by SpaceZephyr · Codex Skill · ★ 81
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🔒 Is space-multi-design-ppt safe to install? View the security audit →
多风格品牌 PPT 生成器 space-multi-design-ppt.skill 「同一份内容，可以长成 62 种品牌气质的演示稿」 多风格品牌 PPT 生成器（Space Multi Design PPT）是一个品牌设计风格驱动的 AI 幻灯片生成 Skill。 它把一段文章、BP、周报、产品介绍或课程内容，转成带真实品牌设计语言的演示稿。你可以指定 Apple、Notion、Claude、Stripe、Linear、Tesla 等风格，也可以让它根据内容智能推荐 5 种匹配风格，并提供第 6 个「智能匹配」选项。 它不是让 AI 随机做一套“看起来还行”的 PPT。 它会先理解内容，再选择设计系统、输出格式和页面结构。核心依赖 brand-design-md 的 62 个真实品牌规范，以及 getdesign.md 的 DESIGN.md token，让颜色、字体、字距、圆角和视觉节奏都有来源。 看效果 · 风格墙 · 安装 · 使用 · 输出格式 · 工作原理 · 诚实边界 案例展示 <img src="https://raw.githubusercontent.com/SpaceZephyr/space-multi-design-ppt/main/examples/chengzhou-coffee-claude/preview.png" al
git clone https://github.com/SpaceZephyr/space-multi-design-ppt.git ~/.codex/skills/space-multi-design-pptTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 81 |
| Forks | 4 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 55.1327376781841/100 |
| Last Updated | 2026-07-07 |
| Created | 2026-07-06 |
| Platforms | codex, python |
| Est. Tokens | ~15k |
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space-multi-design-ppt is Codex-ready brand design system slide deck skill. It is categorized as a Codex Skill with 81 GitHub stars.
space-multi-design-ppt is primarily written in Python.
The README on GitHub (github.com/SpaceZephyr/space-multi-design-ppt) gives: git clone https://github.com/SpaceZephyr/space-multi-design-ppt.git ~/.codex/skills/space-multi-design-ppt. Usage details are in the same README.
The top alternatives to space-multi-design-ppt on Agent Skills Hub include theorist. 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.
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