figma-expert
The figma-expert skill provides guidance for building scalable design systems and component libraries in Figma, emphasizing auto-layout foundations, variant-based components, and design tokens as variables. Use it when designing or refactoring component systems, establishing design tokens, creating developer handoff specifications, or implementing theme switching and responsive behavior in Figma.
git clone --depth 1 https://github.com/RightNow-AI/openfang /tmp/figma-expert && cp -r /tmp/figma-expert/crates/openfang-skills/bundled/figma-expert ~/.claude/skills/figma-expertSKILL.md
# Figma Expert A product designer and design systems architect with deep expertise in Figma's component system, auto-layout, prototyping, and developer handoff workflows. This skill provides guidance for building scalable design systems, creating maintainable component libraries, and ensuring smooth collaboration between designers and engineers through precise specifications and token-driven design. ## Key Principles - Build components with auto-layout from the start; it ensures consistent spacing, responsive resizing, and alignment with how CSS flexbox renders in production - Use variants and component properties to reduce component sprawl; a single button component with size, state, and icon properties replaces dozens of separate frames - Establish design tokens (colors, typography, spacing, radii) as Figma variables and reference them everywhere instead of hardcoding values - Separate styles (visual appearance) from variables (semantic tokens); variables enable theming and mode switching (light/dark, brand A/brand B) - Design with real content and edge cases; placeholder text hides layout issues that surface when actual data varies in length and complexity ## Techniques - Configure auto-layout with padding (top, right, bottom, left), gap between items, and primary axis alignment (packed, space-between) for flexible container behavior - Create component variants using the variant property panel: define axes like Size (sm, md, lg), State (default, hover, disabled), and Type (primary, secondary) - Define a type scale using Figma text styles with consistent size, weight, and line-height ratios; map them to semantic names (heading-lg, body-md, caption) - Build interactive prototypes with smart animate transitions between component variants for micro-interaction demonstrations - Use the Figma Plugin API to automate repetitive tasks: batch-renaming layers, generating color palettes, or exporting design tokens to JSON - Leverage Dev Mode for handoff: inspect spacing, export assets, and copy CSS/iOS/Android code snippets directly from the design - Structure design system files with a cover page, a changelog page, and dedicated pages per component category (buttons, inputs, navigation, feedback) ## Common Patterns - **Atomic Design Structure**: Organize the library into atoms (icons, colors, typography), molecules (inputs, badges), organisms (cards, headers), and templates (page layouts) - **Theme Switching**: Use Figma variable modes to define light and dark color sets; components reference semantic variables that resolve differently per mode - **Responsive Components**: Use auto-layout with fill-container width and min/max constraints to create components that adapt across breakpoints without separate mobile variants - **Documentation Pages**: Embed component instances alongside usage guidelines, do/don't examples, and property tables directly in the Figma file for designer self-service ## Pitfalls to Avoid - Do not use absolute positioning inside auto-layout frames unless the element genuinely needs to break out of flow; it defeats the purpose of responsive layout - Do not create one-off detached instances when a variant or property would serve the use case; detached instances become stale when the source component updates - Do not skip naming and organizing layers; engineers inspecting in Dev Mode rely on meaningful layer names to map designs to code components - Do not embed raster images at full resolution without optimizing; large assets slow down Figma file performance and create unnecessarily heavy exports
Playwright-based browser automation patterns for autonomous web interaction
Expert knowledge for AI video clipping — yt-dlp downloading, whisper transcription, SRT generation, and ffmpeg processing
Expert knowledge for AI intelligence collection — OSINT methodology, entity extraction, knowledge graphs, change detection, and sentiment analysis
Expert knowledge for the Infisical Sync Hand — Infisical API reference, vault operations, error patterns, security guidance
Expert knowledge for AI lead generation — web research, enrichment, scoring, deduplication, and report generation
Expert knowledge for AI forecasting — superforecasting principles, signal taxonomy, confidence calibration, reasoning chains, and accuracy tracking
Expert knowledge for AI deep research — methodology, source evaluation, search optimization, cross-referencing, synthesis, and citation formats
Expert knowledge for autonomous market intelligence and trading — technical analysis, risk management, Alpaca API, financial data sources