Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/tercumantanumut/selenenpx agentmods add skills/tercumantanumut/selene/app-mockupWrote 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/tercumantanumut/selene/app-mockup)<a href="https://agentmods.dev/skills/tercumantanumut/selene/app-mockup"><img src="https://agentmods.dev/badge/skills/tercumantanumut/selene/app-mockup/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/tercumantanumut/selene/app-mockup"><img src="https://agentmods.dev/badge/skills/tercumantanumut/selene/app-mockup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00047 | $0.00743 |
| Opus 5.5 | $0.00019 | $0.00297 |
| Sonnet 5.5 | $0.00009 | $0.00149 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
app-mockup 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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
App Mockup
Use this skill when a user wants an existing screenshot wrapped in a browser or device frame.
Do use it for
- browser-framed web app screenshots
- phone, tablet, or laptop mockups for real app screens
- deterministic export workflows from terminal commands
- marketing or documentation visuals generated from existing UI screenshots
Do not use it for
- imaginary UI generation from text only
- lifestyle scenes or product photography
- diffusion/ML image editing
- claiming photoreal exports when only vector framing is requested
Renderer contract
Run the local renderer in this plugin:
npm --prefix selene-plugins/app-mockup-kit run render -- \
--input <path-or-image-url> \
--output <output.svg> \
--preset <preset>
Supported presets
browser-chromebrowser-safariiphone-14-propixel-6-proipad-promacbook-prowindowplain
Workflow
-
Identify the screenshot source.
- If the user gives a file path, use it directly.
- If the user gives a webpage URL, capture a screenshot first with browser tooling, then render the mockup.
- If the user gives an image URL that already points to a screenshot, pass it directly to the renderer.
-
Infer the right preset.
- web app or dashboard ->
browser-chromeunless Safari styling is explicitly requested - iOS mobile app ->
iphone-14-pro - Android mobile app ->
pixel-6-pro - tablet layout ->
ipad-pro - laptop hero shot ->
macbook-pro
- web app or dashboard ->
-
Render with explicit options.
- Prefer SVG output unless the user explicitly requires a raster export pipeline.
- Use descriptive output names.
- Add title, subtitle, URL label, background, padding, and shadow only when they improve the requested result.
-
Verify the artifact.
- Confirm the output file exists.
- Report the output path, preset, and notable options used.
Example commands
npm --prefix selene-plugins/app-mockup-kit run render -- \
--input ./tmp/pricing-page.png \
--output ./out/pricing-browser-mockup.svg \
--preset browser-chrome \
--url selene.so/pricing \
--background gradient:#0f172a,#2563eb \
--padding 80 \
--shadow lifted
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 · 101 lines · 47 tokens per session scan A f092b5e9469a
app-mockup is a skill published in the GitHub repository tercumantanumut/selene (172 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 743 once invoked, about $0.0002 per session on Opus 5.5. 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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