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ai-interaction-patterns

Catalog AI interaction patterns for transparent AI UX design.

Updated Apr 2, 2026
Search Tags:#ai#trust#human-in-the-loop#interaction-design#pattern-library#ux-patterns#ai-identity
One-click install
npx skills add https://github.com/ssssssssassssss/disease-risk-classifier --skill ai-interaction-patterns-ssssssssassssss
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-interaction-patterns
Source: https://github.com/ssssssssassssss/disease-risk-classifier/tree/main/.claude/skills/25-ai-interaction-patterns
Command: npx skills add https://github.com/ssssssssassssss/disease-risk-classifier --skill ai-interaction-patterns-ssssssssassssss

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Pattern-driven design patterns help product teams craft AI experiences that are intuitive and trustworthy by providing a structured approach to AI interactions, governance, and identity.

Core Features & Use Cases

  • 60+ AI interaction patterns across six categories including Wayfinders, Prompt Actions, Tuners, Governors, Trust Builders, and Identifiers
  • Pattern selection framework with guidance on when and how to apply each pattern
  • Memory and context management guidance to sustain coherent cross-session interactions
  • Anti-patterns and governance considerations for enterprise AI UX
  • Reference documentation and implementation guidance for Kailash SDK integration

Quick Start

Ask the AI to apply the 60+ AI interaction patterns to your product's onboarding and prompt UX.

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 design solutions that guide the creation of transparent, user-friendly AI interfaces. This catalog provides 60+ patterns across categories like Wayfinders, Prompt Actions, Tuners, Trust Builders, and Identifiers to structure AI experiences.

How do I design AI onboarding and prompt UX for user trust?▼

Apply pattern-driven AI UX frameworks to onboarding and prompt management workflows. Use the catalog's Trust Builders and Prompt Actions categories to create intuitive, transparent interactions that sustain coherent cross-session memory and build user confidence.

Does this AI pattern library support Kailash SDK frontend integration?▼

Yes, the AI interaction pattern library includes reference documentation and implementation guidance designed for integration with Kailash SDK frontends, allowing product teams to apply structured patterns directly within their development environment.

When should I use human-in-the-loop governance patterns in AI interfaces?▼

Use human-in-the-loop governance patterns when building enterprise AI UX that requires oversight. The Governors category provides anti-patterns and governance considerations to ensure transparent, controlled AI interactions and mitigate risks in user-facing systems.

What is the best way to manage AI context and memory across sessions?▼

Implement memory and context management guidance from the AI interaction pattern catalog. It provides structured frameworks to sustain coherent cross-session interactions, ensuring AI identity and conversational context remain consistent for users.

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