rt-claw — Codex Skill by zevorn

by zevorn · Codex Skill · ★ 650

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

About rt-claw

Making AI Assistants Cheap Again 中文 | English RT-Claw is an OpenClaw-inspired intelligent assistant for embedded devices. Multi-OS support via OSAL (FreeRTOS, RT-Thread, Zephyr and Linux). Build swarm intelligence with networked nodes. ESP32-S3 WiFi support adapted from MimiClaw. Deploy your own AI assistant on hardware that costs just one dollar — seamlessly integrated into your daily workflow, efficiently bridging the digital and physical worlds. <img src="images/demo.png" alt="RT-Claw Dem

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Quick Facts

Stars650
Forks48
LanguageC
CategoryCodex Skill
LicenseMIT
Quality Score63.8538910544794/100
Open Issues3
Last Updated2026-05-26
Created2026-03-11
Est. Tokens~736k

Compatible Skills

These tools work well together with rt-claw for enhanced workflows:

  • mimiclaw — semantic(0.23)+complementary+rare_topics+same_lang (47%)

rt-claw alternative? Top 6 similar tools

Looking for a rt-claw alternative? If you're comparing rt-claw 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 rt-claw?

rt-claw is Making AI Assistants Cheap Again!. It is categorized as a Codex Skill with 650 GitHub stars.

What programming language is rt-claw written in?

rt-claw is primarily written in C. It covers topics such as ai, assistant, cheap.

How do I install or use rt-claw?

You can find installation instructions and usage details in the rt-claw GitHub repository at github.com/zevorn/rt-claw. The project has 650 stars and 48 forks, indicating an active community.

What license does rt-claw use?

rt-claw is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to rt-claw?

The top alternatives to rt-claw on Agent Skills Hub include openakita, poco-agent, clawsec. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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