Turbo-IO — not yet audited

by Turbo1123 · Codex Skill · ★ 127

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About Turbo-IO

雷鸟 iO / RayNeo iO 非官方 SDK:原生鸿蒙 HarmonyOS SDK/客户端、iOS 客户端及 iOS/Android 官方 App 扩展。自有模型、联网搜索、眼镜导航、录音研究、Codex 与 Web 预览,各平台能力以文档为准。面向开发者,仅供非商业学习研究;只提供源码,不提供 IPA/APK/HAP 或签名包。

asrbes2800codexiosrayneorayneo-iosmart-glassesswiftunofficial-sdk

Quick Facts

Stars127
Forks40
LanguageSwift
CategoryCodex Skill
Quality Score50.5410463457025/100
Open Issues3
Last Updated2026-09-18
Created2026-09-08
Platformsbrowser, codex
Est. Tokens~15k

Compatible Skills

These tools work well together with Turbo-IO for enhanced workflows:

  • Pepper — semantic(0.32)+complementary+same_lang+similar_pop (56%)
  • Lingua — semantic(0.30)+complementary+same_lang+similar_pop (56%)

Turbo-IO alternative? Top 6 similar tools

Looking for a Turbo-IO alternative? If you're comparing Turbo-IO 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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Frequently Asked Questions

What is Turbo-IO?

Turbo-IO is 雷鸟 iO / RayNeo iO 非官方 SDK:原生鸿蒙 HarmonyOS SDK/客户端、iOS 客户端及 iOS/Android 官方 App 扩展。自有模型、联网搜索、眼镜导航、录音研究、Codex 与 Web 预览,各平台能力以文档为准。面向开发者,仅供非商业学习研究;只提供源码,不提供 IPA/APK/HAP 或签名包。. It is categorized as a Codex Skill with 127 GitHub stars.

What programming language is Turbo-IO written in?

Turbo-IO is primarily written in Swift. It covers topics such as asr, bes2800, codex.

How do I install or use Turbo-IO?

You can find installation instructions and usage details in the Turbo-IO GitHub repository at github.com/Turbo1123/Turbo-IO. The project has 127 stars and 40 forks, indicating an active community.

What are the best alternatives to Turbo-IO?

The top alternatives to Turbo-IO on Agent Skills Hub include OpenVision, claude-code-apple-skills, FantasyPremierLeague. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools