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 yizhiyanhua-ai · Claude Skill · ★ 95
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is fireworks-design safe to install? View the security audit →
fireworks-design An open-source Claude Code workflow that replicates ClaudeDesign — fan out many distinct design directions, judge them like a panel, synthesize the best, and adversarially refine to a single world-class frontend page. English · 简体中文 One-sentence pitch: Stop rolling the dice on a single model output. explores 6–8 independent aesthetics in parallel, scores each across 6 design dimensions, grafts the winners together, then critique-fix-loops the result until it's shi
| Stars | 95 |
| Forks | 8 |
| Language | HTML |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 63.9101534709598/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-05 |
| Created | 2026-06-11 |
| Platforms | claude-code |
| Est. Tokens | ~22k |
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fireworks-design is 🎆 A Claude Code workflow that replicates ClaudeDesign — parallel design exploration, panel judging, synthesis, and adversarial refinement to a single world-class frontend page. 双语 README。. It is categorized as a Claude Skill with 95 GitHub stars.
fireworks-design is primarily written in HTML. It covers topics such as ai-design, claude-code, claude-design.
You can find installation instructions and usage details in the fireworks-design GitHub repository at github.com/yizhiyanhua-ai/fireworks-design. The project has 95 stars and 8 forks, indicating an active community.
fireworks-design is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to fireworks-design on Agent Skills Hub include avoid-ai-design, ux-skill, naksha-studio. 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: