{
  "checker": {
    "details": {
      "argv": [
        "/tmp/ym-venv/bin/python",
        "-I",
        "/tmp/ym-check/build_check.py"
      ],
      "kind": "cli",
      "needs_browser": false,
      "needs_credentials": false,
      "returncode": 0,
      "scope": "product operation",
      "stderr": "",
      "stdout": "WARNING \u26a0\ufe0f no model scale passed. Assuming scale='n'.\nYOLO-master-n summary: 442 layers, 7,546,984 parameters, 7,546,968 gradients\nOK_BUILD DetectionModel",
      "working": true
    },
    "status": "PASS"
  },
  "main_blocker": null,
  "operation": "Build YOLO-Master-n detection model from ultralytics/cfg/models/master/v0_1/det/yolo-master-n.yaml via the documented Python API (YOLO(...).info()); prints 442 layers / 7,546,984 parameters and 'OK_BUILD DetectionModel'.",
  "operation_scope": "Covers install and model construction only. Not exercised: validation/inference/training on COCO or any dataset, pretrained weights (yolo_master_n.pt not downloaded), Gradio demo, GPU/CUDA paths, flash_attn (optional, CUDA only). No MCP server is involved in this repo.",
  "outcome": "working",
  "steps": [
    "python3 -m venv /tmp/ym-venv (after apt-get install python3.12-venv)",
    "pip install --index-url https://download.pytorch.org/whl/cpu torch torchvision",
    "pip install -r requirements.txt",
    "pip install -e .  (ultralytics 8.4.101 editable)",
    "apt-get install libgl1 libglib2.0-0 (cv2 import needed libGL.so.1)",
    "python -I /tmp/ym-check/build_check.py (YOLO(yolo-master-n.yaml).info())"
  ],
  "stuck_step": null,
  "suggested_fix": null
}