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 AtlasCloudAI · Agent Tool · ★ 235
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-seedance-2.5-prompts-skills safe to install? View the security audit →
🎬 Awesome Seedance 2.5 Prompts + Seedance 2.5 Skill A curated library of Seedance 2.5 video prompts plus Seedance 2.5 Skill, an installable Agent Skill that improves prompts, plans and reviews storyboards when needed, and generates controllable video. It uses Seedream 5.0 Pro for storyboard images and Seedance 2.0 as the current executable video default, switching to Seedance 2.5 only when the selected provider exposes it. [Install Seedance 2.5 Skill](https://github.com/AtlasCloudAI/awesome-seedance-2.5-prompts-skills/tree/main/skills/seedance
| Stars | 235 |
| Forks | 22 |
| Language | TypeScript |
| Category | Agent Tool |
| Quality Score | 62.9583660155552/100 |
| Open Issues | 3 |
| Last Updated | 2026-10-13 |
| Created | 2026-06-15 |
| Platforms | node |
| Est. Tokens | ~26k |
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awesome-seedance-2.5-prompts-skills is 100+ curated Seedance 2.5 prompts with real video previews, plus an installable Agent Skill that optimizes prompts, creates storyboards, and generates videos via Seedance models.. It is categorized as a Agent Tool with 235 GitHub stars.
awesome-seedance-2.5-prompts-skills is primarily written in TypeScript. It covers topics such as agent-skills, ai, ai-agents.
You can find installation instructions and usage details in the awesome-seedance-2.5-prompts-skills GitHub repository at github.com/AtlasCloudAI/awesome-seedance-2.5-prompts-skills. The project has 235 stars and 22 forks, indicating an active community.
The top alternatives to awesome-seedance-2.5-prompts-skills on Agent Skills Hub include Text-To-Video-AI, sdk, vibeframe. 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: