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 2noise · Agent Tool · ★ 39.9k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is ChatTTS safe to install? View the security audit →
ChatTTS A generative speech model for daily dialogue. English 한국어 Introduction [!Note] This repo contains the algorithm infrastructure and some simple examples. [!Tip] For the extended end-user products, please refer to the index repo [Awesome-ChatTTS](https://github.com/libukai/Awesome
| Stars | 39,856 |
| Forks | 4,260 |
| Language | Python |
| Category | Agent Tool |
| License | AGPL-3.0 |
| Quality Score | 69.5753556236093/100 |
| Open Issues | 60 |
| Last Updated | 2026-04-10 |
| Created | 2024-05-27 |
| Platforms | python |
| Est. Tokens | ~701k |
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ChatTTS is A generative speech model for daily dialogue.. It is categorized as a Agent Tool with 39.9k GitHub stars.
ChatTTS is primarily written in Python. It covers topics such as agent, chat, chatgpt.
You can find installation instructions and usage details in the ChatTTS GitHub repository at github.com/2noise/ChatTTS. The project has 39.9k stars and 4260 forks, indicating an active community.
ChatTTS is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to ChatTTS on Agent Skills Hub include unsloth, AstrBot, dify. 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: