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 BIAsia · Codex Skill · ★ 78
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is voxel-icon safe to install? View the security audit →
Voxel Icon The free tier of voxel-obj: a self-contained Codex Skill for generating clean, playful, low-density isometric voxel icons, plus 30 free icons from the pool. What's in this repository The expanded pool and transparent icon versions ship as one-time paid packs; the Full pack also includes the Three.js source: https://voxel-icon.vercel.app/price.html What the art Skill produces One isolated subject built from a small number of large rectilinear blocks. A fixed orthographic three-quarter camera and shared coarse base-module scale. Opaque polished face-lit acrylic with broad whole-face highlights, not edge shine. A suspended composition with weak or absent external shadow. An opaque RGB output with exact background. Optional four-frame physical-motion loops with fixed connections and real 3D pose changes. Palette modes Default
| Stars | 78 |
| Forks | 5 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 44.7258598549891/100 |
| Last Updated | 2026-08-18 |
| Created | 2026-07-31 |
| Platforms | codex, python |
| Est. Tokens | ~13k |
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voxel-icon is Voxel Icon — 30 free PNG icons plus a self-contained Codex skill for low-density isometric voxel art. It is categorized as a Codex Skill with 78 GitHub stars.
voxel-icon is primarily written in Python.
You can find installation instructions and usage details in the voxel-icon GitHub repository at github.com/BIAsia/voxel-icon. The project has 78 stars and 5 forks, indicating an active community.
The top alternatives to voxel-icon on Agent Skills Hub include theorist. 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: