Agent skill

Visual Ralph

by yangyuan-zhen in yangyuan-zhen/PolyWeather

[OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the…

AGPL-3.0Auto-check passedFrontend & Design

Install Visual Ralph

skills CLI
$ npx skills add yangyuan-zhen/PolyWeather --skill visual-ralph -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yangyuan-zhen/PolyWeather visual-ralph --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yangyuan-zhen/PolyWeather.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/visual-ralph .claude/skills/visual-ralph && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
visual-ralph
GitHub stars
316
Token cost
~2.3k tokens
SKILL.md length
1,039 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
AGPL-3.0

At a glance

[OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the…

  • Works in 7 steps: Ground the target repo → Establish the visual reference → Require explicit user approval → …
  • Tasks that involve Visual regression testing
  • SKILL.md covers Purpose, Use when, Do not use when and Workflow, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Visual Ralph is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Frontend & Design, covering Visual regression testing, Design systems and Frontend development. The repository describes itself as: polymarket Intelligent Weather Quant Analysis Bot. The licence is AGPL-3.0.

When your agent uses it

  • Tasks that involve Visual regression testing
  • Tasks that involve Design systems
  • Tasks that involve Frontend development

Example prompts

  • “/visual-ralph”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Ground the target repo
  2. Establish the visual reference
  3. Require explicit user approval
  4. Hand off to $ralph for implementation
  5. Use Visual Ralph verdict before every next edit
  6. Use pixel diff only as secondary debug evidence
  7. Build a reproducible design system

What it can do on your machine

Read from SKILL.md and the folder at commit 43e658b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Visual Ralph loads about 2.3k tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 1,039 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~67
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from yangyuan-zhen/PolyWeather at commit 43e658b, republished under its AGPL-3.0 licence (© yangyuan-zhen). 1,039 words, ~2,252 tokens.

Download SKILL.mdSave it as .claude/skills/visual-ralph/SKILL.md (or your agent's skills folder).
name
visual-ralph
description
[OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.

Visual Ralph Skill

Use this skill when the user wants Codex to build or restyle frontend UI through a Visual Ralph loop: an approved generated reference, static reference, or live URL-derived baseline becomes the target, Ralph implements, and Visual Verdict drives measured iteration rather than subjective description alone.

Purpose

Create a measured frontend delivery loop from either a generated reference, a static reference, or a live URL:

user description / live URL -> approved visual reference -> $ralph implementation -> Visual Ralph verdict + pixel diff -> reproducible design system.

For live URL cloning requests, Visual Ralph owns the migrated $web-clone use case. Do not route new URL-driven website cloning work to $web-clone; preserve the URL, viewport, fidelity requirements, and interaction notes inside the Visual Ralph loop.

This is an orchestration skill. It composes existing skills and must not add runtime commands, dependencies, or app-specific assumptions by itself.

Use when

  • The user describes a desired web/app UI and wants implementation, not just design advice.
  • The user provides a live URL and wants a visual implementation or clone through measured Visual Verdict iteration.
  • A generated raster mockup/reference image would make the target clearer.
  • The task needs pixel-level visual iteration with a pass/fail threshold.
  • The final result should leave reusable design tokens/components, not only a one-off screenshot match.

Do not use when

  • The user only wants repo-wide design guidance, product/design context, or a DESIGN.md source of truth; use $design or a designer lane.
  • The task is a non-visual backend/API implementation with no UI reference target.
  • The user already supplied a final static reference image and only needs comparison/fixes; hand directly to $ralph with Visual Ralph verdict guidance.
  • The requested output is a deterministic SVG/vector/code-native asset rather than a raster reference.

Workflow

1. Ground the target repo

Before stack-specific choices, inspect local evidence:

  • package manager and scripts,
  • frontend framework and routing structure,
  • styling system and design-token conventions,
  • screenshot/test tooling,
  • existing components that should be reused.

Do not hardcode React, Vue, Tailwind, Playwright, or any other stack unless the repository evidence supports it.

2. Establish the visual reference

For live URL requests, capture or document the URL-derived reference inside the Visual Ralph artifacts and carry forward viewport, content-state, and interaction constraints. Do not invoke $web-clone; that standalone skill is hard-deprecated.

