By tonone-ai
Audits visual designs against core principles like dominant element, visual hierarchy, typography, color usage, and accessibility, citing violations, sources, and fixes with severity levels.
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npx claudepluginhub tonone-ai/tonone --plugin form-examVisual designer — brand identity, color systems, typography, UI design, and design systems
UI/UX designer skills for wireframing, user flows, design systems, UX audits, responsive design, accessibility, and design handoff.
Design fluency for frontend development. 1 skill with 23 commands (/impeccable polish, /impeccable audit, /impeccable critique, etc.) and curated anti-pattern detection.
Design workflow for coding agents: discovery, research, strategy, inclusive design, critique, and handoff — enforced automatically
Design & UX skills: UX Research Plan, Design Critique, Accessibility Audit. Create research plans with discussion guides, critique designs using JTBD and Gestalt principles, and audit for WCAG 2.2 compliance.
Use this agent when creating user interfaces, designing components, building design systems, or improving visual aesthetics. This agent specializes in creating beautiful, functional interfaces that can be implemented quickly within 6-day sprints. Examples:\n\n<example>\nContext: Starting a new app or feature design
Design and build networking infrastructure — VPCs, subnets, DNS, load balancers, firewall rules. Use when asked to "set up networking", "VPC design", "configure DNS", "load balancer setup", "network architecture", or "firewall rules".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Implement a reusable, accessible, typed component from a design spec. Use when asked to "create a component", "build a widget", "implement this design", or "reusable UI element".
Verify observability posture — audit monitoring coverage, find blind spots, prioritize gaps. Use when asked "is monitoring sufficient", "observability review", "are we covered", or "pre-launch monitoring check".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".