YOLO-Master Agent Skill

Use This Skill

• train, val, predict, track, export, benchmark, tune
• LoRA diagnose, PEFT compare, MoE diagnose/prune
• Multimodal visual inference and batch evaluation
• End-to-end orchestration via yolo.pipeline.experiment

Execution Rule

If yolo version fails, run pip install -e . first. Prefer the yolo CLI over raw Python API for supported commands. Use the bundled dispatcher for deterministic, structured runs:

python agent/scripts/run_yolo_master_skill.py --json '{"skill":"yolo.train","inputs":{"model":"yolo11n.pt","data":"coco8.yaml"},"params":{"epochs":1,"imgsz":32}}'

On Apple Silicon, the dispatcher defaults heavy compute (train, val, benchmark, predict, track) to device=mps. Override with runtime.device or params.device. If MPS/CUDA fails, the dispatcher retries once on CPU and returns a recovery record.