RealWorldClaw empowers AI agents to sense and act in the physical world by controlling ESP32 hardware and reading real-time sensor data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install realworldclaw
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install realworldclaw using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is RealWorldClaw?
RealWorldClaw is a powerful integration designed to bridge the gap between digital AI agents and physical hardware. By utilizing this skill, developers can allow their agents to interact with the environment through ESP32-based modules, enabling capabilities like temperature monitoring, motion detection, and mechanical actuation. It serves as a critical hardware abstraction layer within the ecosystem of Openclaw Skills, allowing for seamless communication via local MQTT or cloud-based HTTP APIs.
This skill is particularly valuable for developers building autonomous smart home systems, industrial monitoring tools, or automated 3D printing setups. It provides a standardized way for AI agents to interpret physical signals and respond with precise hardware actions, effectively giving software agents a physical body to manipulate and observe the real world.
RealWorldClaw Use Cases
- Automating climate control systems based on real-time temperature and humidity readings.
- Building AI-driven security alerts using PIR motion sensors and light sensors.
- Controlling 3D printer enclosures and peripherals through relay and servo actuation.
- Managing smart lighting and visual status indicators using RGB LED controls.
- Creating autonomous hardware-in-the-loop testing environments managed by AI.
How RealWorldClaw Works
- The AI agent receives a task requiring physical interaction and triggers the RealWorldClaw skill.
- The skill parses the command and checks the local configuration for the target ESP32 device.
- A request is sent via MQTT (for low-latency local control) or HTTP (for remote access) to the device.
- The ESP32 module executes the GPIO-level action, such as toggling a relay or reading a sensor value.
- The resulting data or confirmation is sent back to the agent to inform the next step of the workflow.
RealWorldClaw Setup
To get started, install the necessary communication dependencies via pip:
pip install httpx paho-mqtt
After installation, configure your hardware modules in the config.json file found in the skill directory:
{
"api_url": "https://realworldclaw-api.fly.dev/api/v1",
"devices": [
{
"name": "my-esp32",
"ip": "192.168.x.x",
"access_code": "xxxxxxxx",
"serial": "xxxxxxxxxxxx",
"type": "esp32"
}
]
}
RealWorldClaw Data Schema & Taxonomy
RealWorldClaw organizes device interaction through a structured data manifest that defines capabilities and states. This ensures that any agent using Openclaw Skills can understand the available hardware interface.
| Component | Data Description |
|---|---|
| Sensors | Provides JSON objects containing DHT22, PIR, LDR, and soil moisture data. |
| Actuators | Accepts command strings for relay toggles, servo positions, and RGB values. |
| Rules | Stores conditional logic (e.g., temperature > 30) for edge-based automation. |
| Status | Returns connectivity health and uptime for all configured ESP32 modules. |
RealWorldClaw Advanced Features
- Support for continuous monitoring mode to track sensor fluctuations in real-time.
- Edge-level automation rules that allow hardware to react to conditions without agent latency.
- Compatibility with multiple ESP32 variants including C3 and S3 models.
- Secure device registration and management through an optional platform API.
- Multi-agent coordination for complex hardware tasks involving multiple modules.
SKILL.md
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