.codex-plugin/plugin.json

{
  "name": "yolo",
  "version": "0.5.1",
  "description": "Agent skills for Ultralytics YOLO and Platform: model selection, dataset annotation, training, tuning, inference, export, and deployment through the Platform web UI, the Python package, and the yolo and ul CLIs.",
  "author": {
    "name": "Ultralytics",
    "email": "hello@ultralytics.com",
    "url": "https://www.ultralytics.com"
  },
  "homepage": "https://www.ultralytics.com",
  "repository": "https://github.com/ultralytics/skills",
  "license": "AGPL-3.0",
  "keywords": [
    "ultralytics",
    "yolo",
    "computer-vision",
    "object-detection",
    "segmentation",
    "pose",
    "training",
    "annotation",
    "cloud-training",
    "platform",
    "onnx",
    "tensorrt"
  ],
  "skills": "./skills/",
  "interface": {
    "displayName": "Ultralytics YOLO",
    "shortDescription": "Train and deploy vision AI",
    "longDescription": "Ultralytics YOLO skills help Codex build computer-vision models end to end, in Ultralytics Platform or local code. Choose the right YOLO model, upload and annotate datasets, train on cloud or local GPUs, improve accuracy, and run inference, tracking, and Solutions such as object counting, then export to ONNX, TensorRT, CoreML, Core AI, OpenVINO, or NPU formats or deploy a dedicated endpoint. The skills also script Platform with the ul CLI, and they defer to your installed ultralytics version over their own tables.",
    "developerName": "Ultralytics",
    "category": "Developer Tools",
    "capabilities": ["Interactive", "Write"],
    "websiteURL": "https://www.ultralytics.com",
    "supportURL": "https://www.ultralytics.com/support",
    "privacyPolicyURL": "https://www.ultralytics.com/legal/privacy",
    "termsOfServiceURL": "https://www.ultralytics.com/legal/terms-of-service",
    "logo": "./assets/logo.svg",
    "composerIcon": "./assets/logo.svg",
    "defaultPrompt": [
      "Run yolo26n.pt on bus.jpg and show me what it detects",
      "Train yolo26n.pt on coco8 for 10 epochs and report mAP",
      "Export yolo26n.pt to ONNX and test it on bus.jpg"
    ],
    "brandColor": "#042AFF"
  }
}