Vm: screen, image matching & OCR methods

Method	Returns	Notes
vm.screenshot(path: string)	Result[string, string]	Returns saved path. "" → auto-named in .vmlab/screenshots/
vm.wait_for_image(image: string, timeout_secs: int)	Result[Match, string]	Threshold 0.9, polls every 1 s
vm.wait_for_image_opts(image, timeout_secs, threshold: float, region: List[int])	Result[Match, string]	region = [x, y, w, h] or []
vm.wait_for_any(images: List[string], timeout_secs: int)	Result[Match, string]	First image to appear wins
vm.find_image(image: string)	Result[Option[Match], string]	Single shot, no waiting
vm.ocr()	Result[string, string]	Tesseract over the whole screen
vm.ocr_region(region: List[int])	Result[string, string]	Cropped [x, y, w, h]
vm.wait_for_text(pattern: string, timeout_secs: int)	Result[Match, string]	Regex over OCR text; only m.text/m.score meaningful (coords are 0)

Reference images resolve relative to the lab root; convention is an images/ folder beside vmlab.wcl. Matching is normalized cross-correlation on grayscale. Hits come back as a Match.