AIAny
AI Agent2026
Icon for item

Awesome DESIGN.md

Provides a curated collection of DESIGN.md files extracted from real websites so AI coding and design agents can generate visually consistent UIs from a single markdown file. Includes previews, extracted tokens, and ready prompts for quick agent integration.

Introduction

Design guidance is often locked in Figma files or scattered CSS; DESIGN.md flips that by encoding visual systems as plain text LLMs read well. This repository collects ready-to-drop DESIGN.md files, previews, and prompt hints so coding/design agents can produce consistent UI that maps closely to real product visuals.

What Sets It Apart
  • Real-site extractions with previews — the files are derived from public websites and include preview.html (light/dark) so agents work from production-visible tokens rather than hand-waved color lists; this reduces mismatch between generated UI and target brand.
  • Agent-focused artifacts — each entry bundles semantic color roles, typography scales, component rules and a short prompt guide, so an AI agent can consume the design doc with minimal translation effort.
  • Breadth and curation — covers multiple categories (platforms, developer tools, consumer brands) with analyzed patterns and do/don't rules; this makes it easier to prototype distinct visual languages without designing from scratch.
  • Lightweight, text-first format — because DESIGN.md is just markdown, it integrates with code projects and CI pipelines more easily than binary Figma assets, enabling programmatic UI generation.
Who it's for and trade-offs

Great fit if you want to rapidly prototype UIs with AI agents, enforce visual consistency across generated screens, or study real-world design tokens for prompt engineering. It’s especially useful for teams using coding agents or Google Stitch-style workflows.

Look elsewhere if you need authoritative, up-to-date brand assets or legal permission to reproduce a company’s identity in production — the files are extracted from public CSS and are best suited for prototyping and agent-driven generation rather than replacing an official design system. Also, extracted tokens can miss internal variants or platform-specific behavior, so expect refinement when moving to production.

Information

  • Websitegithub.com
  • OrganizationsVoltAgent, GetDesign.md
  • Published date2026/03/31

Categories

More Items

GitHub
AI Agent2026

Trains reusable natural-language 'skills' for frozen LLM agents by optimizing the skill document in text-space — using trajectory-driven edits, validation-gated updates, and deployable best_skill.md artifacts. Multi-backend, zero inference-time cost at deployment, designed for iterative, validation-led skill improvement.

Hugging Face
AI Model2026

Provides quantized GGUF weights and configs for Agents‑A1 — a 35B Mixture-of-Experts agent trained for long-horizon, tool-enabled reasoning; supports 262K-context serving and runtimes like vLLM and SGLang.

GitHub
AI Agent2026

Defines 10 design principles and reference implementations for building agent-native, token-efficient CLIs that reduce token and turn costs for AI agents; includes the TOON output format, benchmarks (browser and GitHub), and an AXI catalog of tools.