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 beshuaxian · Agent Tool · ★ 741
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is higgsfield-seedance2-jineng safe to install? View the security audit →
🌐 English / 简体中文 繁體中文 🎬 higgsfield-seedance2-jineng Seedance 2.0 × Higgsfield 技能集 | Prompt Engineering Skills Collection Higgsfield · 创建视频 Create Video · 𝕏 @higgsfield 这是什么？ What Is This? 15 个专业 Claude 技能，专为 Seedance 2.0（Higgsfield）打造。每个技能将 Claude 变成特定视频风格的提示词工程师——生成大型、详细、可直接使用的提示词，包含强力 2 秒钩子，让观众停止滑动。 15 specialized Claude skills built for Seedance 2.0 on Higgsfield. Each skill turns Claude into a prompt engineer for a specific video style — generating large, detailed, paste-ready prompts with powerful 2-second hooks that stop the scroll. 👉 立即在 Higgsfield 上创建视频 Start creating on Higgsfield 每个技能包含 What Each Skill Contains 2 秒钩子框架 / 2-Second Hook Framework — 10-12 种抓取注意力的开场模式 | 10-12 atte
| Stars | 741 |
| Forks | 150 |
| Language | Shell |
| Category | Agent Tool |
| Quality Score | 54.7468660635126/100 |
| Open Issues | 7 |
| Last Updated | 2026-04-09 |
| Created | 2026-04-09 |
| Platforms | claude-code, cli |
| Est. Tokens | ~70k |
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higgsfield-seedance2-jineng is Seedance 2.0 × Higgsfield 技能集 | 15 Claude prompt skills for AI video generation — cinematic, 3D CGI, anime, e-commerce ads, music videos & more. Each skill: 2-second hook framework, camera encyclopedi. It is categorized as a Agent Tool with 741 GitHub stars.
higgsfield-seedance2-jineng is primarily written in Shell.
You can find installation instructions and usage details in the higgsfield-seedance2-jineng GitHub repository at github.com/beshuaxian/higgsfield-seedance2-jineng. The project has 741 stars and 150 forks, indicating an active community.
The top alternatives to higgsfield-seedance2-jineng on Agent Skills Hub include playwright-skill, chinese-novelist-skill, skills. 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: