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 CaliCastle · Agent Tool · ★ 93
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is skills safe to install? View the security audit →
Skills A collection of Agent Skills by Cali Castle. Currently includes Signal Geometry and Chalk Logic. Signal Geometry Signal Geometry is an Agent Skill for turning one concept into a sparse abstract illustration or poster. It uses precise geometry, quiet matte fields, restrained contrast, and one legible spatial event. Install Using npm: Using pnpm: Use Invoke the skill explicitly with : For a prompt without rendering: Output Rendered work includes the accepted image, its exact final prompt, and the complete composition recipe. Prompt-only mode returns the prompt and recipe without generating an image. Requirements Prompt-only mode works without image tools. Rendered
| Stars | 93 |
| Forks | 2 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66.4815083123889/100 |
| Last Updated | 2026-07-24 |
| Created | 2026-07-23 |
| Est. Tokens | ~16k |
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skills is A collection of Agent Skills by Cali Castle.. It is categorized as a Agent Tool with 93 GitHub stars.
You can find installation instructions and usage details in the skills GitHub repository at github.com/CaliCastle/skills. The project has 93 stars and 2 forks, indicating an active community.
skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skills on Agent Skills Hub include LabArt, canvas-mcp, TArt. 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: