visual-ralph

Automate frontend UI restyling with pixel-diff verification against approved references.

Updated Jan 4, 2026
One-click install
npx skills add https://github.com/YeaChan05/Remittance --skill visual-ralph-yeachan05
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: visual-ralph
Source: https://github.com/YeaChan05/Remittance/tree/main/.codex/skills/visual-ralph
Command: npx skills add https://github.com/YeaChan05/Remittance --skill visual-ralph-yeachan05

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates frontend UI delivery by orchestrating approved references, Ralph implementation, and visual verdict evaluation.

Core Features & Use Cases

  • Visual Ralph orchestration of UI restyling across generated, static, or live references.
  • Pixel-diff driven iteration with reproducible design system tokens and components.
  • Non-runtime-commands approach; composes existing skills without app-specific assumptions.

Quick Start

Describe your UI target and run Visual Ralph to iterate until the design matches.

Frequently Asked Questions about visual-ralph

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

FAQPage Schema
How do I automate frontend UI restyling to match a design reference?

Automate frontend UI restyling by orchestrating approved references, iterative implementation, and visual verification. This Skill uses pixel-diff evidence and Visual Verdict scoring to iterate until generated, static, or live URL targets match the approved design.

What is pixel-diff driven iteration for UI delivery?

Pixel-diff driven iteration is a visual verification process that compares implemented UI against approved references. It generates reproducible design system tokens and components, using Visual Verdict scoring to measure pixel-perfect replication accuracy.

Can I use this approach to match visuals across live URLs and static files?

Yes, the orchestration supports pixel-perfect replication across generated, static, or live URL targets. It avoids app-specific assumptions, allowing you to apply UI restyling and visual verification to various frontend target types.

How does Visual Verdict scoring work for frontend design verification?

Visual Verdict scoring evaluates how accurately an implemented UI matches an approved reference. It works alongside pixel-diff evidence to provide measured QA, automating the iterative visual verification process until the frontend design matches.

Do I need runtime dependencies to run pixel-perfect UI replication?

No, this UI restyling approach uses a non-runtime-commands method and composes existing skills without requiring runtime dependencies. This avoids app-specific assumptions while orchestrating references and visual verification.