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 geekjourneyx · Agent Tool · ★ 79
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-ai-video-prompts safe to install? View the security audit →
🎥 Awesome AI Video Prompting 🚀 A curated guide to mastering AI video generation prompts, techniques, and cinematic storytelling Comprehensive collection of official guides, prompt templates, cinematic language, and audio-visual synchronization techniques for Veo / Sora / Runway / Pika / Kling 📖 Quick Start • 🎬 Prompt Engineering • 🧠 Cinematic Language • 📚 Official Guides • 🔊 Audio & Visual Sync • 🎯 Best Practices • 🤝 Contributing Language: English | 中文 📋 Table of Contents Quick Start 🎬 Prompt Engineering 🧠 Cinematic Language [📚 Official Guides](#-official-guides
| Stars | 79 |
| Forks | 26 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 58.64678912023/100 |
| Open Issues | 10 |
| Last Updated | 2026-01-04 |
| Created | 2025-10-16 |
| Est. Tokens | ~3k |
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awesome-ai-video-prompts is A curated collection of AI video prompting resources, featuring official guides, prompt templates, cinematic techniques, and audio-visual synchronization methods for Veo, Sora, Runway, Pika, Kling,. It is categorized as a Agent Tool with 79 GitHub stars.
You can find installation instructions and usage details in the awesome-ai-video-prompts GitHub repository at github.com/geekjourneyx/awesome-ai-video-prompts. The project has 79 stars and 26 forks, indicating an active community.
awesome-ai-video-prompts is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-ai-video-prompts on Agent Skills Hub include lanshu-awesome-ai-video-kit, clipcat-skill, Sora-FullStack. 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: