What problem does it solve? Interfaces built with AI assistance often accumulate generic decorative layers, repeated template patterns, fake proof elements, and established usability defects. This Skill produces a diagnostic audit that identifies the smallest set of removals or corrections to improve an interface without prescribing a speculative redesign. ## Core Features & Use Cases - Evidence-backed findings: Every issue cites a concrete location, component, behavior, or line of copy from the inspected artifact, classified as a quality defect or slop pattern. - Removal-first recommendations: A structured removal test prioritizes subtraction over restyling, with findings ranked P0 through P3 by user impact. - Use Case: Paste a screenshot of a landing page and receive a compact report flagging stacked decorative effects, interchangeable icon-heading-description tiles, and unverifiable testimonials, each with a specific removal or correction. ## Quick Start Audit this landing page screenshot for AI design slop and give me the highest-impact removals.