visual-verdict

Name: visual-verdict
Availability: InStock
Author: gtpgg1013

Compare generated UI screenshots with reference images to produce a deterministic JSON verdict.

Updated Mar 21, 2026

Search Tags:#quality-assurance #screenshot #design-review #visual-regression #ui-evaluation #visual-verdict

Ready to run

npx skills add https://github.com/gtpgg1013/claude-skills-collection --skill visual-verdict-gtpgg1013

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: visual-verdict
Source: https://github.com/gtpgg1013/claude-skills-collection/tree/main/skills/agents/visual-verdict
Command: npx skills add https://github.com/gtpgg1013/claude-skills-collection --skill visual-verdict-gtpgg1013

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enable deterministic evaluation of visual UI fidelity by comparing a generated screenshot to reference images and returning a strict JSON verdict that guides the next iteration.

Core Features & Use Cases

Deterministic pass/fail assessments for UI screenshots against reference images
JSON-driven outputs suitable for automation in design QA and regression testing
Use Case: When validating layout, spacing, and typography across UI screens during design reviews and rework cycles.

Quick Start

Compare your latest UI screenshot with one or more reference images to obtain a structured JSON verdict for the next edit.

Frequently Asked Questions about visual-verdict

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

FAQPage Schema

How do I automate visual regression testing for UI screenshots against reference images?▼

Visual regression testing for UI screenshots is automated by comparing generated screenshots against reference images to produce a deterministic JSON verdict. This structured output includes a score, pass/fail status, category match status, and specific differences to guide the next UI iteration.

What is a deterministic JSON verdict in UI evaluation and how does it work?▼

A deterministic JSON verdict in UI evaluation is a strict, structured output generated by comparing a current UI screenshot to reference images. It removes subjective human judgment by returning a score, pass/fail assessment, category match status, and actionable suggestions for design rework.

Can I use screenshot comparison for design QA during UI iteration cycles?▼

Screenshot comparison supports design QA during UI iteration cycles by validating layout, spacing, and typography against reference renders. It outputs a structured JSON verdict containing a score, category match status, and specific differences to directly inform necessary design edits.

What inputs are required to perform a UI evaluation with screenshot comparison?▼

Performing a UI evaluation requires inputs of one or more reference images and a single generated screenshot. The tool compares these inputs to evaluate visual fidelity and outputs a strict JSON verdict detailing differences, suggestions, and a pass/fail score.

Does automated screenshot comparison work for evaluating layout and typography differences?▼

Automated screenshot comparison works effectively for evaluating layout and typography differences by comparing current renders to reference images. It identifies specific visual discrepancies and returns them within a deterministic JSON verdict to guide corrections and rework.