awesome-claude-design: 68 ready-to-use design system inspirations in DESIGN.md format. Drop one in, scaffold a full UI in one shot

Security audit verdict: SAFE · quality 55/100

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.

Quick Facts

About awesome-claude-design

A collection of ready-to-use DESIGN.md files that Claude Design expands into a full UI scaffold with one drop. Awesome Claude Design Upload any to Claude Design and it scaffolds a full design system (colors, type, components, preview cards, and a working UI kit) in a single shot.

Compatible Skills

These tools work well together with awesome-claude-design for enhanced workflows:

• bridge — semantic(0.39)+complementary+rare_topics+similar_pop+shared_platform (63%)
• typeui — semantic(0.55)+complementary+rare_topics+similar_pop (59%)
• uSpec — semantic(0.40)+complementary+rare_topics+similar_pop+shared_platform (58%)
• design-system-ops — semantic(0.66)+rare_topics+similar_pop+shared_platform (57%)

awesome-claude-design alternative? Top 6 similar tools

Looking for a awesome-claude-design alternative? If you're comparing awesome-claude-design with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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• awesome-design-skills by bergside · ⭐ 2.8k

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• open-codesign by OpenCoworkAI · ⭐ 8.1k

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• cursor-talk-to-figma-mcp by grab · ⭐ 7.1k

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How this security grade is produced

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:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this