AI, Spatial & Voice UX

Guide design of AI-native, voice, spatial, and multimodal interfaces.

35|13|Updated Feb 14, 2026
One-click install
npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill ai-spatial-voice-ux
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: AI, Spatial & Voice UX
Source: https://github.com/phazurlabs/ux-ui-mastery/tree/main/skills/ai-spatial-voice-ux
Command: npx skills add https://github.com/phazurlabs/ux-ui-mastery --skill ai-spatial-voice-ux

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you design interfaces for AI-native products, voice experiences, and spatial computing so users can trust, understand, and comfortably navigate advanced interaction patterns.

Core Features & Use Cases

  • AI-Native UX Patterns: Handles streaming responses, context transparency, confidence cues, tool-use visibility, and safe human-in-the-loop controls.
  • Voice and Conversational Design: Covers wake words, dialog state management, prompt escalation, error recovery, and multimodal voice-plus-screen experiences.
  • Spatial and Multimodal Design: Provides guidance for AR, VR, MR, gaze, hand, gesture, and mixed-input layouts that stay comfortable and legible.
  • Use Case: A product team building an AI assistant for visionOS can use this Skill to shape conversational flows, clarify model behavior, and design spatial controls that feel natural instead of overwhelming.

Quick Start

Ask for a design recommendation for your AI, voice, or spatial interface and specify the platform, user goal, and interaction constraints.

Frequently Asked Questions about AI, Spatial & Voice UX

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

FAQPage Schema
How do I design UX patterns for streaming AI responses and confidence indicators?

Design streaming AI responses and confidence indicators by applying context transparency, tool-use visibility, and safe human-in-the-loop approval gates. This ensures users understand model behavior and can safely approve critical actions during conversational workflows.

What is the best way to design voice UX and conversational UI error recovery?

Voice UX and conversational UI error recovery require prompt escalation, dialog state management, and multimodal voice-plus-screen fallbacks. These patterns ensure assistants gracefully handle misunderstandings and guide users back to successful interactions.

Can I use spatial computing UX patterns for AR, VR, and mixed-reality layouts?

Spatial computing UX patterns support AR, VR, and mixed-reality layouts using gaze, hand, and gesture inputs. They ensure multimodal interfaces remain comfortable, legible, and accessible without overwhelming the user during extended mixed-input sessions.

How do I manage multimodal input fusion for embedded AI copilot workflows?

Manage multimodal input fusion for embedded AI copilot workflows by designing interfaces that clarify model behavior and fuse mixed-input sources gracefully. This allows desktop and mobile experiences to handle overlapping voice, spatial, and screen interactions seamlessly.

Does this approach handle accessibility and comfort for visionOS AI assistants?

Yes, this approach handles accessibility and comfort for visionOS AI assistants by shaping conversational flows and spatial controls. It ensures mixed-reality interfaces provide natural interaction patterns and graceful fallback behavior instead of overwhelming users.