dembrandt is a production-grade design token extraction tool that analyzes live websites via headless Chromium (Playwright) and produces structured outputs including colors, typography, spacing, components, shadows, motion, and gradients. It supports multiple export formats: W3C DTCG tokens, Tailwind CSS v4 themes, DESIGN.md, self-contained HTML reports, PDF brand guides, and terminal display. Beyond extraction, it offers drift detection (comparing extractions over time with a 0–100 score), a GitHub Action for CI gates, and an MCP server for AI agent integration (Claude, Cursor). The architecture is modular with fault-isolated extractors, a pure-function drift engine, and a generic async job queue. While primarily an application, it includes an optional ONNX ML model for brand primary color prediction and advanced color science (OKLab, CIEDE2000, gamut mapping), giving it a hybrid character. The codebase demonstrates strong engineering practices: extensive test coverage, CI/CD pipelines, lazy browser loading, and graceful degradation across all output formatters.
This repository is a curated collection of design system analyses for over 70 brands, each documented in a standardized DESIGN.md file. The analyses reverse-engineer public websites to extract design tokens (colors, typography, spacing, components) and present them in a machine-readable YAML front matter format alongside human-readable prose sections. The repo serves as a reference dataset for design system research, AI-assisted UI generation, and cross-brand comparison. It is not a software application or a traditional data pipeline; rather, it is a hybrid content repository that blends design research with structured data extraction. The project is maintained by VoltAgent and includes a commercial layer for requesting new analyses. While the data is well-structured and consistent, the analyses are static snapshots that may drift from live sites, and some files contain placeholder markers or typos.