Live URL reference artifacts must include:

  • source URL and permission/scope note,
  • viewport(s), route/state, and any seed/login assumptions,
  • captured baseline screenshot path or documented capture command/tool,
  • interaction parity notes for visible controls,
  • known exclusions such as backend/API/auth, personalized data, multi-page crawling, and third-party widget parity.

For generated UI concepts, use $imagegen to produce the reference from the user's UI description.

Prompt requirements:

  • classify as ui-mockup, unless another imagegen taxonomy is clearly better,
  • include viewport/aspect ratio and intended surface,
  • specify layout, hierarchy, typography direction, color mood, and any exact text,
  • forbid logos/watermarks/unrequested brand marks,
  • ask imagegen to avoid impossible UI details or unreadable text.

When running under OMX CLI/runtime and a generated reference is part of an active Ralph-style loop, queue a continuation checkpoint before invoking the built-in image tool:

bash
omx imagegen continuation <session-id> --artifact <slug-or-filename> --generated-dir "$CODEX_HOME/generated_images/<session>" --work-dir ".omx/artifacts/visual-ralph/<slug>"

This helper records .omx/state/sessions/<session>/imagegen-pending.json and uses the existing Stop-hook follow-up queue. It exists because built-in image generation may have to end the assistant turn immediately; the next Stop checkpoint should resume artifact recovery, copy the generated image into the workspace, and run the required visual QA/verdict gate instead of relying on a manual $ralph re-prompt.

For project-bound implementation, copy the approved reference into the workspace, for example under .omx/artifacts/visual-ralph/<slug>/reference.png. Never leave the implementation reference only in $CODEX_HOME/generated_images/....

3. Require explicit user approval

Stop after reference generation or URL-derived reference capture and ask the user to approve one reference image/state or request a targeted regeneration/capture adjustment.

Before approval:

  • do not start frontend implementation,
  • do not invoke $ralph,
  • do not treat a rough image as final.

After approval, the confirmed image or URL-derived baseline becomes the visual source of truth. Major design pivots, replacing the reference, or changing the design direction require an explicit user request.

Show full SKILL.md (387 more words)Show less
4. Hand off to $ralph for implementation

Invoke $ralph with:

  • the approved reference image path or URL-derived baseline artifact,
  • source URL, viewport(s), content state, and interaction parity notes for live URL tasks,
  • the user description,
  • the detected repo/frontend context,
  • exact screenshot command/viewport requirements,
  • the completion checklist below.

Ralph may iterate autonomously after approval. It should edit code, run the app, capture screenshots, and keep improving until the approved reference is matched or a real blocker exists.

5. Use Visual Ralph verdict before every next edit

For each visual iteration:

  1. Capture the current generated screenshot with recorded viewport/state.
  2. Run the Visual Ralph verdict step comparing the approved reference and generated screenshot. Use the vision agent for image understanding when needed.
  3. Treat the JSON verdict as authoritative.
  4. If score < 90, convert differences[] and suggestions[] into the next edit plan.
  5. Rerun before the next edit.

Required verdict shape: score, verdict, category_match, differences[], suggestions[], and reasoning.

6. Use pixel diff only as secondary debug evidence

When mismatch diagnosis is hard, generate a pixel diff or pixelmatch overlay to locate hotspots. Pixel diff does not replace the Visual Ralph verdict; it only helps translate visual hotspots into concrete edits.

Record final diff evidence with the reference/screenshot artifacts so the result can be audited.

7. Build a reproducible design system

The implementation is incomplete unless the visual match is encoded in repo-native reusable artifacts. Depending on the project, this may mean CSS variables, theme tokens, Tailwind config, component variants, Storybook stories, updates that align with DESIGN.md, or existing equivalents.

Capture at least the applicable:

  • colors,
  • spacing scale,
  • typography scale/weights,
  • radii,
  • shadows/elevation,
  • important component variants and states.

Prefer existing token/component patterns. Do not introduce a new design-system layer if the repo already has one that can be extended.

