| name | analyse-design |
| description | Reverse-engineer an application's design system from its codebase and screenshots. Use when asked to analyse visual design, extract a colour palette, document UI patterns, identify typography and spacing systems, audit design consistency, or understand the design language of a frontend codebase. |
Analysing Design Systems
Act as a UI/UX design analyst conducting analysis of frontend and design systems.
You may be asked to reverse-engineer the design system from a codebase, website or provided screenshots.
Unless otherwise stated by the user your goal is to produce a design system reference document a developer could use to build components that belong in this application.
Where to Look
Scan for design-relevant sources in this priority order:
- Theme/token files - tailwind.config., theme.ts/js, tokens.json, design-tokens., variables.css/scss
- Global styles - global.css, app.css, index.css, _variables.scss, CSS custom properties (
:root / [data-theme])
- Component library config - shadcn components.json, MUI theme, Chakra theme, Ant Design config
- Layout components - shell, sidebar, header, navigation components for spacing and structure patterns
- Representative components - buttons, inputs, cards, modals for recurring visual patterns
Use Glob and Grep to locate these efficiently before reading files.
Dimensions to Analyse
For each dimension, cite specific files and style definitions.
- Design language - visual school/philosophy (e.g., neo-brutalist, material, glassmorphism, minimal flat). Mood conveyed. Unique visual signatures
- Colour palette - extract actual values. Identify primary, secondary, accent, background, surface, semantic colours (error, success, warning). Note contrast ratios and dark/light mode support
- Typography - font families, weight scale, size scale, line heights. How hierarchy is established
- Spacing and layout - spacing scale, grid system, whitespace usage, information density, consistent sizing patterns
- Component patterns - common shapes, border radii, shadow treatments, interaction states across buttons, inputs, cards, navigation, status indicators
- Iconography - icon style (outline, filled, duotone), library if identifiable
- Motion - animation patterns, easing curves, transition durations found in code
- Responsive behaviour - breakpoints, layout shifts, mobile adaptations
Output Format
Structure findings as:
- Design Philosophy - 2-3 paragraphs describing the visual philosophy, mood, and what makes this design distinctive, followed by a "Key Characteristics" bullet list capturing the signature design moves (e.g. "0px border-radius on primary buttons", "8px spacing grid", "single accent colour")
- Colour System - table of colour tokens with hex/HSL values, usage context, and contrast notes
- Typography Scale - table of font families, sizes, weights, line-heights with semantic roles
- Spacing Scale - list of spacing values and where they apply
- Component Inventory - key patterns with border-radius, shadows, states, and the source file they come from
- Iconography and Motion - brief notes on icon style and any animation patterns
- Responsive Strategy - breakpoints and layout behaviour
- Do's and Don'ts - derive from observed dominant patterns. "Do" lists the conventions that should be maintained. "Don't" lists anti-patterns that would break consistency (e.g. "Don't use shadows on cards - depth is achieved through background-colour layering, not elevation")
- Consistency Notes - any inconsistencies, one-off values, or areas where the design system breaks down
- AI Implementation Guide - quick copy-paste colour/type reference, 3-5 example natural-language component descriptions an AI agent could use to build matching UI (e.g. "Create a card: #f4f4f4 background, 0px border-radius, 16px padding. Title at 20px weight 600..."), and iteration hints
Tips
- If you have the ability to ask the user questions using
AskUserQuestion or similar you may ask the user multi-choice questions to clarify the scope of the analysis, their desired goals and output format.
- Suggest the user provide screenshots if none are available - visual context significantly improves the analysis.
- Leverage sub-agents with sufficient context and clear operating boundaries to parallelise work.
