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 iart-ai · Claude Skill · ★ 12
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is kinetic-typography-skills safe to install? View the security audit →
Kinetic typography skills for AI coding agents — turn text into beat-synced, animated type for social, titles, and lyric videos.
| Stars | 12 |
| Forks | 3 |
| Language | HTML |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 71.2414881444169/100 |
| Last Updated | 2026-06-22 |
| Created | 2026-06-22 |
| Platforms | claude-code |
| Est. Tokens | ~16k |
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kinetic-typography-skills is Kinetic typography skills for AI coding agents — turn text into beat-synced, animated type for social, titles, and lyric videos.. It is categorized as a Claude Skill with 12 GitHub stars.
kinetic-typography-skills is primarily written in HTML. It covers topics such as animated-text, claude-skill, kinetic-typography.
You can find installation instructions and usage details in the kinetic-typography-skills GitHub repository at github.com/iart-ai/kinetic-typography-skills. The project has 12 stars and 3 forks, indicating an active community.
kinetic-typography-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to kinetic-typography-skills on Agent Skills Hub include opus-video-skills, claude-code-settings, creativly.ai-brand-video-remotion. 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: