Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/orinks/accessiweather/visual-ralphnpx skills add Orinks/AccessiWeather --skill visual-ralphgit clone --depth 1 https://github.com/Orinks/AccessiWeatherWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/orinks/accessiweather/visual-ralph)<a href="https://agentmods.dev/skills/orinks/accessiweather/visual-ralph"><img src="https://agentmods.dev/badge/skills/orinks/accessiweather/visual-ralph.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00054 | $0.01607 |
| Opus 5 | $0.00027 | $0.00804 |
| Sonnet 5 | $0.00011 | $0.00321 |
| Haiku 4.5 | $0.00005 | $0.00161 |
Grade A, and why
visual-ralph scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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-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 design critique or general frontend advice; use
$frontend-ui-uxor 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
$ralphwith$visual-verdictguidance. - 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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 154 lines · 54 tokens per session scan A 80d8b9d45c6f
visual-ralph is a skill published in the GitHub repository Orinks/AccessiWeather (24 stars, last pushed 10d ago), licensed MIT. It adds 54 tokens to every session and 1,607 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…