by dominikmartn · Claude Skill · ★ 2.8k
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git clone https://github.com/dominikmartn/nothing-design-skill.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
One of 10 tools we ran end to end on the same task for our AI Design Tools page (2026-10-10).
Our pick for one fixed identity: The same dot-matrix look both times, unlike anything else here. That is the point of it, and the limit: check the phone layout, one build scrolled sideways.
Result: One fixed identity: a dot-matrix headline, black on grey, both times. One build scrolled sideways on a phone. · shares 1.0 of 4 with the page built with no skill (fonts, accent, background) · its two builds share 4 of 4 · 6.5 of 7 page checks passed
| Stars | 2,849 |
| Forks | 165 |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 59/100 |
| Open Issues | 4 |
| Last Updated | 2026-04-01 |
| Created | 2026-04-01 |
| Platforms | browser, claude-code |
| Est. Tokens | ~16k |
Nothing Design Skill A design system skill for Claude Code inspired by Nothing's visual language. Monochrome, typographic, industrial. I kept describing the same design rules to Claude over and over — Swiss typography, OLED blacks, segmented progress bars, dot-matrix motifs. So I packaged it into a reusable skill.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: