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JARVIS AI Skills
by
Aly-Joseph
· GitHub ↗
· v1.0.0
2242
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3
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Install in OpenClaw
/install jarvis-skills
Description
Control robotic arms and grippers via voice or code with OpenClaw, supporting precise 6-DOF movement, force sensing, collision detection, and simulation.
README (SKILL.md)
Robotic Control Skill (OpenClaw)\r
\r
Overview\r
The Robotic Control skill integrates OpenClaw for physical robotic arm and gripper manipulation through voice commands and programmatic control.\r \r
Slug\r
robotic-control\r \r
Features\r
- Robotic arm movement (6-DOF)\r
- Gripper grab/release operations\r
- Precise positioning and orientation\r
- Force/torque sensing\r
- Collision detection and safety\r
- Action sequence execution\r
- Hardware auto-detection\r
- Simulation mode support\r \r
Implementation\r
- Module:
openclaw_control.py\r - Primary Library:
OpenClaw SDK\r - Communication: USB Serial, Ethernet, ROS\r \r
Configuration\r
from openclaw_control import init_claw, get_claw\r
\r
# Initialize claw\r
claw = init_claw()\r
\r
# Control operations\r
claw.grab(force=50.0)\r
claw.move_to(10, 20, 30)\r
claw.release()\r
```\r
\r
## Voice Commands\r
- "Jarvis, grab the object"\r
- "Jarvis, move to 10 20 30"\r
- "Jarvis, rotate 45 degrees"\r
- "Jarvis, release"\r
- "Jarvis, return to home"\r
- "Jarvis, claw status"\r
\r
## Hardware Support\r
- Universal Robots (UR)\r
- ABB Robotics\r
- KUKA\r
- Stäubli\r
- Custom embedded systems\r
\r
## Performance\r
- Reach: 2-3 meters (model-dependent)\r
- Payload: 3-500 kg (model-dependent)\r
- Precision: ±0.03-0.1 mm\r
- Speed: 1-7000 mm/s\r
- Response Time: \x3C10ms\r
\r
## Dependencies\r
- openclaw\r
- pyserial\r
- numpy\r
\r
## Author\r
Aly-Joseph\r
\r
## Version\r
2.0.0\r
\r
## Last Updated\r
2026-01-31\r
Usage Guidance
Do not install or attach this to any real robot yet. The skill package is incomplete and inconsistent: it references an implementation file (openclaw_control.py) and dependencies but those are not included. Before proceeding, ask the publisher for the missing code and a trustworthy repository link, verify the openclaw package source, confirm how network/serial credentials and IPs are supplied, and run thoroughly in a disconnected simulator or controlled test environment. If you plan to use this with physical hardware, require explicit safety checks, audited code, and deny the agent direct access to serial/network interfaces until you have vetted the implementation.
Capability Analysis
Type: OpenClaw Skill
Name: jarvis-skills
Version: 1.0.0
The skill bundle appears benign based on the provided metadata and documentation. The `SKILL.md` and `skill.json` files clearly define the purpose as robotic arm and gripper manipulation, listing appropriate dependencies (`openclaw`, `pyserial`, `numpy`) and interfaces (`grab`, `release`, `move_to`). There is no evidence of prompt injection attempts against the agent, data exfiltration, malicious execution, or other harmful behaviors in the analyzed files. The instructions and descriptions are consistent with the stated purpose of controlling a physical robot.
Capability Assessment
Purpose & Capability
The SKILL.md and skill.json describe a robotic-control module (openclaw_control.py) and hardware capabilities (USB/ETH/ROS) but no code files are included and no install spec is provided. The registry metadata at the top lists a different name/version (JARVIS AI Skills v1.0.0) than the skill.json/SKILL.md (Robotic Control / v2.0.0), and skill.json declares a homepage/repo while registry metadata reported none — these inconsistencies suggest the package is incomplete or mismatched with its claims.
Instruction Scope
Runtime instructions show example code calling init_claw(), grab(), move_to(), etc., and describe direct hardware communication (USB Serial, Ethernet, ROS). However, since the required implementation file (openclaw_control.py) is missing and there are no concrete safe-usage constraints or required network addresses/credentials declared, the instructions are incomplete and would push an agent to attempt hardware access without provenance or safeguards.
Install Mechanism
There is no install spec (instruction-only), which reduces the risk of arbitrary downloads. However, skill.json lists dependencies (openclaw, pyserial, numpy) and requiredFiles including openclaw_control.py that are not present — this mismatch is concerning because the runtime assumes local modules that aren't provided by the package.
Credentials
No environment variables, credentials, or config paths are required, yet the skill describes networked hardware (Ethernet, ROS) which typically requires IPs, authentication, or config. The absence of any declared env/config requirements is disproportionate to the claimed capability and hides where connection details or secrets would come from.
Persistence & Privilege
The skill does not request always: true and has normal autonomous-invocation settings. That is reasonable, but combined with the ability to control physical hardware (if implemented), autonomous invocation increases risk — the package itself does not request elevated system persistence or system-wide config changes.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install jarvis-skills - After installation, invoke the skill by name or use
/jarvis-skills - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the Robotic Control Skill (OpenClaw) for robotic arm and gripper control.
- Supports 6-DOF arm movement, gripper operations, collision detection, and force/torque sensing.
- Includes action sequence execution, hardware auto-detection, and simulation mode.
- Compatible with multiple industrial robot brands and custom systems.
- Provides voice command interface and example code for integration.
- Performance specifications and main dependencies documented.
Metadata
Frequently Asked Questions
What is JARVIS AI Skills?
Control robotic arms and grippers via voice or code with OpenClaw, supporting precise 6-DOF movement, force sensing, collision detection, and simulation. It is an AI Agent Skill for Claude Code / OpenClaw, with 2242 downloads so far.
How do I install JARVIS AI Skills?
Run "/install jarvis-skills" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is JARVIS AI Skills free?
Yes, JARVIS AI Skills is completely free (open-source). You can download, install and use it at no cost.
Which platforms does JARVIS AI Skills support?
JARVIS AI Skills is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created JARVIS AI Skills?
It is built and maintained by Aly-Joseph (@aly-joseph); the current version is v1.0.0.
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