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 adityarajdigital · LLM Plugin · ★ 59
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is designmd safe to install? View the security audit →
DesignMD Production-grade design context for AI coding workflows. Extract a real design system from any production URL — colors, typography, spacing, breakpoints, motion, interaction states — and stream it as a portable your coding agent can actually read. Web · Benchmarks · CLI on npm · Examples Quick start That's the whole flow. No account, no config, no API key. The command streams a measured spec for to stdout; redirect it into a file and hand it to your AI coding agent. For repeat use, install globally: Requires Node 18+. What it does URL → Live browser measurement
| Stars | 59 |
| Forks | 5 |
| Category | LLM Plugin |
| License | MIT |
| Quality Score | 68.5296111969523/100 |
| Last Updated | 2026-05-20 |
| Created | 2026-05-12 |
| Platforms | browser, claude-code, cli |
| Est. Tokens | ~125k |
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designmd is Production-grade design context for AI coding workflows. Extract a real design system from any URL — colors, typography, spacing, breakpoints — as a portable DESIGN.md.. It is categorized as a LLM Plugin with 59 GitHub stars.
You can find installation instructions and usage details in the designmd GitHub repository at github.com/adityarajdigital/designmd. The project has 59 stars and 5 forks, indicating an active community.
designmd is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to designmd on Agent Skills Hub include brandmd, multi-cli, humanizer-ru. 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: