components
Skill1 starsChanged 9 months agoMITView on GitHub
Creates and registers Tambo components - generative (AI creates on-demand) and interactable (pre-placed, AI updates). Use when defining components, working with TamboComponent, withTamboInteractable, propsSchema, or registering components for AI to render or update.
7 other projects use a version of this.
Adopted by
Most recently taken up by
- CreativesLibrary/Componentstheir own version, first seen Nov 8, 2026
- AnayDhawan/Componentstheir own version, first seen Oct 13, 2026
- trezor/trezor-suitetheir own version, first seen Oct 8, 2026
- sukirman1901/frontend-experttheir own version, first seen Sep 10, 2026
- wachterjohannes/symfony-skillstheir own version, first seen Sep 3, 2026
- blixvip/skillstheir own version, first seen Aug 19, 2026
Other versions7 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 7
- trezor/trezor-suite★ 1.1ksame name
- mistralai/client-ts★ 162same name
- AnayDhawan/Components★ 17same name
- CreativesLibrary/Components★ 17same name
- sukirman1901/frontend-expert★ 9same name
- blixvip/skills★ 4same name
- wachterjohannes/symfony-skills★ 4same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository11 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .agents/skills/vercel-composition-patterns/AGENTS.mdAGENTS.md
- .agents/skills/vercel-react-best-practices/AGENTS.mdAGENTS.md
- add-components-to-registrySkill
- cliSkill
- component-renderingSkill
- react-router-framework-modeSkill
- threadsSkill
- tools-and-contextSkill
- vercel-composition-patternsSkill
- vercel-react-best-practicesSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 1 is distinctive, and 2 are very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 59
Use ComponentRenderer to render AI-generated components in your message list:
- Very specific: line 100
Use z.infer<typeof Schema> for TypeScript props type
- Distinctive: line 136
Tool registration: Update tools registered automatically
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Tambo Components
Two component types: generative (AI creates on-demand) and interactable (pre-placed, AI updates).
Quick Start
// Generative: AI creates when needed
const components: TamboComponent[] = [
{
name: "WeatherCard",
component: WeatherCard,
description: "Shows weather. Use when user asks about weather.",
propsSchema: z.object({ city: z.string(), temp: z.number() }),
},
];
<TamboProvider components={components}>
<App />
</TamboProvider>;Generative Components
AI dynamically selects and renders these in response to user messages.
import { TamboProvider, TamboComponent } from "@tambo-ai/react";
import { z } from "zod";
const WeatherCardSchema = z.object({
city: z.string().describe("City name"),
temperature: z.number().describe("Temperature in Celsius"),
condition: z.string().describe("Weather condition"),
});
const components: TamboComponent[] = [
{
name: "WeatherCard",
component: WeatherCard,
description:
"Displays weather for a city. Use when user asks about weather.",
propsSchema: WeatherCardSchema,
},
];
<TamboProvider apiKey={apiKey} components={components}>
<App />
</TamboProvider>;Rendering Generative Components
Use ComponentRenderer to render AI-generated components in your message list:
import { ComponentRenderer } from "@tambo-ai/react";
function Message({
message,
threadId,
}: {
message: TamboMessage;
threadId: string;
}) {
return (
<div>
{message.content.map((block) => {
switch (block.type) {
case "text":
return <p key={block.type}>{block.text}</p>;
case "component":
return (
<ComponentRenderer
key={block.id}
content={block}
threadId={threadId}
messageId={message.id}
/>
);
default:
return null;
}
})}
</div>
);
}Generative Key Points
- propsSchema: Zod object with
.describe()on each field - description: Tells AI when to use the component
- Streaming: Props start
undefined, make them optional or handle gracefully - Use
z.infer<typeof Schema>for TypeScript props type
Interactable Components
Pre-place in your UI; AI can observe and update props via natural language.
import { withTamboInteractable } from "@tambo-ai/react";
import { z } from "zod";
const NoteSchema = z.object({
title: z.string().describe("Note title"),
content: z.string().describe("Note content"),
color: z.enum(["white", "yellow", "blue"]).optional(),
});
function Note({ title, content, color = "white" }: Props) {
return (
<div style={{ backgroundColor: color }}>
<h3>{title}</h3>
<p>{content}</p>
</div>
);
}
export const InteractableNote = withTamboInteractable(Note, {
componentName: "Note",
description: "A note with editable title, content, and color",
propsSchema: NoteSchema,
});Interactable How It Works
- Auto-registration: Component registers when mounted
- Context sending: Current props automatically visible to AI
- Tool registration: Update tools registered automatically
- Bidirectional: User edits and AI updates both work
When to Use Each
| Generative | Interactable |
| AI creates on-demand | You pre-place in UI |
| One-time render | Persistent across session |
| Props generated once | AI can update props |
| Chat responses, dashboards | Settings, forms, task boards |
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

