by SenseTime-Copilot · AI Tool · ★ 149
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 149 |
| Forks | 7 |
| Language | Python |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 55/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-07 |
| Created | 2026-03-30 |
| Platforms | python |
| Est. Tokens | ~8k |
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 。...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: