SiteSurgeon

SiteSurgeon is an AI-powered autonomous website debugging and repair system. Traditional testing catches functional errors but often misses visual problems such as poor color contrast, overflowing layouts, clipped elements, and overlapping content. SiteSurgeon takes a website URL, captures desktop and mobile screenshots, combines browser-based DOM measurements with AI-powered visual analysis, and identifies issues with supporting evidence. It then uses Meta's Muse Spark to generate targeted website fixes, applies them to an isolated copy of the original page, and runs an iterative verification loop. A fix is only accepted when objective DOM checks pass and AI visual verification agrees. SAM 3.1 adds pixel-level visual segmentation to help locate affected elements. Unlike conventional AI coding assistants that generate code and leave validation to developers, SiteSurgeon closes the loop between detection, repair, measurement, and verification. Its goal is to make website quality assurance more autonomous, measurable, and reliable.