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 pyang5166 · Agent Tool · ★ 51
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gbro-collage-info safe to install? View the security audit →
gbro-collage-info 半调纸拼贴风信息动画 Agent Skill。给一份口播逐字稿，AI 帮你挑出适合做成信息动画的段落，经三道确认门后，产出 1080×1920 竖屏、带拟音音轨的 mp4 动画——纯 HTML/CSS/GSAP 本机渲染（HyperFrames），不调用任何图片生成模型。 Editorial halftone paper-collage info-graphic animations from your voiceover script, rendered locally with HTML/CSS/GSAP — no image-generation models involved. English intro below. 效果 GIF 无声；实际成片是 30fps mp4，内置卡纸落位、翻面、抽出等拟音音轨。GIF 中的中文文案来自一次真实项目的逐字稿，仅作风格演示。 一次口播视频的 11 条末帧（每条动画的收帧就是一张可读海报）： 它做什么 从逐字稿里挑出"讲信息"的段落——数字冲击、流程结构、清单收敛、对比翻转、结果高光——做成同一视觉家族的信息图动画：米色纸场、卡纸剪片、单一点色、半调截图、stop-motion 定格。 工作流是三道确认门，每道门停下来等你确认，不跳门： 风格上的硬规则（详见 references/style-system.md）： 纸场底不用渐变；一件信息 = 一张卡纸剪片 一帧只有一处点色批注 + 一个出画大色块 信息只落在画面上 2/3（y ≤ 1280），底部 640px 是字幕安全区 真实截图过半调处理；没拿到截图前用抽象灰条占位，绝不画假界面 屏幕文字只用逐字稿里有的事实，不替内容编数据 动效全部对齐 10fps 定格网格（ easing），八种主动效全片不重复（详见 references/motion-grammar.md）。 安装 这是一个 Agent Skill（SKILL.md 格式），Claude Code 直接可用： bash git clone https://github.com/pyang5166/gbro-collage-info.git /.cla
| Stars | 51 |
| Forks | 7 |
| Language | CSS |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 60.8800605680142/100 |
| Last Updated | 2026-08-01 |
| Created | 2026-08-01 |
| Est. Tokens | ~16k |
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gbro-collage-info is 半调纸拼贴风信息动画 Agent Skill · Halftone paper-collage info-graphic animations from voiceover scripts (HyperFrames, no image models). It is categorized as a Agent Tool with 51 GitHub stars.
gbro-collage-info is primarily written in CSS.
You can find installation instructions and usage details in the gbro-collage-info GitHub repository at github.com/pyang5166/gbro-collage-info. The project has 51 stars and 7 forks, indicating an active community.
gbro-collage-info is released under the MIT license, making it free to use and modify according to the license terms.
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.
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