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 · ★ 5
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is text-message-video-skills safe to install? View the security audit →
Text-message animation skills for AI coding agents — turn a chat script into a scroll-stopping iMessage/WhatsApp/SMS conversation video, rendered from a messages array.
| Stars | 5 |
| Forks | 4 |
| Language | HTML |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 70.9290353325918/100 |
| Last Updated | 2026-06-22 |
| Created | 2026-06-22 |
| Platforms | claude-code |
| Est. Tokens | ~16k |
Looking for a text-message-video-skills alternative? If you're comparing text-message-video-skills with other claude skill tools, these 5 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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text-message-video-skills is Text-message animation skills for AI coding agents — turn a chat script into a scroll-stopping iMessage/WhatsApp/SMS conversation video, rendered from a messages array.. It is categorized as a Claude Skill with 5 GitHub stars.
text-message-video-skills is primarily written in HTML. It covers topics such as chat-animation, claude-skill, fake-text-video.
You can find installation instructions and usage details in the text-message-video-skills GitHub repository at github.com/iart-ai/text-message-video-skills. The project has 5 stars and 4 forks, indicating an active community.
text-message-video-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to text-message-video-skills on Agent Skills Hub include claude-code-settings, after-effects-mcp, claude-design-auditor-skill. 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: