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 joeseesun · Codex Skill · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qiaomu-icon-generator safe to install? View the security audit →
qiaomu-icon-generator 设计网站 favicon、iOS App 图标或工具品牌入口时，最难的常常不是“生成一张图”，而是一次拿到可比较的方向、让用户选中、再导出到 Web 和 iOS 真实可用的尺寸。 Generate comparable app-icon directions, let the user choose, then export real Web and iOS icon assets. 中文 | English 已验证: npx skills add joeseesun/qiaomu-ic
| Stars | 55 |
| Forks | 6 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.2431946039928/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-21 |
| Created | 2026-06-20 |
| Platforms | browser, codex, python |
| Est. Tokens | ~15k |
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qiaomu-icon-generator is 生成可比较的 Web/iOS 图标候选并导出真实资产 | Generate comparable Web/iOS icon candidates and export real assets.. It is categorized as a Codex Skill with 55 GitHub stars.
qiaomu-icon-generator is primarily written in Python. It covers topics such as agent-skill, ai-workflow, app-icons.
You can find installation instructions and usage details in the qiaomu-icon-generator GitHub repository at github.com/joeseesun/qiaomu-icon-generator. The project has 55 stars and 6 forks, indicating an active community.
qiaomu-icon-generator is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to qiaomu-icon-generator on Agent Skills Hub include frontend-design, kaggle-skill, deepcontext-mcp. 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: