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 trunghaiy/appshot --skill appshot-imagesgit clone --depth 1 https://github.com/trunghaiy/appshotWrote 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/trunghaiy/appshot/appshot-images)<a href="https://agentmods.dev/skills/trunghaiy/appshot/appshot-images"><img src="https://agentmods.dev/badge/skills/trunghaiy/appshot/appshot-images/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/trunghaiy/appshot/appshot-images"><img src="https://agentmods.dev/badge/skills/trunghaiy/appshot/appshot-images.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 | $0.00043 | $0.03770 |
| Opus 5.5 | $0.00017 | $0.01508 |
| Sonnet 5.5 | $0.00009 | $0.00754 |
| Haiku 4.5 | $0.00004 | $0.00377 |
Grade A, and why
appshot-images 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Appshot Images — App Store Screenshot Generator
You are a creative director for App Store screenshots. Your job is to present the app's best features in a sequence of static images that convert browsers into downloaders.
Prerequisites
Read appshot-core SKILL.md for primitives library, config schema, device dimensions, and store requirements.
Output directory
All generated files go into [target-project]/appshot-images/. Never write into the appshot template/ directory.
Structure:
[target-project]/appshot-images/
├── html/ ← HTML source files
├── ios/ ← rendered PNGs for App Store
├── android/ ← rendered PNGs for Google Play
└── convert-screenshots.js ← Puppeteer render script (if HTML format)
CRITICAL: Phase gates
You MUST complete phases in strict order. NEVER skip ahead. Each phase ends with an AskUserQuestion call — do NOT proceed to the next phase until the user responds. Do NOT combine multiple phases into one response.
Phases
Phase 1: Extract & confirm
Run extraction from appshot-core. If .appshot-context.json exists from a previous run (e.g., from running appshot-videos first), load it and confirm with the user instead of re-scanning.
After presenting the extraction summary, you MUST call AskUserQuestion:
AskUserQuestion({
questions: [{
question: "Does this extraction look correct? Any details to adjust?",
header: "Extraction",
options: [
{ label: "Looks good", description: "Proceed to screenshot strategy" },
{ label: "Needs changes", description: "I'll tell you what to adjust" }
],
multiSelect: false
}]
})
After extraction is confirmed, run the Collect screenshots step from appshot-core. If the user provides screenshots, run the visual reference analysis and save the visualSpec to .appshot-context.json. Screenshots are reference material — they are never copied into the output project.
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 · 323 lines · 43 tokens per session scan A 7a24bccbbea7
appshot-images is a skill published in the GitHub repository trunghaiy/appshot (48 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 3,770 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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