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 skills add GktuOktay/ai-skills --skill image-to-codegit clone --depth 1 https://github.com/GktuOktay/ai-skillsWrote 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/gktuoktay/ai-skills/image-to-code)<a href="https://agentmods.dev/skills/gktuoktay/ai-skills/image-to-code"><img src="https://agentmods.dev/badge/skills/gktuoktay/ai-skills/image-to-code/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/gktuoktay/ai-skills/image-to-code"><img src="https://agentmods.dev/badge/skills/gktuoktay/ai-skills/image-to-code.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 | $0.00073 | $0.01329 |
| Opus 5 | $0.00036 | $0.00665 |
| Sonnet 5 | $0.00015 | $0.00266 |
| Haiku 4.5 | $0.00007 | $0.00133 |
Grade A, and why
Image to Code Conversion 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 10d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image to Code Conversion Skill
Overview
This skill defines the systematic process for analyzing static images (screenshots, design mockups) and translating them into high-quality, production-ready frontend code (HTML/CSS, React, SwiftUI, etc.). The goal is pixel-perfect accuracy, responsive behavior, and semantic structure.
Phase 1: Visual Analysis Workflow
Before writing any code, systematically break down the image.
1. Structural Layout
- Identify the Grid/Layout Model: Is it a column-based layout, a grid of cards, or a single column? (Flexbox vs. CSS Grid).
- Macro Regions: Divide the design into header, sidebar, main content area, and footer.
- Alignment & Spacing: Mentally measure the gaps. Are they consistent? (e.g., 16px, 24px, 32px gaps).
2. Component Identification
Break down regions into reusable components:
- Buttons (primary, secondary, icon-only)
- Cards
- Input fields and forms
- Badges/Tags
- Navigation items
3. Style Extraction (Educated Guessing)
- Colors: Identify the primary brand color, background colors, text colors (primary, secondary, muted), and border colors.
- Typography: Estimate font families (serif, sans-serif, monospace), weights (regular, medium, bold), and sizing hierarchy (H1 down to captions).
- Radii & Shadows: Note corner rounding (e.g., 4px subtle, 999px pill, 16px card) and the direction/softness of drop shadows.
Phase 2: Reconstruction Strategy
1. The Semantic Skeleton (HTML/JSX)
Always start by writing semantic HTML without styles.
- Use
<header>,<main>,<section>,<article>,<nav>,<aside>. - Ensure accessibility: use
<button>for actions,<a>for links, and addaria-labelsfor icon-only buttons.
<!-- Example of a good structural skeleton -->
<article class="card">
<div class="card-image-wrapper">
<img src="..." alt="..." />
</div>
<div class="card-content">
<span class="badge">Technology</span>
<h3 class="title">Understanding AI</h3>
<p class="description">A deep dive into...</p>
<div class="card-footer">
<div class="author">...</div>
<button>Read More</button>
</div>
</div>
</article>
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.
- 10d ago First seen · 124 lines · 73 tokens per session scan A 410af314e2a5
Image to Code Conversion is a skill published in the GitHub repository GktuOktay/ai-skills (2 stars, last pushed 7d ago), licensed MIT. It adds 73 tokens to every session and 1,329 once invoked, about $0.0004 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 2026-08-31.
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design-taste-frontend
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frontend-ui-engineering
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antigravity-design-expert
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top-design
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refactoring-ui
Audit and fix visual hierarchy, spacing, color, and depth in web UIs. Use when the user mentions "my UI looks off" (or amateur/unprofessional), "fix the design", "Tailwind styling", "color palette", "visual hierarchy", "design system", "spacing scale", or "component styling". Also trigger when building consistent…