Borrowing it
Nothing to install: this file belongs to MohamedAbdallah-14/prompt-to-asset. 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/MohamedAbdallah-14/prompt-to-asset/main/.claude/skills/ui-mockup-prompt/SKILL.mdgit clone --depth 1 https://github.com/MohamedAbdallah-14/prompt-to-assetWrote 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/mohamedabdallah-14/prompt-to-asset/ui-mockup-prompt)<a href="https://agentmods.dev/skills/mohamedabdallah-14/prompt-to-asset/ui-mockup-prompt"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/ui-mockup-prompt/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/mohamedabdallah-14/prompt-to-asset/ui-mockup-prompt"><img src="https://agentmods.dev/badge/skills/mohamedabdallah-14/prompt-to-asset/ui-mockup-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00209 | $0.05126 |
| Opus 5 | $0.00105 | $0.02563 |
| Sonnet 5 | $0.00042 | $0.01025 |
| Haiku 4.5 | $0.00021 | $0.00513 |
Grade A, and why
ui-mockup-prompt 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 12d 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 — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ui-mockup-prompt
This skill turns a UI brief into a single paste-ready prompt for a strong-text image model (gpt-image-2, Nano Banana Pro, Ideogram 3 Turbo, Flux 2 Pro, Midjourney v7) that produces designer-quality mockups for inspiration, not pixel-exact production UI.
The output is for a working designer to riff on. They will redo the spacing, the radius, the font, the exact palette. What they need from the image is a visual direction with soul — one that isn't AI-default purple-gradient-on-white-Inter-rounded-card slop.
Four things this skill must do, in order
- Identify the surface and its job. A pricing page, a dashboard, a settings screen, an onboarding flow — each has a different job. Aesthetic commitment is constrained by what the surface must do, not chosen freely. Look the surface up in
references/surface-patterns.md. - Pick the right model. Text density, transparency need, available references, and budget all flow into a routing decision the calling agent should not have to think about.
- Compose a slot-labeled prompt in that model's specific dialect, with the universal anti-slop rules, craft-grounded design intelligence, and the surface's UX-pattern requirements baked in.
- Return the bundle: chosen model + reasoning + paste-ready prompt + multi-ref recipe (if the user has refs) + validation reminder (with surface-specific UX checks).
The prompt should resist AI defaults by construction. The model still has freedom — the skill commits to one bold aesthetic direction constrained by the surface's job and writes the prompt around it, instead of letting the model fall back to indigo + Inter + rounded cards OR to editorially-polished output that violates the page's UX fundamentals.
Why both halves matter. Visual-craft rules alone (no Inter, no purple gradient, no rounded card chrome) produce non-slop pixels. UX-pattern rules alone (comparison matrix on pricing, F-pattern on dashboards) produce functional layout. Without both, the output is either slop OR editorial slop — still slop. Iteration-1 of this skill caught the first; iteration-2 added the second after a pricing-page output rendered with magazine-grade typography but no comparison matrix, hero eating the page, and value-prop below the tiers.
What ships with it
12 files 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.
- references/anti-slop-detail.md 11 KB
- references/craft-rules-condensed.md 11 KB
- references/laws-of-ux.md 23 KB
- references/models/_skeleton.md 2.8 KB
- references/models/flux-2-pro.md 7.0 KB
- references/models/gpt-image-1.5.md 5.4 KB
- references/models/gpt-image-2.md 6.4 KB
- references/models/ideogram-3-turbo.md 5.7 KB
- references/models/midjourney-v7.md 5.1 KB
- references/models/nano-banana-pro.md 8.1 KB
- references/routing-evidence.md 5.2 KB
- references/surface-patterns.md 14 KB
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.
- 12d ago First seen · 259 lines · 209 tokens per session scan A ca42d92f0bee
ui-mockup-prompt is a skill published in the GitHub repository MohamedAbdallah-14/prompt-to-asset (19 stars, last pushed yesterday), licensed MIT. It adds 209 tokens to every session and 5,126 once invoked, about $0.0010 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.
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