analytics-metrics
Build data visualization and analytics dashboards. Use when creating charts, KPI displays, metrics dashboards, or data visualization components. Triggers on…
Turn any video into a cinematic scroll-driven landing page — Apple-style hero where scrolling progresses the visible frame through the video. Use when the user provides a video file and asks for "a landing page from this video", "scroll-frame website", "Apple-style scroll site",
$ npx -y skills add hoodini/ai-agents-skills --skill video-to-landing-page --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/video-to-landing-pageContext preview
The summary Claude sees to decide when to auto-load this skill.
Turn any video into a cinematic scroll-driven landing page — Apple-style hero where scrolling progresses the visible frame through the video. Use when the user provides a video file and asks for "a landing page from this video", "scroll-frame website", "Apple-style scroll site",
name: video-to-landing-page description: Turn any video into a cinematic scroll-driven landing page — Apple-style hero where scrolling progresses the visible frame through the video. Use when the user provides a video file and asks for "a landing page from this video", "scroll-frame website", "Apple-style scroll site", "hero that scrubs the video", "like the GitHub Copilot landing", or any equivalent. Extracts N evenly-spaced frames via ffmpeg, builds a self-contained HTML page with a sticky hero + JS scroll listener that swaps the visible frame as you scroll, plus headline, sections and CTA below. For YUV.AI projects, applies the yuv-design-system skill in Neon mode (pink/cyan/white, default for YUV.AI web) — Decks (purple/yellow) is reserved for slides only. For generic / non-YUV.AI projects, picks an appropriate palette per the source video. Output is one folder with `index.html` and a `frames/` directory — drop on any static host.
Build a cinematic landing page where the hero is a video playing **on scroll** instead of time — like Apple product pages or the GitHub Copilot landing. Frames are extracted from the source video and swapped as the user scrolls; below the sticky hero, normal-scroll sections carry copy and CTA.
**Default:** `~/Documents/yuv-projects/landings/<slug>/` — always save landing pages here so you can find them again. Create the parent directory if missing.
mkdir -p ~/Documents/yuv-projects/landings cd ~/Documents/yuv-projects/landings # Build <slug>/ here.
Final path: `~/Documents/yuv-projects/landings/<slug>/`. Tell the user where the landing lives at the end of every build.
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1. **Probe the source** — `ffprobe` for duration, fps, dimensions, audio. 2. **Pick frame count** — default `80`. Floor `40` (choppy if lower), ceiling `160` (heavy page). Choose by duration: ≤10s → 50, 10–30s → 80, 30–60s → 120, >60s → 160. 3. **Decide output directory** — default `~/Documents/yuv-projects/landings/<slug>/`. The `<slug>` is short, derived from the video name or the topic. Override only on explicit request. 4. **Extract frames** — run `references/extract-frames.py <source-video> <output-dir> [count]`. Outputs `output-dir/frames/f_0001.jpg`… with consistent JPG quality 82 and a max-width of 1920 (downscaled if source is larger). 5. **Copy and customise** `references/landing-template.html` into `output-dir/index.html`:
6. **Optimise frames** — the build script already scales to 1920px max-width. If the page total weight is > 12 MB, drop quality to 75 or reduce frame count. 7. **Preview** — `python -m http.server` inside the output directory and open `http://localhost:8000`. Scroll feels buttery on a decent machine. 8. **Deploy** — drop the folder on Vercel/Netlify/Cloudflare Pages. No build step needed.
| File | Purpose | | --- | --- | | `references/extract-frames.py` | ffmpeg-based frame extractor; optionally builds the full HTML in one go | | `references/landing-template.html` | Self-contained landing-page skeleton with the scroll mechanic | | `references/design-notes.md` | Typography, palette, and motion defaults |
🧠 AI Agent Skills Repository - A curated collection of specialized skills for AI coding agents (Claude Code, GitHub Copilot, Cursor, Windsurf). Created by Yuval Avidani using GitHub Copilot via VS Code Insiders.
Repo: hoodini/ai-agents-skills
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