A collection of design system “reference files” published by VoltAgent, a company working on AI agent infrastructure. It analyzes the color palettes, typography, spacing, and component design principles of well-known sites such as Apple, Stripe, Figma, Linear, and Notion, and distills each one into a single Markdown file called DESIGN.md. Usage is simple: drop the DESIGN.md for the site you want into your project root. From there, coding agents like Cursor, Claude Code, and Bolt read it and write new pages and components in the same visual language. The GitHub version (awesome-design-md) is open source under the MIT license, and it was listed on Product Hunt as “Design.MD”.
When you let AI build UI, every project tends to settle into the same generic, mass-produced look. The cause is that agents have no visual criteria of their own, and DESIGN.md is a tool for supplying those criteria from the outside.
Key Features
- Well-known design systems turned into Markdown: Colors, typography, spacing, corner radii, shadows, and component behavior are written out as prose and tokens that an agent can read. What sets it apart is that it is not just a list of color codes ─ it also covers the reasoning behind each choice
- Works by simply placing the file: No installation and no dependencies. Put the file at the root of your repository and tell your agent to “follow DESIGN.md”. It is not tied to a particular framework or editor
- Broad genre coverage: AI/LLM platforms (Claude, OpenAI, Mistral), developer tools (Cursor, Vercel, Linear), design tools (Figma, Framer, Webflow), e-commerce (Shopify, Nike, Airbnb), automotive (Tesla, Ferrari, BMW), and media (Spotify, WIRED). Even 1990s-style retro sites are included
- Preview HTML included: Each entry ships a preview HTML file alongside the DESIGN.md, so you can check what the design looks like before applying it
- Requests for individual site analysis: The official site accepts requests to produce a DESIGN.md for a site that is not in the catalog. This is useful when you want your own brand guidelines translated for agents
- Starter kits and related resources: Website and mobile app starter kits, background assets, and similar material are offered alongside the catalog
Pricing
| Plan | Price | What’s included |
|---|---|---|
| GitHub version (awesome-design-md) | Free (MIT license) | Use, modify, and redistribute the DESIGN.md files in the repository freely |
| Public catalog on the official site | Free to browse | Browse design analyses on the web and obtain DESIGN.md files |
| Catalog Pass / individual analysis / starter kits | Check the official site | Access to the full catalog, analysis of a specified site, and templates |
Pricing is as of August 2026. Specific prices for the paid options (Catalog Pass, individual analysis requests, starter kits) could not be confirmed on the public pages, so please check the official site for the latest information.
Pros & Cons
✅ Pros
- Helps you escape the “seen it somewhere before” look common to AI-generated UI, and reduces the effort of re-explaining direction in words
- Because it works by just placing a file, the setup cost is close to zero. You can add it to an existing project later
- It does not care which agent you use ─ Cursor, Claude Code, Bolt, Google Stitch and others all work, so your investment survives a tool switch
- The MIT license means you can rewrite it for your own project and run it as an internal design standard
- It also works as reading material on design systems, showing what reasoning well-known sites use to settle on colors and spacing
⚠️ Cons
- These are text instructions, so how faithfully an agent follows them depends on the model and the prompt. Pixel-level matching is not something to expect
- Since you end up closely imitating the look of an existing brand, publishing the result as-is may call for care around visual identity
- The analyses do not necessarily follow along when the original site is redesigned, so contents can go stale
- What is collected are templates of “looks like a well-known site” ─ it is not suited to designing something highly original from scratch
- Prices for the paid options are hard to read off the public pages, which makes budgeting in advance difficult
Comparison with Similar Services
| Item | getdesign.md | v0 (Vercel) | Google Stitch | shadcn/ui |
|---|---|---|---|---|
| What it provides | Design guidance in Markdown | UI generation service | UI generation service | A set of components |
| How to adopt | Just place the file | Generate on the web | Generate on the web | Fetch code via CLI |
| Agent integration | Agent-agnostic | Inside the v0 environment | Inside the Stitch environment | Edit generated code directly |
| Fit with existing projects | Easy | Output must be ported | Output must be ported | Easy |
| How it steers the look | Specifies a well-known visual language | Depends on the prompt | Depends on the prompt | Adjusted via theme settings |
| Price | GitHub version is free (MIT) | Free tier + paid | Free tier available | Free (OSS) |
getdesign.md is not a service that generates UI; it sits on the side of providing the “brief” you hand to whatever does the generating. So rather than competing with the services above, it is closer to reality to think of it as something you combine with them.
Who Is It For
- Developers who have agents like Cursor or Claude Code write UI but feel the output never looks consistent
- Teams without a dedicated designer that want a lightweight mechanism for visual consistency
- Solo developers building landing pages or dashboards who want to try a direction other than off-the-shelf templates
- Non-designers who want to grasp design system thinking quickly through real examples
- Product teams that want their brand guidelines translated into a form agents can read
Summary
getdesign.md is a tool focused on exactly one thing: giving AI coding agents criteria for how things should look. The mechanism itself is plain ─ you place a single Markdown file ─ but the quality of generated UI shifts far more on whether such reference material exists than on how the prompt is worded. Since the GitHub version is published under the MIT license, a natural path is to try one file with the agent you already use, and once you can feel the difference, write a DESIGN.md tailored to your own product.