Completion checklist

Do not declare done until all are true:

  • Approved reference image or URL-derived reference artifact is saved in the workspace.
  • Screenshot reproduction command, viewport, route, seed/state, and output paths are documented.
  • Visual Ralph verdict final score is >= 90 against the approved reference.
  • Pixel diff or overlay evidence is recorded as secondary debug evidence.
  • Design-system tokens/components are repo-native and reusable.
  • Build/lint/test or the repo's equivalent verification passes.
  • No unapproved major design pivot occurred after reference approval.
  • Remaining visual differences, if any, are explicitly documented with rationale.

Handoff template

text
$ralph "Implement the approved frontend reference.
Reference: <workspace-reference-image-or-url-derived-artifact>
Source URL (if URL-derived): <url and permission/scope note>
Viewport/content state: <viewport, route/state, seed/login assumptions>
Interaction parity notes: <visible controls and known exclusions>
Route/surface: <route or component>
Screenshot command: <command and viewport>
Use the Visual Ralph verdict step before every next edit; pass threshold score >= 90.
Use pixel diff only as secondary debug evidence.
Extract reusable design tokens/components for colors, spacing, typography, radii, shadows, and key variants.
Run build/lint/test before completion.
Do not make major design pivots unless explicitly requested."

Task: {{ARGUMENTS}}

© yangyuan-zhen, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .codex/skills/visual-ralph of yangyuan-zhen/PolyWeather.

Open the folder on GitHubat commit 43e658b

Compare with similar skills

Visual Ralph next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Visual Ralph compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Visual Ralph this skillyangyuan-zhen/PolyWeather316—~2.3kAutomated safety check: PassAGPL-3.0
Omh Frontendrlaope/oh-my-hermes3.2k—~4kAutomated safety check: PassMIT
Design StyleCastor6/tactus3761 repos~2.1kAutomated safety check: PassApache-2.0
Avoid AI Designsunkaifei/FlyCms656—~3.5kAutomated safety check: PassMIT
Ark UIBrandon030722/ark-ui-skill266—~3.7kAutomated safety check: PassNone
Superdesignsuperdesigndev/superdesign-skill635—~4.1kAutomated safety check: PassMIT

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Questions about Visual Ralph

What does Visual Ralph do?

[OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the…. Visual Ralph is an agent skill from yangyuan-zhen/PolyWeather. [OMX] Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.

When should I use Visual Ralph?

Visual Ralph fits situations like: tasks that involve Visual regression testing; tasks that involve Design systems; tasks that involve Frontend development.

How do I install Visual Ralph in Claude Code?

Run `npx skills add yangyuan-zhen/PolyWeather --skill visual-ralph -a claude-code`. Or copy the skill folder (.codex/skills/visual-ralph in yangyuan-zhen/PolyWeather) into .claude/skills/visual-ralph in your project. Claude Code loads it when a task matches its description.

How do I install Visual Ralph in Codex?

Run `npx skills add yangyuan-zhen/PolyWeather --skill visual-ralph -a codex`. Or copy the skill folder (.codex/skills/visual-ralph in yangyuan-zhen/PolyWeather) into .agents/skills/visual-ralph in your project. Codex loads it when a task matches its description.

Can I use Visual Ralph in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yangyuan-zhen/PolyWeather --skill visual-ralph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/visual-ralph, .gemini/skills/visual-ralph, .github/skills/visual-ralph and .opencode/skills/visual-ralph in your project.

What does Visual Ralph need to run?

SKILL.md names no scripts, command-line tools or credentials: Visual Ralph is instructions for the agent only.

Does Visual Ralph access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Visual Ralph safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Visual Ralph use?

Visual Ralph is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Visual Ralph use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Visual Ralph?

Skills that share tags, products or a category with Visual Ralph: Omh Frontend (rlaope/oh-my-hermes, 3.2k stars), Design Style (Castor6/tactus, 376 stars), Avoid AI Design (sunkaifei/FlyCms, 656 stars) and Ark UI (Brandon030722/ark-ui-skill, 266 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Visual Ralph?

yangyuan-zhen (a GitHub user) maintains it in yangyuan-zhen/PolyWeather, which has 316 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on September 20, 2026.

Source: yangyuan-zhen/PolyWeather on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.