The 12-skill AI UX design engine for Claude Code & GitHub Copilot — purpose-built for designing UX for AI products, agents, and experiences.
Skill Claude CodeCodex
WCAG 2.2 Level AA accessibility audit for AI product surfaces - color contrast, focus order, ARIA usage, keyboard navigation, motion/animation, reduced-motion respect, alt text, and form label association. Use when: accessibility audit, a11y review, WCAG audit, screen reader compliance, keyboard-only navigation, color…
Skill Claude CodeCodex
Design user experiences for autonomous AI agents that act on behalf of users - control panels, consent flows, action previews, audit trails, and undo mechanisms. Use when: agentic AI, autonomous agents, AI autonomy controls, agent UX, AI actions, computer use, agent consent, agent audit trail.
Skill Claude CodeCodex
Design conversational AI interfaces that feel natural, recover from failures gracefully, and build user trust through dialogue. Use when: chatbot UX, conversational UI, dialogue design, AI assistant interface, chat flow, turn-taking, AI persona voice, multi-turn context.
Skill Claude CodeCodex
Design graceful failure experiences for AI products - hallucinations, uncertainty, wrong outputs, and edge cases. Use when: AI hallucination UX, error handling for AI, uncertainty design, graceful degradation, AI failure recovery, confidence thresholds, safe fallbacks.
Skill Claude CodeCodex
Design feedback mechanisms that help AI systems learn from users - thumbs up/down, preference ranking, corrections, and human-in-the-loop escalation. Use when: RLHF UX, user feedback for AI, thumbs up down design, AI correction flow, human in the loop, feedback signal design, AI improvement loops.
Skill Claude CodeCodex
Map human-AI interaction journeys - trust arcs, capability discovery paths, autonomy progression, and AI-specific touchpoints. Use when: AI user journey, human-AI interaction mapping, trust arc mapping, AI capability discovery, AI adoption journey, AI experience map.
Skill Claude CodeCodex
Design how AI presents results across text, code, images, charts, and mixed media - response formatting, output hierarchy, and cross-modal transitions. Use when: AI output design, response formatting, AI results display, multimodal output, AI-generated content presentation, code output UX, AI visualization.
Skill Claude CodeCodex
Design onboarding experiences that help users build accurate mental models of AI capabilities, set expectations, and discover features progressively. Use when: AI onboarding, progressive disclosure for AI, capability communication, AI mental models, expectation setting, AI feature discovery, first-time AI user…
Skill Claude CodeCodex
Design AI-driven personalization that adapts interfaces to users while respecting privacy, avoiding filter bubbles, and maintaining user agency. Use when: adaptive UI, AI personalization, recommendation UX, filter bubble prevention, privacy personalization balance, algorithmic fairness UX, user preference learning.
Skill Claude CodeCodex
Design the input experience for AI products - how users craft, structure, and refine their instructions to AI systems. Use when: prompt interface, AI input design, prompt templates, prompt suggestions, context window UX, instruction design, AI input affordances, prompt engineering UX.
Skill Claude CodeCodex
Design safety experiences for AI products - content moderation UX, bias detection surfaces, harm prevention patterns, and responsible AI interfaces. Use when: AI safety UX, content moderation, responsible AI, AI bias UX, harm prevention, content filtering UX, AI refusal design, safety disclaimers.
Skill Claude CodeCodex
Design explainability interfaces that help users understand AI decisions, build calibrated trust, and verify AI outputs. Use when: AI explainability, XAI UX, confidence indicators, citation design, source attribution, trust signals, AI transparency, why did AI do this.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: