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interactive-widgets

Transform AI text responses into interactive widget experiences.

Updated Apr 2, 2026
Search Tags:#rbac#flutter#streaming responses#interactive widgets#widget protocol#llm ui
One-click install
npx skills add https://github.com/myeohVmzrka92/disease-risk-controller-S2 --skill interactive-widgets-myeohvmzrka92
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: interactive-widgets
Source: https://github.com/myeohVmzrka92/disease-risk-controller-S2/tree/main/.claude/skills/20-interactive-widgets
Command: npx skills add https://github.com/myeohVmzrka92/disease-risk-controller-S2 --skill interactive-widgets-myeohvmzrka92

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It replaces static AI text replies with interactive widget experiences so users can act on data, submit inputs, and drill into results without leaving the conversation.

Core Features & Use Cases

  • LLM-driven widget generation: Convert user intent and backend data into structured widgets such as cards, charts, tables, forms, and navigation actions.
  • Streaming UI responses: Send text, widget descriptors, and citations incrementally to keep the interface responsive during long-running generation.
  • Protocol and action design: Define safe widget schemas, permissions, and backend action handlers for enterprise workflows.
  • Use Case: A support assistant can answer a question, render a form for follow-up details, and then update the conversation with a drill-down table after submission.

Quick Start

Use this skill to design a streaming widget protocol for an AI chat app that renders interactive components and permission-checked actions.

Frequently Asked Questions about interactive-widgets

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

FAQPage Schema
How do I turn AI text responses into interactive widgets within an LLM UI?▼

Interactive widget protocols replace static text by sending validated JSON descriptors from the backend to render dynamic UI components like cards, charts, and forms. This allows users to submit inputs and drill into results without leaving the conversation.

How do I implement streaming responses for dynamic UI components in a chat application?▼

Streaming UI responses are implemented by sending text, widget descriptors, and citations incrementally from the backend. This keeps the frontend interface responsive during long-running LLM generation while updating the conversation state dynamically.

What is the best way to handle state management and RBAC for LLM-generated widget actions?▼

Handling RBAC for LLM-generated widget actions requires defining safe widget schemas and permission-checked backend action handlers. State management ensures that enterprise workflows remain secure when users interact with dynamic forms and navigation elements.

Can I use Flutter to render streaming widget protocols and dynamic forms?▼

Yes, Flutter can serve as the frontend rendering layer for streaming widget protocols. It consumes validated JSON descriptors to render interactive components, while the backend manages state management and streams incremental UI updates.

When should I not use interactive widgets for AI chat responses?▼

You should avoid interactive widgets if your application only requires static text replies, lacks backend streaming capabilities, or cannot implement validated JSON schemas and RBAC-protected action handlers for secure enterprise workflows.

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