by vigorX777 · AI Tool · ★ 260
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ppt-svg-generator safe to install? View the security audit →
PPT SVG 生成器 🎨 将 Markdown 文稿转化为精美、可编辑的 PPT 页面 ✨ 项目简介 PPT SVG 生成器 是一个 OpenCode Skill，帮助你将 Markdown 文稿快速转化为可导入 PowerPoint 的 SVG 文件。 🎯 核心特性 一键生成 - 命令一键完成全流程 智能文稿分析 - 自动拆解内容，生成结构化页面清单 多风格支持 - 5 种预设风格 + 自定义配色 + AI 智能推荐 PPT 原生兼容 - 生成的 SVG 支持「转换为形状」后二次编辑 批量生成 - 一键输出所有 PPT 页面 📐 输出规格 🚀 快速开始 前置要求 安装 OpenCode 将本项目放置于 OpenCode 的 skills 目录 依赖安装（可选，用于导出功能） 如果需要使用 命令将 SVG 导出为 PDF 或 PPTX： 这将自动安装所有依赖并下载 Chromium 浏览器（用于 PDF 渲染）。 跨平台支持：✅ macOS / ✅ Windows / ✅ Linux 💡 如果只需要生成 SVG 文件导入 PPT，无需安装这些依赖。 使用流程 ┌─────────────────────────────────────────────────────────────────┐ │ PPT SVG 生成流程 │ ├─────────────────────────────────────────────────────────────────┤ │ │ │ ⚡ 快捷方式 /ppt-quick @文稿.md --style=风格名称 │ │ ↓ 一键完成全流程，无需交互
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 | 260 |
| Forks | 23 |
| Language | HTML |
| Category | AI Tool |
| License | MIT |
| Quality Score | 59.4753623547624/100 |
| Open Issues | 3 |
| Last Updated | 2026-02-14 |
| Created | 2026-01-21 |
| Est. Tokens | ~18k |
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ppt-svg-generator is ppt-svg-generator 是一个 Skill，帮助你将 Markdown 文稿快速转化PPT 或 PDF，并支持多种预设风格选择，效果美观且可控。 使用流程参考公众号：懂点儿 AI 👇. It is categorized as a AI Tool with 260 GitHub stars.
ppt-svg-generator is primarily written in HTML.
You can find installation instructions and usage details in the ppt-svg-generator GitHub repository at github.com/vigorX777/ppt-svg-generator. The project has 260 stars and 23 forks, indicating an active community.
ppt-svg-generator is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ppt-svg-generator on Agent Skills Hub include pivotnacci, MedgeClaw, SciToolAgent. 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: