Borrowing it
Nothing to install: this file belongs to Coinyak/onchainai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Coinyak/onchainai/main/.agents/skills/visual-qa/SKILL.mdgit clone --depth 1 https://github.com/Coinyak/onchainaiWrote 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/coinyak/onchainai/visual-qa)<a href="https://agentmods.dev/skills/coinyak/onchainai/visual-qa"><img src="https://agentmods.dev/badge/skills/coinyak/onchainai/visual-qa/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/coinyak/onchainai/visual-qa"><img src="https://agentmods.dev/badge/skills/coinyak/onchainai/visual-qa.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00052 | $0.02196 |
| Opus 5.5 | $0.00021 | $0.00878 |
| Sonnet 5.5 | $0.00010 | $0.00439 |
| Haiku 4.5 | $0.00005 | $0.00220 |
Grade A, and why
visual-qa 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 1mo 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.
This is a copy
100% identical to visual-qa — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual QA
Use vision models to self-review screenshots against design intent. Catch spacing issues, alignment problems, color inconsistencies, responsive bugs, and accessibility gaps before shipping.
When to Use
- User asks to "review this design" or "check this screenshot"
- After building a page/component, before shipping
- User wants to compare implementation vs mockup/reference
- User asks "does this look right?" or "what's off about this?"
- Automated design QA step in a build workflow
Core Philosophy
- Screenshot first, then critique. Always look at the actual rendered output, not just the code.
- Be specific. "The spacing looks off" is useless. "The gap between the heading and paragraph is 32px but should be 16px based on the surrounding spacing rhythm" is useful.
- Prioritize impact. Not every pixel matters. Focus on what users will actually notice.
- Reference the intent. Compare against design tokens, mockups, or stated design goals.
How to Review
Step 1: Capture the Screenshot
Use one of these methods to get a screenshot:
Via browser tool:
browser: screenshot (captures the current page)
Via node screen capture (if available):
node: screen_record
Via Peekaboo (macOS):
exec: peekaboo screenshot
User-provided: The user may paste/attach a screenshot directly.
Step 2: Analyze with Vision
Use the image tool to analyze the screenshot:
image: [path or URL to screenshot]
prompt: "Review this UI screenshot for design quality..."
Step 3: Structured Review
Analyze the screenshot against these categories (in priority order):
Review Categories
1. Layout & Spacing
Check for:
- Consistent spacing rhythm (is everything on the spacing grid?)
- Alignment — are elements that should be aligned actually aligned?
- Padding consistency within similar components
- Container widths and max-widths
- Responsive behavior (if multiple viewport screenshots available)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 329 lines · 52 tokens per session scan A 98eca5078b4d
visual-qa is a skill published in the GitHub repository Coinyak/onchainai (1 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 2,196 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to visual-qa, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
magic-ui
Use this skill when users want to add, customize, or troubleshoot Magic UI components in React/Next.js projects. It covers component selection, shadcn registry installation (@magicui/), integration patterns, and practical quality checks for accessibility and maintainability.
kiranism-shadcn-dashboard
Guide for building features, pages, tables, forms, themes, and navigation in this Next.js 16 shadcn dashboard template. Use this skill whenever the user wants to add a new page, create a feature module, build a data table, add a form, configure navigation items, add a theme, set up RBAC access control, or work with…
sandbox
Visual HTML canvas sandbox for agent-driven UI and live previews.
omd-apply
A skill that applies a project's DESIGN.md file as visual and brand guidance for interface work. It covers components, colors, fonts, layout, copy, motion, and visual assets.
common-architecture-diagramming
Draws architecture diagrams as editable draw.io files with a fixed house style, C4 levels, evidence-tagged shapes, and optional multi-view identity checks. Use when producing a system context, container, component, deployment, data flow, sequence, state, or ERD, or redrawing an ASCII or Mermaid one.
system-design-diagramming
Draw system diagrams in the Archify visual language: a typed JSON spec rendered as dark-canvas SVG with numbered lanes, semantic node colors, masked edge labels, and a legend. Covers architecture, workflow, sequence, dataflow, and lifecycle views. Use for any design-session diagram.