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 ancoleman · Claude Skill · ★ 503
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ai-design-components safe to install? View the security audit →
Full-stack development skills for AI-assisted development with Claude What is this? A collection of 76 production-ready Claude Skills covering frontend, backend, DevOps, infrastructure, security, cloud, and AI/ML development. Skills provide Claude with domain expertise, decision frameworks, and production-ready code patterns. Documentation Full documentation: ancoleman.github.io/ai-design-components | [Skillchain Guide](https://ancoleman.github.io/ai-design-components/docs
| Stars | 503 |
| Forks | 73 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 70.8617611780662/100 |
| Open Issues | 4 |
| Last Updated | 2025-12-11 |
| Created | 2025-11-13 |
| Platforms | claude-code, python |
| Est. Tokens | ~537k |
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ai-design-components is Comprehensive UI/UX and Backend component design skills for AI-assisted development with Claude. It is categorized as a Claude Skill with 503 GitHub stars.
ai-design-components is primarily written in Python. It covers topics such as ai-design, anthropic, claude.
You can find installation instructions and usage details in the ai-design-components GitHub repository at github.com/ancoleman/ai-design-components. The project has 503 stars and 73 forks, indicating an active community.
ai-design-components is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-design-components on Agent Skills Hub include styleseed, ux-ui-agent-skills, awesome-claude-design. 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: