analytics-metrics
Build data visualization and analytics dashboards. Use when creating charts, KPI displays, metrics dashboards, or data visualization components. Triggers on…
Build a premium cinematic landing page with mouse-scrub video hero and brand-driven narrative-arc sections. Use whenever the user provides a hero video plus a product / subject / brand and wants a landing page, promo site, product showcase, marketing page, or storytelling site.
$ npx -y skills add hoodini/ai-agents-skills --skill cinematic-scrub-landing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/cinematic-scrub-landingContext preview
The summary Claude sees to decide when to auto-load this skill.
Build a premium cinematic landing page with mouse-scrub video hero and brand-driven narrative-arc sections. Use whenever the user provides a hero video plus a product / subject / brand and wants a landing page, promo site, product showcase, marketing page, or storytelling site.
name: cinematic-scrub-landing description: Build a premium cinematic landing page with mouse-scrub video hero and brand-driven narrative-arc sections. Use whenever the user provides a hero video plus a product / subject / brand and wants a landing page, promo site, product showcase, marketing page, or storytelling site. Works for any language (RTL or LTR — Hebrew, English, Arabic, Spanish, French, Japanese, etc.) and any subject (food, tech, animals, fashion, services, SaaS, wildlife campaigns, music releases, books, real estate). The signature effect is mouse-driven video scrubbing — the hero video lives across the entire page as a fixed backdrop, and moving the mouse left-right scrubs the video timeline so the subject responds to the cursor. Below the hero, 4-5 fully-opaque sections each carry their own brand identity (color, typography emphasis, layout pattern) and walk the viewer through a narrative arc (e.g. longing → joy → nostalgia → contemplation → action). Triggers on phrases like "build a landing page from this video", "cinematic landing page", "mouse scrub hero", "video that follows the cursor", "Apple-style premium product page", "the baby video scrub thing", "narrative landing page", "scrubable hero", "golden landing template", "make a promo site for this brand", "build me a showcase page with this clip". Do NOT use for parallax frame-scrub landings where the page itself doesn't scroll (use `parallax-landing-page` instead) or for video editing / captioning workflows (use `video-edit`).
Build a premium, brand-aware landing page where the hero video responds to the mouse and the rest of the page walks the viewer through a 5-beat narrative arc. The user provides a video, optionally a logo + product photo + brand context — this skill handles palette extraction, typography selection, RTL/LTR, scaffolding, the all-keyframes video re-encode, the mouse-scrub effect, the section library, and verification.
The reference implementation lives in <https://github.com/hoodini/bamba> — an Israeli RTL site for the snack "במבה" where a baby video tracks the cursor across the whole page while 4 distinct sections below (bright yellow recipe, cream nostalgia album, dark contemplative pricing, red action finale) walk the viewer through *longing → joy → nostalgia → contemplation → action*.

Every rule in this skill was extracted from that build. The bullets in [the hard-rules section](#phase-8--hard-rules-priority-over-any-contradicting-best-practice) are ALL hard-won — they override generic "good code" defaults.
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The hero stays on top. Below it, pick 4 sections from the library, ordered to follow the narrative arc. Each is fully opaque (no video bleed-through) and has its own brand identity:
| Beat | Type | Reference | |---|---|---| | 1 — Longing | **Hero** (mouse-scrub video) |  | | 2 — Joy | **Sun** — bright primary-accent gradient, floating motif SVGs, giant ghost typography, stat cards |  | | 3 — Nostalgia | **Album** — cream paper, dotted micro-pattern, polaroid bento with real product photo |  | | 4 — Contemplation | **Roast** — dark with radial accent glows, three pricing cards each with DIFFERENT visual treatment |  | | 5 — Action | **Signal** — full-bleed strong accent (red/orange/green), massive headline + CTA, glass-contained panel |  |
For technical/SaaS brands, swap section types as needed (see the section library below) — but always end with a Signal section.
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1. **Drop assets** into a clean working directory:
2. **Confirm with the user (briefly — propose defaults, move on):**
3. **Execute the workflow below in order.** All phases are mandatory. Don't skip the ffmpeg re-encode — that's the magic that makes scrub feel buttery.
4. **Verify before reporting done.** Phase 9 has 12 checks. Run all of them.
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PRODUCT_NAME: "<e.g. במבה / Bamba / Hope the Cheetah / Acme CRM>" TAGLINE: "<the meta-message — e.g. 'it's not a snack, it's lifelong memories'>" LANGUAGE: "<he | en | ar | es | fr | ja | ...>" IS_RTL: "<true | false>" # he/ar/fa = true; everything else = false HERO_VIDEO_FILE: "<exact filename in cwd — e.g. baby2.mp4>" LOGO_FILE: "<exact filename — leave blank if none>" PRODUCT_IMAGE_FILE: "<exact filename — leave blank if none>" BRAND_CONTEXT: | <2-4 sentences: era it evokes, who the audience is, the emotional core, the visual identity (warm/cool/playful/serious). Drives palette + motifs.> PALETTE: "<optional — comma-separated hexes if overriding>" NARRATIVE_ARC: "<optional — 5 emotional beats; AI proposes if blank>"
The full text-template (with the same YAML block and prompt body) is in [`references/GOLDEN_PROMPT.md`](references/GOLDEN_PROMPT.md) — paste it into Claude with the YAML filled in when you don't have direct skill-runtime access.
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Before writing any code, output:
1. **Extracted 5-color palette**: `background` (deepest ink), `cream` (warm off-white text — NEVER `#FFFFFF`), `accent` (primary brand color), `accent2` (secondary brand color), `support` (tertiary tone). Extract from the l
🧠 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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