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 hugohe3 · Agent Tool · ★ 54.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ppt-master safe to install? View the security audit →
PPT Master — AI generates native PowerPoint from any document English | 中文 This project is kept free and open source with the support of Kimi, PackyCode, APIKEY.FUN, RunAPI, <a href="https://www.compshare.cn/coding-plan?ytag=GPUYY-gitpptm
| Stars | 54,283 |
| Forks | 4,319 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 59.2360638737596/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-14 |
| Created | 2025-12-10 |
| Platforms | python |
| Est. Tokens | ~22k |
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ppt-master is AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support. It is categorized as a Agent Tool with 54.3k GitHub stars.
ppt-master is primarily written in Python. It covers topics such as ai-agent, aippt, office.
You can find installation instructions and usage details in the ppt-master GitHub repository at github.com/hugohe3/ppt-master. The project has 54.3k stars and 4319 forks, indicating an active community.
ppt-master is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ppt-master on Agent Skills Hub include OfficeCLI, guizang-ppt-skill, AionUi. 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: