菜单
NVIDIA Cosmos — open platform world models cho Physical AI: robotics, autonomous vehicles. Cosmos3-Nano (16B) + Super (64B). Text/video/action I/O. Diffusers/vLLM/NIM. OpenMDW-1.1.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yanacuti1121/Yana-AI --skill nvidia-cosmos命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Sovereign-grade safety OS for AI coding agents. 62 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.
Use when the user wants to generate or keep repository documentation up to date via OpenWiki (langchain-ai/openwiki) — an LLM-driven CLI that writes a wiki for a codebase (or a personal knowledge base from Notion/Gmail/Slack/X/web search) and keeps it fresh via a scheduled CI pull request. Examples: "set up OpenWiki for this repo", "keep the docs updated automatically", "generate an agent wiki".
Use when implementing the core AR pipeline (camera pose estimation, marker tracking, projection overlay) from first principles — not when just using ARKit/ARCore/Unity's AR framework as a black box. Triggers on: 'build augmented reality from scratch', 'marker-based AR tracking', 'camera pose estimation', 'implement fiducial marker detection', 'AR projection matrix math', 'markerless AR tracking'. Covers marker-based vs markerless tracking, pose estimation, and the projection math to overlay 3D content on a camera feed.
基于 SOC 职业分类
| name | nvidia--cosmos |
| description | NVIDIA Cosmos — open platform world models cho Physical AI: robotics, autonomous vehicles. Cosmos3-Nano (16B) + Super (64B). Text/video/action I/O. Diffusers/vLLM/NIM. OpenMDW-1.1. |
| allowed-tools | Bash, Read, Write |
| user-invocable | true |
NVIDIA Cosmos: world model platform cho Physical AI — robots và autonomous vehicles hiểu + simulate thế giới vật lý thay vì chỉ generate text.
Cosmos3-Nano (16B) — compact, multimodal understanding + world simulation
Cosmos3-Super (64B) — frontier-scale, advanced capabilities
Specialized:
Text-to-image variants
Image-to-video variants
Robot policy models
Reasoner
Input: text + vision
Output: text
Uses: world understanding, physical reasoning, task planning, autonomous decisions
→ "Is this grasp stable?" / "What happens if I push this box?"
Generator
Input: text + vision + sound + actions
Output: visual content + audio + action sequences
Uses: simulation, synthetic training data, video generation
# Diffusers (research/dev)
pip install diffusers transformers
# huggingface: nvidia/Cosmos3-Nano
# vLLM-Omni (production API)
pip install vllm
vllm serve nvidia/Cosmos3-Nano --task generate
# NIM containers (turnkey)
docker run nvcr.io/nim/nvidia/cosmos3-nano:latest
# Cosmos Framework (training + eval)
git clone https://github.com/NVIDIA/cosmos
pip install -e .
Video captioning + event detection
Embodied reasoning + physical plausibility analysis
Spatial grounding
Text-to-video + image-to-video generation
Action-conditioned simulation
Synthetic training data generation for robotics
OpenMDW-1.1 (custom NVIDIA license, not fully open-source)
https://github.com/NVIDIA/cosmos · OpenMDW-1.1 · +479⭐/week