appshot: Generate App Store & Google Play preview videos and screenshots from a simple TypeScript config

by trunghaiy · Claude Skill · ★ 52

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Featured in: Claude Video Editing & Remotion Skills

How to install appshot

npx skills add trunghaiy/appshot
npx skills add trunghaiy/appshot --skill appshot-videos appshot-images

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 63/100

None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsapp-marketingapp-storeasoclaude-codegoogle-playmobile-apppreview-videoremotion-reactscreenshot-generator

Quick Facts

Stars52
Forks0
LanguageTypeScript
CategoryClaude Skill
LicenseMIT
Quality Score63/100
Last Updated2026-06-06
Created2026-05-19
Platformsclaude-code, node
Est. Tokens~16k

About appshot

Appshot Generate polished App Store preview videos, Google Play preview videos, and website demo videos — from your codebase, not a video editor. Appshot is a primitives library + AI skill that acts as a creative director: it scans your project, understands your app, and generates custom scene files tailored to your product. No video editing experience required.

Compatible Skills

These tools work well together with appshot for enhanced workflows:

  • mcp-appstore — semantic(0.46)+complementary+rare_topics+same_lang+similar_pop+shared_platform (70%)
  • linkedin-content-creator — semantic(0.16)+complementary+shared_fw(react)+same_lang+similar_pop+shared_platform (58%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Claude Skill tools