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miovragmiovrag/claude-skills/ai-design-patterns/SKILL.md

ai-design-patterns

Skill1 starsChanged 5 months agoNo licenceView on GitHub

Best-practice guidance for designing, building, auditing, or reviewing AI-powered interfaces and human-AI interaction patterns — covering trust-building, transparency, explainability, user control, AI onboarding, confidence and uncertainty communication, error recovery, feedback loops, progressive disclosure of AI capabilities, AI output presentation, and ethical AI design. Use this skill whenever the user is building or reviewing any interface that incorporates AI or ML — chatbots, AI assistants, recommendation systems, AI-generated content interfaces, AI search, copilot features, autocomplete driven by ML, smart suggestions, AI image generation UIs, AI writing tools, or any feature where the system makes predictions, inferences, or decisions on behalf of the user. Trigger on words like AI interface, AI UX, AI design, human-AI interaction, chatbot, conversational UI, chat interface, AI assistant, AI copilot, AI suggestions, smart suggestions, AI recommendations, trust in AI, AI transparency, explainability, XAI, explainable AI, AI confidence, uncertainty communication, AI error, AI onboarding, AI output, AI-generated content, AI writing, generative AI, LLM interface, prompt input, AI design patterns, responsible AI, ethical AI — or when a component uses ML predictions, shows AI-generated content, or requires the user to evaluate, accept, or reject AI output.

We split this skill into the rules it gives an agent

16 rules. About 0 are common, 16 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈16

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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