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 katipally · Codex Skill · ★ 265
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openlive safe to install? View the security audit →
OpenLive The open voice and vision layer for AI agents. Your AI can think. OpenLive gives it ears, a mouth, and eyes. Bring your own model, or talk to the coding agents you already use, with the whole voice loop running on your own machine. An open alternative to ElevenLabs Agents, Gemini Live, and OpenAI Realtime. [![Down
| Stars | 265 |
| Forks | 55 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.7048847918307/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-27 |
| Created | 2026-07-09 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~16k |
These tools work well together with openlive for enhanced workflows:
Looking for a openlive alternative? If you're comparing openlive with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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openlive is Opensource, on-device voice + vision layer for AI agents. Bring any model or coding agent; the whole speech loop (VAD, STT, TTS, barge-in) runs locally. An open alternative to ElevenLabs Agents, Gemin. It is categorized as a Codex Skill with 265 GitHub stars.
openlive is primarily written in TypeScript. It covers topics such as claude-code, cli, codex.
You can find installation instructions and usage details in the openlive GitHub repository at github.com/katipally/openlive. The project has 265 stars and 55 forks, indicating an active community.
openlive is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openlive on Agent Skills Hub include memorix, agentsys, OpenContext. 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: