No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by bergside · Codex Skill · ★ 2.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is design-md-chrome safe to install? View the security audit →
TypeUI DESIGN.md Extractor (Chrome Extension) This Chrome extension extract styles and information from any given site and generates a or file that you can use with tools such as Google Stitch, Claude Code, Codex, and others to build websites with a given design system blueprint. The file is based on the open-source TypeUI DESIGN.md format. Getting started Load the extension in Chrome: Open Enable Developer mode Click Load unpacked Select this project folder Curated design skills Check out curated design systems at typeui.sh/design-skills. Available actions Generated file structure The generated markdown follows this structure: What it do
| Stars | 2,867 |
| Forks | 312 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.7290615594978/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-25 |
| Created | 2026-04-14 |
| Platforms | browser, claude-code, codex, gemini, node |
| Est. Tokens | ~4k |
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design-md-chrome is Chrome extension to extract styles from any website and generate DESIGN.md files and design skills for AI based on TypeUI. It is categorized as a Codex Skill with 2.9k GitHub stars.
design-md-chrome is primarily written in JavaScript. It covers topics such as ai, chrome, chrome-extension.
You can find installation instructions and usage details in the design-md-chrome GitHub repository at github.com/bergside/design-md-chrome. The project has 2.9k stars and 312 forks, indicating an active community.
design-md-chrome is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to design-md-chrome on Agent Skills Hub include nanobrowser, ChatGPT-Shortcut, open-codesign. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: