visual-verdict

Compare UI screenshots against reference images and output a JSON verdict.

Updated Feb 21, 2026
One-click install
npx skills add https://github.com/byonk19-svg/rt-scheduler --skill visual-verdict-byonk19-svg
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: visual-verdict
Source: https://github.com/byonk19-svg/rt-scheduler/tree/main/.codex/skills/visual-verdict
Command: npx skills add https://github.com/byonk19-svg/rt-scheduler --skill visual-verdict-byonk19-svg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quickly determine how closely a generated UI screenshot matches reference images by producing a structured, deterministic verdict that can drive the next iteration.

Core Features & Use Cases

  • Uses a strict JSON verdict with fields score, verdict, category_match, differences, suggestions, and reasoning to guide design or development edits.
  • Accepts inputs: reference_images[] and generated_screenshot to quantify visual fidelity across layouts, spacing, typography, and component styling.
  • Ideal for UI review workflows, pixel-perfect validation of dashboards, apps, or marketing pages, and for standardizing QA feedback across teams.

Quick Start

Use the generated_screenshot path and reference_images to obtain a JSON verdict that describes visual differences and suggested fixes.

Frequently Asked Questions about visual-verdict

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compare a generated UI screenshot against a reference image for pixel-perfect accuracy?

Screenshot comparison for UI quality assurance accepts reference images and a generated screenshot to produce a structured JSON verdict, quantifying visual fidelity across layouts, spacing, typography, and component styling with actionable suggestions.

What is a deterministic JSON verdict for visual QA and how does it work?

A deterministic JSON verdict outputs structured fields including score, verdict, category_match, differences, suggestions, and reasoning to identify visual fidelity gaps between a generated UI screenshot and reference images for standardized QA feedback.

Can I use screenshot comparison to validate mobile app layouts and web dashboards?

Screenshot comparison applies to UI dashboards, components, and layouts across web or mobile interfaces when pixel-perfect accuracy is required, accepting reference images and a generated screenshot to quantify visual fidelity gaps.

What is the best way to automate UI review workflows with structured visual feedback?

The best way to automate UI review workflows is using a deterministic JSON verdict from screenshot comparison, providing score, differences, and suggestions fields that programmatically drive the next design or development iteration for pixel-perfect validation.

Do I need any dependencies or specific components to run visual verdict checks?

Visual verdict checks require no dependencies or specific components; you only need to provide the generated screenshot path, reference images array, and an optional category hint to obtain the structured JSON output for pixel-diff analysis.