generative-ui

tambo-ai/tambo · updated Apr 8, 2026

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$npx skills add https://github.com/tambo-ai/tambo --skill generative-ui
0 commentsdiscussion
summary

Build generative UI apps with Tambo — create rich, interactive React components from natural language.

skill.md

Generative UI

Build generative UI apps with Tambo — create rich, interactive React components from natural language.

Reference Guides

Load these when you need deeper implementation details beyond the bootstrap flow:

  • Components - Load when creating custom components. Generative vs interactable, propsSchema, ComponentRenderer.
  • Component Rendering - Streaming props, loading states, persistent state. Load when customizing rendering.
  • Threads and Input - Load when building custom chat UI. useTambo(), useTamboThreadInput(), userKey/userToken auth, suggestions, voice.
  • Tools and Context - Load when adding tools or MCP. defineTool(), MCP servers, contextHelpers.
  • CLI Reference - Load for tambo add components. Component library, non-interactive flags, exit codes.

These shared references are duplicated from building-with-tambo so each skill works independently.

One-Prompt Flow

The goal is to get the user from zero to a running app in a single prompt. Ask all questions upfront using AskUserQuestion with multiple questions, then execute everything without stopping.

Step 1: Gather All Non-Sensitive Preferences (Single AskUserQuestion Call)

Use AskUserQuestion with up to 3 questions in ONE call. Authentication is handled by the CLI in a later step.

Question 1: What do you want to build?

Ask the user what kind of app they're building. This drives which starter components to create. Examples: "a dashboard", "a chatbot", "a data visualization tool", "a task manager". If the user already said what they want in their initial message, skip this question.

Question 2: Framework

Options:

  • Next.js (Recommended) - Full-stack React with App Router
  • Vite - Fast, lightweight React setup

Question 3: App name

Let the user pick a name for their project directory. Default suggestion: derive from what they want to build (e.g., "my-dashboard", "my-chatbot"). Use kebab-case (letters, numbers, hyphens only). If the user gives a non-slug name like "Sales Dashboard", propose sales-dashboard instead.

Skip questions when the user already told you the answer. If they said "build me a Next.js dashboard app called analytics", you already know the framework, the app idea, and the name.

Step 2: Execute Everything (No Stopping)

Run all of these sequentially without asking for confirmation between steps. If any command fails, stop the flow, surface the error, and ask the user how to proceed — do not continue to later steps.

All templates (standard, vite, analytics, expo) come with chat UI, TamboProvider wiring, component registry, and starter components already included. You do NOT need to add chat UI or wire up the app — just scaffold, configure the API key, add custom components, and start the server.

2a. Scaffold the project

For Next.js (recommended):

npx tambo create-app <app-name> --template=standard --skip-tambo-init
cd <app-name>

For Vite:

npx tambo create-app <app-name> --template=vite --skip-tambo-init
cd <app-name>

Use --skip-tambo-init since create-app normally tries to run tambo init interactively, which won't work in non-interactive environments like coding agents. We handle authentication in the next step.

2b. Authenticate and initialize Tambo

npx tambo init --project-name=<app-name>

This opens the browser for authentication and polls until the user completes auth (up to 15 minutes). Use a long timeout (at least 15 minutes) when running this command. Once auth completes, the CLI creates the project and writes the API key to .env.local with the correct env var for the framework (NEXT_PUBLIC_TAMBO_API_KEY, VITE_TAMBO_API_KEY, etc.).

IMPORTANT: Do NOT ask the user to paste an API key manually. Always use the CLI auth flow.

2c. Create custom starter components

The template includes basic components, but add 1-2 components tailored to what the user wants to build. Don't use generic examples:

  • Dashboard appStatsCard, DataTable
  • ChatbotBotResponse with markdown support
  • Data visualizationChart with configurable data
  • Task managerTaskCard, TaskBoard
  • Generic / unclearContentCard

Each component needs:

  1. A Zod schema with .describe() on every field
  2. The React component itself
  3. Registration in the existing component registry (lib/tambo.ts — add to the existing components array, don't replace it)

Schema constraints — Tambo will reject invalid schemas at runtime:

  • No z.record() — Record types (objects with dynamic keys) are not supported anywhere in the schema, including nested inside arrays or objects. Use z.object() with explicit named keys instead.
  • No z.map() or z.set() — Use arrays and objects instead.
  • For tabular data like rows, use z.array(z.object({ col1: z.string(), col2: z.number() })) with explicit column keys — NOT z.array(z.record(z.string(), z.unknown())).

React best practices for generated components:

  • Always add unique key props when rendering lists (.map()). Use a unique field from the data (like id) — not the array index.
  • Include an id field (e.g., z.string().describe("Unique identifier")) in schemas for array items so there's always a stable key available.

