by SenseTime-Copilot · AI Tool · ★ 149
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is raccoon-ppt-skill safe to install? View the security audit →
小浣熊 PPT 技能 (Raccoon PPT Skill) 为 OpenClaw 设计的远程 PPT 生成技能，主要用于“用户一句话新建一整份 PPT”，并支持继续已有任务或查询结果。 核心特性 一句话新建一整份 PPT 自动收集最小必要字段：、、、 自动轮询任务状态，无需用户反复追问进度 支持服务端补充提问并继续任务 成功后直接返回最终 PPT 下载链接 对用户隐藏 等内部实现细节 面向 OpenClaw 的设计目标 这个 skill 的目标不是让用户理解底层 PPT 编排流程，而是让 OpenClaw 在识别到“用户要新建一整份 PPT”时，自动进入一个稳定的任务工作流： 从用户自然语言中提取或追问最小输入 调用 PPT OpenAPI 创建任务 自动轮询 如遇补充问题，继续向用户追问 返回最终下载链接或失败原因 OpenClaw 侧的关键触发依赖主要来自 中的 、 和 。 环境变量 执行前需要设置： 可选设置（默认为 https://xiaohuanxiong.com）： 校验方式： 快速开始（OpenClaw 使用） 创建一个 PPT 任务 默认使用 ，前台观察约 2 分钟后返回。任务状态保存到 。 继续回答补充问题 先查找最近的待回复任务： 然后继续： 查看任务列表和进度 调试命令（可选） bash python3 scripts/main.py create-job \ --prompt "帮我做一份
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 | 149 |
| Forks | 7 |
| Language | Python |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 54.9893279152083/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-07 |
| Created | 2026-03-30 |
| Platforms | python |
| Est. Tokens | ~8k |
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raccoon-ppt-skill is an open-source ai tool by SenseTime-Copilot with 149 GitHub stars.
raccoon-ppt-skill is primarily written in Python.
You can find installation instructions and usage details in the raccoon-ppt-skill GitHub repository at github.com/SenseTime-Copilot/raccoon-ppt-skill. The project has 149 stars and 7 forks, indicating an active community.
raccoon-ppt-skill is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to raccoon-ppt-skill 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.
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