Flagged: opens a tunnel service. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by PatterAI · Codex Skill · ★ 1.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Patter safe to install? View the security audit →
Patter SDK About • How It Works • Documentation • Quickstart • Skills • Templates About
| Stars | 1,040 |
| Forks | 114 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.0775624540118/100 |
| Open Issues | 8 |
| Last Updated | 2026-08-24 |
| Created | 2026-04-07 |
| Platforms | python |
| Est. Tokens | ~15k |
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Looking for a Patter alternative? If you're comparing Patter 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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Explore other popular codex skill tools:
Patter is Open-source voice-AI SDK. The Vapi/Retell alternative for builders who want to own the stack. Give your AI agent a phone number in 4 lines — Python and TypeScript, MIT licensed, Twilio, Telnyx, and Pl. It is categorized as a Codex Skill with 1.0k GitHub stars.
Patter is primarily written in Python. It covers topics such as ai-agent, ai-phone-agent, hermes-agent.
You can find installation instructions and usage details in the Patter GitHub repository at github.com/PatterAI/Patter. The project has 1.0k stars and 114 forks, indicating an active community.
Patter is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Patter on Agent Skills Hub include QuickVoice, ai, clawpanel. 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: