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ai-interaction-patterns

Design AI interaction patterns for onboarding, prompting, trust, and user control.

Updated Apr 2, 2026
Search Tags:#onboarding#prompt design#transparency#trust#interaction patterns#ai ux#human in the loop
One-click install
npx skills add https://github.com/aliciapls/ML-Week-2---Healthcare --skill ai-interaction-patterns-aliciapls
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-interaction-patterns
Source: https://github.com/aliciapls/ML-Week-2---Healthcare/tree/main/.claude/skills/25-ai-interaction-patterns
Command: npx skills add https://github.com/aliciapls/ML-Week-2---Healthcare --skill ai-interaction-patterns-aliciapls

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps teams design AI-powered experiences that reduce blank-canvas friction, improve prompt quality, and make AI behavior understandable, controllable, and trustworthy.

Core Features & Use Cases

  • Wayfinding and onboarding: Use galleries, suggestions, templates, and nudges to help users start with confidence and discover what the AI can do.
  • Prompt actions and tuning: Apply patterns such as inline actions, regeneration, attachments, modes, parameters, and prompt enhancers to refine outputs and adapt behavior.
  • Governance and trust: Add action plans, stream of thought, controls, citations, verification, disclosure, caveats, consent, and memory controls for high-stakes or persistent AI products.
  • Use case: A healthcare assistant can guide first-time users with prompt examples, explain its limits, surface citations, let users stop generation, and clearly label AI-generated content.

Quick Start

Use the ai-interaction-patterns skill to recommend the best AI UX patterns for a healthcare assistant that needs onboarding, citations, disclosure, and user control.

Frequently Asked Questions about ai-interaction-patterns

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

FAQPage Schema
What are AI interaction patterns for UX design?▼

AI interaction patterns are reusable UX frameworks that improve onboarding, prompt quality, trust, transparency, and user control in AI-powered interfaces like chat assistants and copilots.

How do I design onboarding for an AI chat assistant?▼

Design AI onboarding using wayfinding patterns like galleries, suggestions, templates, and nudges to help users start confidently and discover what the AI can do without blank-canvas friction.

How do I build trust and transparency in AI-powered interfaces?▼

Build trust and transparency in AI interfaces by applying governance patterns such as citations, verification, disclosure, caveats, stream of thought, and clear AI identity labels for generated content.

What UX patterns help users control and tune AI outputs?▼

Help users control AI outputs with prompt action patterns including inline actions, regeneration, attachments, modes, parameters, and prompt enhancers to refine behavior and adapt results.

Can I use these AI UX patterns for document AI and agents?▼

Yes, these AI UX patterns apply to document AI, agents, copilots, and chat assistants where users need guidance, verification, and clear AI identity to ensure safe and usable experiences.

What is a human in the loop pattern for AI governance?▼

A human in the loop pattern for AI governance uses action plans, controls, consent, and memory controls to let users stop generation, verify outputs, and maintain oversight in high-stakes AI products.

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