by senlindesign · Claude Skill · ★ 284
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/senlindesign/taste-skill ~/.claude/skills/taste
git clone https://github.com/senlindesign/taste-skill ~/.gemini/skills/taste
Taken 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.
| Stars | 284 |
| Forks | 21 |
| Language | JavaScript |
| Category | Claude Skill |
| Quality Score | 48/100 |
| Open Issues | 5 |
| Last Updated | 2026-07-07 |
| Created | 2026-05-24 |
| Platforms | browser, claude-code, node |
| Est. Tokens | ~13k |
/taste — Design DNA Extractor Reverse-engineer any website's design taste. Tokens + trade-offs — not just "what", but "why". Quick start: Clone into , install Playwright MCP, run . Full install guide below. Why? Every design extraction tool gives you tokens. "The background is #08090A. The font is Inter. The radius is 6px." That's not taste — that's a spec sheet.
These tools work well together with taste-skill for enhanced workflows:
Looking for a taste-skill alternative? If you're comparing taste-skill with other claude skill tools, these 4 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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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: