backend: `app/api/chat/route.ts`

The backend streams from Anthropic and converts each event into OpenAI-compatible SSE chunks that `openAIAdapter()` expects (`data: {json}\n\n` lines, terminated by `data: [DONE]`).

```typescript
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import Anthropic from "@anthropic-ai/sdk";

const client = new Anthropic();

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

  const systemPrompt = openuiChatLibrary.prompt({
    preamble: "You are a helpful assistant that generates interactive UIs.",
    additionalRules: ["Always use Stack as root when combining multiple components."],
  });

  // ANTHROPIC_MODEL alternatives: claude-opus-4-8, claude-haiku-4-5, claude-fable-5
  const stream = client.messages.stream({
    model: process.env.ANTHROPIC_MODEL ?? "claude-sonnet-4-6",
    max_tokens: 4096,
    system: systemPrompt,
    messages,
  });

  const encoder = new TextEncoder();
  const readableStream = new ReadableStream({
    async start(controller) {
      const id = `chatcmpl-${Date.now()}`;
      for await (const event of stream) {
        if (
          event.type === "content_block_delta" &&
          event.delta.type === "text_delta"
        ) {
          const chunk = {
            id,
            object: "chat.completion.chunk",
            choices: [
              {
                index: 0,
                delta: { content: event.delta.text },
                finish_reason: null,
              },
            ],
          };
          controller.enqueue(
            encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`)
          );
        }
      }
      const done = {
        id,
        object: "chat.completion.chunk",
        choices: [{ index: 0, delta: {}, finish_reason: "stop" }],
      };
      controller.enqueue(encoder.encode(`data: ${JSON.stringify(done)}\n\n`));
      controller.enqueue(encoder.encode("data: [DONE]\n\n"));
      controller.close();
    },
  });

  return new Response(readableStream, {
    headers: { "Content-Type": "text/event-stream" },
  });
}
```

### Frontend: `app/chat/page.tsx`

```tsx
"use client";
import { FullScreen } from "@openuidev/react-ui";
import { openuiChatLibrary } from "@openuidev/react-ui/genui-lib";
import {
  openAIAdapter,
  openAIMessageFormat,
} from "@openuidev/react-headless";

export default function ChatPage() {
  return (
    <FullScreen
      componentLibrary={openuiChatLibrary}
      streamProtocol={openAIAdapter()}
      messageFormat={openAIMessageFormat}
      apiUrl="/api/chat"
    />
  );
}
```

> The backend emits SSE (`data: {json}\n\n`). Pair it with `openAIAdapter()` on the frontend — `openAIReadableStreamAdapter()` is for NDJSON (no `data:` prefix) and will silently produce no output here.

## Component Creation

```tsx
import { defineComponent } from "@openuidev/react-lang";
import { z } from "zod";

export const StatusCard = defineComponent({
  name: "StatusCard",
  description: "Displays a status with label and color indicator",
  props: z.object({
    label: z.string().describe("Status label text"),
    status: z.enum(["ok", "warning", "error"]).describe("Current status level"),
  }),
  component: ({ props }) => {
    const colors = { ok: "#22c55e", warning: "#eab308", error: "#ef4444" };
    return (
      <div style={{ display: "flex", alignItems: "center", gap: 8 }}>
        <span style={{ width: 10, height: 10, borderRadius: "50%", background: colors[props.status] }} />
        <span>{props.label}</span>
      </div>
    );
  },
});
```

## System Prompt Generation

```bash
npx @openuidev/cli generate ./src/lib/library.ts --out src/generated/system-prompt.txt
```

Or at runtime: `openuiChatLibrary.prompt({ preamble: "...", additionalRules: [...] })`.

## Validation Checklist

- [ ] `ANTHROPIC_API_KEY` is set in `.env.local`
- [ ] CSS import present in root layout
- [ ] Backend converts Anthropic `content_block_delta` events to OpenAI-compatible SSE chunks
- [ ] Final chunk has `finish_reason: "stop"` and ends with `data: [DONE]`
- [ ] Frontend uses `streamProtocol={openAIAdapter()}` and `openAIMessageFormat`
- [ ] `componentLibrary={openuiChatLibrary}` prop passed to `FullScreen`

## Error Patterns

| Error | Cause | Fix |
|-------|-------|-----|
| 401 from Anthropic | Missing or invalid API key | Set `ANTHROPIC_API_KEY` in `.env.local` |
| Stream hangs | Missing `[DONE]` sentinel or `controller.close()` | Ensure final chunk and `[DONE]` are sent |
| Garbled output | Not wrapping in `data: ...` SSE format | Each chunk must be `data: {json}\n\n` |
| Components render as text | Library not passed to FullScreen | Add `componentLibrary={openuiChatLibrary}` prop |
| Nothing renders, no error | Used `openAIReadableStreamAdapter()` (NDJSON) on SSE stream, or `adapter=` prop (silently ignored) | Use `streamProtocol={openAIAdapter()}` |
| `max_tokens` required | Anthropic API requires explicit max_tokens | Always set `max_tokens` (e.g., 4096) |

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Low GitHub adoption signal
AI review approval is missing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 22 GitHub stars
Stars/forks activity: 22 stars, 0 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution
Review status: AI review approval is missing

Open full audit

Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.

Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3

Source & usage notes

IndexedStatic Checked

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: OthmanAdi/openui-forge
License: MIT
Version: 1.2.0
Last GitHub push: Aug 3, 2026
Registry updated: Sep 13, 2026
Instruction path: .agents/skills/openui-forge-anthropic/SKILL.md @ 977180d4d3e9

Version reported in registry metadata; check source releases before relying on it.

Quality

49/100

Needs review

Trust

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "othmanadi-openui-forge-anthropic",
      "task": "Use openui-forge-anthropic in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/othmanadi-openui-forge-anthropic",
    "api": "https://www.openagentskill.com/api/agent/skills/othmanadi-openui-forge-anthropic",
    "audit": "https://www.openagentskill.com/skills/othmanadi-openui-forge-anthropic/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=othmanadi-openui-forge-anthropic&task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20openui-forge-anthropic%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/othmanadi-openui-forge-anthropic/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/othmanadi-openui-forge-anthropic"
  }
}

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Creator: OthmanAdi
Source: OthmanAdi/openui-forge
Indexed by: OpenAgentSkill community index

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