Example:

// src/components/StatsCard.tsx
import { z } from "zod/v4";

export const StatsCardSchema = z.object({
  title: z.string().describe("Metric name"),
  value: z.number().describe("Current value"),
  change: z.number().optional().describe("Percent change from previous period"),
  trend: z.enum(["up", "down", "flat"]).optional().describe("Trend direction"),
});

type StatsCardProps = z.infer<typeof StatsCardSchema>;

export function StatsCard({
  title,
  value,
  change,
  trend = "flat",
}: StatsCardProps) {
  // ... implementation with Tailwind styling
}

Then add to the existing registry in lib/tambo.ts:

// Add to the existing components array — don't replace what's already there
// Next.js: import { StatsCard, StatsCardSchema } from "@/components/StatsCard";
// Vite: import { StatsCard, StatsCardSchema } from "../components/StatsCard";
import { StatsCard, StatsCardSchema } from "@/components/StatsCard";

// ... existing components ...
{
  name: "StatsCard",
  component: StatsCard,
  description: "Displays a metric with value and trend. Use when user asks about stats, metrics, or KPIs.",
  propsSchema: StatsCardSchema,
},

2d. Start the dev server

Only start the dev server after all code changes (scaffolding, init, component creation, registry updates) are complete.

npm run dev

Run this in the background so the user can see their app immediately.

Step 3: Summary

After everything is running, give a brief summary:

  • What was set up
  • What components were created and what they do
  • The URL where the app is running (typically http://localhost:3000 for Next.js, http://localhost:5173 for Vite)
  • If auth was skipped: remind them once to run npx tambo init to authenticate
  • A suggestion for what to try first (e.g., "Try asking it to show you a stats card for monthly revenue")

Technology Stacks Reference

Recommended Stack (Default)

Next.js 14+ (App Router)
├── TypeScript
├── Tailwind CSS
├── Zod (for schemas)
└── @tambo-ai/react
npx tambo create-app my-app --template=standard

Vite Stack

Vite + React
├── TypeScript
├── Tailwind CSS
├── Zod
└── @tambo-ai/react

Minimal Stack (No Tailwind)

Vite + React
├── TypeScript
├── Plain CSS
├── Zod
└── @tambo-ai/react

Component Registry Pattern

Every generative component must be registered:

import { TamboComponent } from "@tambo-ai/react";
import { ComponentName, ComponentNameSchema } from "@/components/ComponentName";

export const components: TamboComponent[] = [
  {
    name: "ComponentName",
    component: ComponentName,
    description: "What it does. When to use it.",
    propsSchema: ComponentNameSchema,
  },
];

Key rules:

  • propsSchema: Zod object with .describe() on every field — this is how the AI knows what to pass
  • description: Tell the AI when to use this component — be specific about trigger phrases
  • Streaming: Props arrive incrementally, so handle undefined gracefully (optional fields or defaults)

Adding More Chat UI (Optional)

Templates already include chat UI. These are only needed if the user wants additional UI primitives beyond what the template provides:

npx tambo add message-thread-full --yes    # Complete chat interface
npx tambo add control-bar --yes            # Controls and actions
npx tambo add thread-history --yes         # Conversation history sidebar

Supported Technologies

Technology Support Level Notes
Next.js 14+ Full Recommended, App Router preferred
Vite Full Great for SPAs
Create React App Partial Works but CRA is deprecated
Remix Partial Works with client components
TypeScript Full Strongly recommended
JavaScript Full Works but less type safety
Tailwind CSS Full Default for CLI components
Plain CSS Full Need custom component styling
CSS Modules Full Supported
Zod Required Used for all schemas

Verification

Have the user verify the app works by:

  1. Opening the app URL in a browser
  2. Typing a prompt that should trigger one of the registered components (e.g., "Show me a stats card for monthly revenue")
  3. Verifying the component renders with AI-generated props

If something doesn't work:

  • Check the registry includes the component
  • Check the description matches the prompt
  • Check the dev server has no console errors

Reporting Bugs & Feedback

If you encounter any of these while helping a user, suggest filing a GitHub issue:

  • A bug in @tambo-ai/react, @tambo-ai/client, or the tambo CLI
  • Documentation that contradicts actual behavior
  • Missing or misleading instructions in this skill

Issue Template

Use this template when drafting an issue for tambo-ai/tambo:

**
how to use generative-ui

How to use generative-ui on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add generative-ui
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/tambo-ai/tambo --skill generative-ui

The skills CLI fetches generative-ui from GitHub repository tambo-ai/tambo and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/generative-ui

Reload or restart Cursor to activate generative-ui. Access the skill through slash commands (e.g., /generative-ui) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.550 reviews
  • Luis Garcia· Dec 24, 2024

    Keeps context tight: generative-ui is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Lucas Perez· Dec 24, 2024

    Registry listing for generative-ui matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zara Taylor· Dec 16, 2024

    generative-ui has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Dec 8, 2024

    generative-ui has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 4, 2024

    Registry listing for generative-ui matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Anika Srinivasan· Dec 4, 2024

    generative-ui fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 23, 2024

    generative-ui reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Chawla· Nov 23, 2024

    We added generative-ui from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Anika Reddy· Nov 15, 2024

    Useful defaults in generative-ui — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Soo Kapoor· Nov 15, 2024

    I recommend generative-ui for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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