chat-layer

Orchestrate agents and render rich content via the A2UI v0.10 protocol.

2|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/ai-kitchen-inc/openbench --skill chat-layer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: chat-layer
Source: https://github.com/ai-kitchen-inc/openbench/tree/main/.claude/skills/chat-layer
Command: npx skills add https://github.com/ai-kitchen-inc/openbench --skill chat-layer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides the backend infrastructure to build dynamic, interactive chat interfaces, enabling rich content rendering and complex conversational workflows.

Core Features & Use Cases

  • A2UI v0.10 Protocol: Supports Google's declarative JSON streaming UI protocol for building interactive surfaces.
  • Content Rendering: Integrates various renderers for text, charts, forms, files, and more.
  • Streaming Transport: Implements SSE and REST transport for real-time communication.
  • Use Case: Develop a customer support chatbot that can display interactive charts of user data, allow users to fill out forms directly within the chat, and stream responses progressively.

Quick Start

Use the chat-layer skill to stream a response from the provided agent.

Frequently Asked Questions about chat-layer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an interactive AI chat interface with streaming text and custom components?

You can build interactive AI chat interfaces by orchestrating agents and rendering rich content via the A2UI v0.10 protocol. This supports streaming text, custom components like charts and file cards, and integrates external agent frameworks through a unified transport layer.

What is the A2UI v0.10 protocol for building chat experiences?

The A2UI v0.10 protocol is a declarative JSON streaming UI protocol used for building interactive surfaces. It enables chat interfaces to dynamically render rich content like forms, files, and charts during real-time agent orchestration.

How do I stream responses progressively in an AI customer support chatbot?

You can stream responses progressively by implementing SSE and REST transport for real-time communication. This allows a customer support chatbot to display interactive data charts and stream text efficiently within the chat session.

Can I use this agent orchestration layer with external agent frameworks?

Yes, you can integrate external agent frameworks through a unified transport layer. This enables dynamic chat session management and rich content rendering while maintaining real-time streaming communication.

Does this chat layer support rendering interactive forms directly within the chat?

Yes, the chat layer supports rendering interactive forms directly within the chat. It integrates various renderers for text, charts, and files, allowing users to fill out forms without leaving the conversational workflow.