Flagged: environment access. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by xzf-thu · Agent Tool · ★ 724
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is VoiceMem safe to install? View the security audit →
中文 | English 项目主页 🌐 / 技术报告 📖 / VoiceMem Utils 🤗 / VoiceMem Model Families 🤗 / ChatMem-400K 🤗 我们带来 VoiceMem，为语音模型增加最后一个组件：灵魂，让它真正越来越懂你。VoiceMem 建立在「流式双脑」架构之上，提供精准、有情感、懂人格、低延迟且最便宜的记忆服务。本仓库将「永久保持全部开源」。 快速理解 VoiceMem： 左脑：
| Stars | 724 |
| Forks | 59 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 61.0531470898688/100 |
| Open Issues | 6 |
| Last Updated | 2026-09-05 |
| Created | 2026-08-17 |
| Platforms | python |
| Est. Tokens | ~19k |
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VoiceMem is Infrastructure for the next generation of voice agents, designed to provide universal memory. It is divided into a left brain and a right brain, storing information and emotions respectively, while a . It is categorized as a Agent Tool with 724 GitHub stars.
VoiceMem is primarily written in Python. It covers topics such as ai, ai-agents, ai-tools.
You can find installation instructions and usage details in the VoiceMem GitHub repository at github.com/xzf-thu/VoiceMem. The project has 724 stars and 59 forks, indicating an active community.
VoiceMem is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to VoiceMem on Agent Skills Hub include agentic-context-engine, EverMemOS, LLM-Agents-Ecosystem-Handbook. 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: