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 CattleZ · Agent Tool · ★ 139
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is dance-video-to-prompt safe to install? View the security audit →
dance-video-to-prompt 把 本地短视频（跳舞 / 姿态 / 变装 / 旅行打卡 / 穿搭行走等，优先 ≤10s）反推成可直接用于 AI 视频生成的结构化 Prompt。 仓库：https://github.com/CattleZ/dance-video-to-prompt 能力包含：密帧抽帧、关键帧清晰度检测与邻帧救援、音轨节奏/BPM 分析、画面事实观察、节奏卡点融合、7 段生成提示词。 看图须分析 人物身材特征、穿搭颜色与样式、拍摄场景、拍摄方法 / 运镜 / 关注重点 与面部表情。 动作清单强制含：左右肢、角度/幅度、手型、视线、面部表情（含变化）。 快速开始 输出目录默认在 （该目录不入库）。 输出模板（固定 7 段） 两个版本 两种版本 共用： 抽帧逻辑（密帧） 三阶段流程（事实 → 模板 Prompt → 校验） 同一套 7 段输出契约 text 本地视频 │ ▼ scripts/extractframes.sh ← 共用，无 API │ ├──────────── Agent/Skill 版 ────────────┐ │ Agent read
| Stars | 139 |
| Forks | 1 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 58.4386606282438/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-22 |
| Created | 2026-08-17 |
| Platforms | python |
| Est. Tokens | ~7k |
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dance-video-to-prompt is 本地短视频反推 AI 视频生成提示词：抽帧、清晰度、节奏卡点、Agent Skill. It is categorized as a Agent Tool with 139 GitHub stars.
dance-video-to-prompt is primarily written in Python.
You can find installation instructions and usage details in the dance-video-to-prompt GitHub repository at github.com/CattleZ/dance-video-to-prompt. The project has 139 stars and 1 forks, indicating an active community.
The top alternatives to dance-video-to-prompt on Agent Skills Hub include claude-plugins, tutor-skills, repren. 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: