待翻译：Show HN: I turned Apple-style scroll-video websites into a reusable AI skill

AI 服务暂时不可用，以下为来源正文，待恢复后补全翻译。

Notifications You must be signed in to change notification settings Fork 2 Star 6 BranchesTags Open more actions menu Latest commit History 16 Commits 16 Commits Folders and files NameName Last commit message Last commit date assets assets scroll-video-website scroll-video-website LICENSE LICENSE README.md README.md Repository files navigation Turn any video into a smooth, scroll-controlled website with one Agent Skill. Install npx skills add musoyangrigor/scroll-video-website-skill --skill scroll-video-website Live Demo · Install · Usage · Features Live Demo View the full demo GIF Example Website The demo shows a simple product website made from a single video. The video fills the screen, and scrolling forward or backward smoothly moves through its frames. You can create the same kind of website with: $scroll-video-website ./media/product-demo.mp4 The skill converts the video into optimized frames and builds the responsive scroll-controlled page for you. Usage Give your agent the skill name followed by a video path: $scroll-video-website ./media/product-film.mp4 Optionally add visual direction after the path: $scroll-video-website ./media/product-film.mp4 use a dark editorial style Optimize an existing generated frame sequence interactively: $scroll-video-website optimize The command takes no arguments. The agent discovers generated sequences in the current project, measures the real assets, trial-encodes representative frames, and shows separate estimates for format, frame count, quality, and other supported settings. It then shows their combined estimated impact and asks for confirmation before rewriting anything. Features Converts video into an optimized WebP frame sequence. Scrubs smoothly in both directions with progressive frame loading. Renders a responsive, full-viewport canvas with adjacent-frame blending. Preserves the existing project stack and supports reduced-motion preferences. Builds a minimal canvas-only experience by default, or follows added design direction. Interactively optimizes existing sequences with file-specific size estimates before processing. MIT licensed. See LICENSE. Resources Readme MIT license Activity Stars 6 stars Watchers 1 watching Forks 2 forks Report repository