joint-agent-cli

Name: joint-agent-cli
Availability: InStock
Author: NVIDIA Omniverse

Classify articulated 3D components and generate joint topologies for USD assets.

179|21|Updated Apr 28, 2026

Search Tags:#automation #robotics #articulation #usd #3d-modeling #joint-agent

Ready to run

npx skills add https://github.com/NVIDIA-Omniverse/usd-content-agents --skill joint-agent-cli

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: joint-agent-cli
Source: https://github.com/NVIDIA-Omniverse/usd-content-agents/tree/main/.agents/skills/joint-agent-cli
Command: npx skills add https://github.com/NVIDIA-Omniverse/usd-content-agents --skill joint-agent-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, joint-agent.

What problem does it solve?

This skill automates the complex, manual process of classifying articulated components in 3D assets and generating structured joint topologies for simulation-ready USD packages.

Core Features & Use Cases

Articulated Component Classification: Uses VLM analysis to identify moving parts in robot arms, props, and mechanical assemblies.
Joint Candidate Inference: Automatically generates structured joint candidates and articulation graphs.
USD Package Publication: Produces self-contained, validated USD/USDZ files ready for downstream simulation workflows.

Quick Start

Use the joint-agent-cli skill to analyze the articulated asset located at path/to/model.usd and generate a rigged joint package.

Frequently Asked Questions about joint-agent-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate joint rigging for articulated USD assets?▼

You can automate joint rigging for articulated USD assets by using VLM-based inference to classify moving components and generate structured joint topologies. This produces validated USD packages without manual rigging.

What is automated articulation graph generation for 3D models?▼

Automated articulation graph generation for 3D models identifies moving parts in mechanical assemblies and maps their joint relationships. It uses VLM analysis to automatically generate structured joint candidates for robot arms and mechanical props.

Do I need a Linux environment to generate USD joint topologies?▼

Yes, generating USD joint topologies requires a configured Linux environment. You also need the joint-agent package, the uv dependency manager, and a valid API key for your selected model backend to run the inference.

Can I use VLM analysis to classify moving parts in mechanical assemblies?▼

Yes, you can use VLM analysis to classify moving parts in mechanical assemblies. The tool identifies articulated components in 3D assets and automatically generates structured joint candidates for downstream simulation workflows.

What's the best way to prepare robot arm 3D models for simulation?▼

The best way to prepare robot arm 3D models for simulation is to automate articulation classification and joint topology generation. This creates validated, self-contained USD files ready for downstream simulation packages.

Why does automated USD rigging require an API key?▼

Automated USD rigging requires an API key because it relies on VLM-based inference to identify articulated components. The API key authenticates requests to the selected model backend that powers the visual analysis.