visual-verdict

Analyze UI screenshots against reference images and output structured JSON verdicts.

Updated Apr 20, 2026
One-click install
npx skills add https://github.com/jimmi2051/oh-my-copilot --skill visual-verdict-jimmi2051
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: visual-verdict
Source: https://github.com/jimmi2051/oh-my-copilot/tree/main/plugins/omc-copilot/skills/visual-verdict
Command: npx skills add https://github.com/jimmi2051/oh-my-copilot --skill visual-verdict-jimmi2051

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Structured visual QA verdicts for screenshot-to-reference comparisons.

Core Features & Use Cases

  • Deterministic JSON verdicts that quantify visual differences and provide a clear pass/revise/fail signal.
  • Supports multiple reference images to handle layout variations and real-world UI states.
  • Outputs a strict JSON payload including score, verdict, category_match, differences, suggestions, and reasoning for automated gating.
  • Use Case: Validate a new UI against design references to drive targeted edits and ensure consistency.

Quick Start

Run this skill on a generated screenshot and the reference images to obtain a JSON verdict.

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 design references?▼

Automate visual regression testing by analyzing a generated UI screenshot against reference images to produce a structured JSON verdict. This output describes visual differences and required edits, enabling automated gating in design QA workflows.

What is a JSON visual verdict for screenshot comparison?▼

A JSON visual verdict is a structured payload that quantifies visual differences between a UI screenshot and a reference image. It enforces a fixed schema including score, verdict, category_match, differences, suggestions, and reasoning to provide a clear pass, revise, or fail signal.

How do I validate UI layout, typography, and colors across multiple screen captures?▼

Validate UI layout, typography, and colors by running a screenshot comparison skill that supports multiple reference images. It analyzes these specific styling properties across screen captures and outputs a deterministic JSON verdict detailing any visual differences and required edits.

Can I use screenshot comparison for automated gating in design QA workflows?▼

Yes, you can use screenshot comparison for automated gating by leveraging the strict JSON payload output. The deterministic score and verdict fields provide a clear pass, revise, or fail signal suitable for integrating automated visual checks into continuous integration pipelines.

Does UI testing with image diff work with multiple reference images for layout variations?▼

Yes, UI testing with image diff supports multiple reference images to handle layout variations and real-world UI states. This allows the analysis to account for different valid configurations when validating a generated UI against design references.

What's the best way to get a deterministic pass or fail signal for UI visual differences?▼

The best way to get a deterministic pass or fail signal is to use a structured visual QA tool that enforces a fixed JSON schema. It quantifies visual differences and outputs a clear verdict, ensuring consistent automated validation against design references.