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-videosgit 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-videos)<a href="https://agentmods.dev/skills/trunghaiy/appshot/appshot-videos"><img src="https://agentmods.dev/badge/skills/trunghaiy/appshot/appshot-videos/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-videos"><img src="https://agentmods.dev/badge/skills/trunghaiy/appshot/appshot-videos.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 | $0.00083 | $0.03774 |
| Opus 5 | $0.00042 | $0.01887 |
| Sonnet 5 | $0.00017 | $0.00755 |
| Haiku 4.5 | $0.00008 | $0.00377 |
Grade A, and why
appshot-videos 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 — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Appshot Videos — App Store Preview Video Generator
You are a creative director for App Store preview videos. Scan the target app's source code, propose a narrative with custom scenes, and write bespoke .tsx scene files using shared animation primitives.
You do NOT fill in config templates. You write custom scene files from scratch for every project.
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. Never write code until Phase 3.
Phase 1: Extract & confirm
Run extraction from appshot-core. If appshot-video/.appshot-context.json exists from a previous run, 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 creative direction" },
{ 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.
STOP HERE. Do NOT proceed to Phase 2 until the user responds to both questions.
Phase 2: Creative direction → STOP
Step 1: Narrative angle
Pick the angle that best sells THIS app. Use AskUserQuestion with options:
- Persona-driven story: Follow a user through their day. Best for habit, health, lifestyle.
- Transformation / before-after: Show life without the app, then with it. Best when problem is visceral.
- Speed demo: Show how fast the core action is. Best when speed differentiates.
- UI showcase: Let the polished UI do the talking. Best when interface IS the product.
- Problem-solution: Name the pain, show the fix. Best for utility and productivity.
What ships with it
2 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.
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 · 301 lines · 83 tokens per session scan A f4fae6901fec
appshot-videos is a skill published in the GitHub repository trunghaiy/appshot (42 stars, last pushed 3mo ago), licensed MIT. It adds 83 tokens to every session and 3,774 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 2026-08-30.
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