TuyaOpenClaw: Edge-Hardware (SoC/MCU) oriented Claw

by tuya · Codex Skill · ★ 197

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How to install TuyaOpenClaw

git clone https://github.com/tuya/TuyaOpenClaw.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 63/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agenticclawclawdbothardwareopenclawsmart-hardwaretuyatuyaopen

Quick Facts

Stars197
Forks40
LanguageC
CategoryCodex Skill
LicenseApache-2.0
Quality Score63/100
Open Issues5
Last Updated2026-07-06
Created2026-03-02
Est. Tokens~18k

About TuyaOpenClaw

TuyaOpenClaw Ducky — TuyaOpen's hardware mascot — runs the Claw on every board. (Formerly known as DuckyClaw.) TuyaOpenClaw is a hardware-oriented AI agent built on the TuyaOpen C SDK. It runs a Claw-style agent loop on edge devices (Tuya T5AI, ESP32, Raspberry Pi, Linux) that communicates with users via IM channels (Telegram, Discord, Feishu, WeChat, QQ Bot) and executes MCP-style tools directly...

Compatible Skills

These tools work well together with TuyaOpenClaw for enhanced workflows:

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  • m5-paper-buddy — semantic(0.22)+complementary+rare_topics+similar_pop (47%)

TuyaOpenClaw alternative? Top 6 similar tools

Looking for a TuyaOpenClaw alternative? If you're comparing TuyaOpenClaw 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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  • milady by milady-ai · ⭐ 354

    terminally online

  • clawhost by bfzli · ⭐ 349

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  • ClawLink by CN-Syndra · ⭐ 313

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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