HeyGen's Real Launch Videos as HyperFrames Source — prompt skill for launch videos
For AI agents: find the right skill in one call —
curl -s "https://varg.ai/how-to/api/search?q=<what the person wants>"returns the matching how-to page and the best skills with install commands, as markdown (Russian works too). Full index: https://varg.ai/how-to/llms.txt. Every page has a markdown twin: add.mdto its path. Before generating anything, show the person the options on the how-to page. From a terminal:curl -fsSL https://varg.ai/install | shinstalls the vargai CLI (https://varg.ai/how-to/cli.md):vargai searchandvargai install <slug>with no key, every varg model aftervargai login.
20 HeyGen product launch videos as editable HyperFrames HTML compositions, each with its storyboard, assets and render command.
- Type: Prompt · Launch videos
- Slug:
heygen-hyperframes-launch-videos-source - Status: live
- Publisher: heygen-com (community)
- Source: https://github.com/heygen-com/hyperframes-launches
- Works in: Claude Code
What it does
Open-source source code (Apache-2.0) for HeyGen's own launch videos: HyperFrames, Cloud Render, Figma integration, Timeline editor, Kimi K3 promo, a Codex replica and more. Each folder is a standalone HyperFrames project with index.html, scene compositions, assets and a STORYBOARD.md; the HyperFrames launch storyboard runs 10 timed beats over 60 s (cold open on a moving canvas, name, proposition, anatomy, thesis, flex, contrast, engine, CTA, return to canvas). Preview with hyperframes preview, render with hyperframes render. Needs Git LFS for assets; bundled brand media and fonts are not covered by the license.
Use when
- Remix a real, shipped SaaS launch video instead of starting blank
- See how a 60 s launch film is storyboarded beat by beat
- Re-brand a launch template (the heygen-apple-motion set) for your product
- Learn HyperFrames composition structure from production examples
Install
- Claude Code:
git clone https://github.com/heygen-com/hyperframes-launches.git - Any agent, with the vargai CLI:
vargai install heygen-hyperframes-launch-videos-source
Example output
https://github.com/heygen-com/hyperframes-launches/raw/main/codex-five-hour-limit-replica/codex-five-hour-limit-replica.mp4 — example (credit: heygen-com)
More launch videos skills
- Orbit Card: A single feature card orbits a dot sphere on a Blender-made camera move: a 10-second product beat.
- Higgsfield Academy (Higgsfield Open-Source Promo): Higgsfield's 64 s promo for Higgsfield Academy, made almost entirely with Seedance 2.0.
- Seed Audio 1.0 Launch (Higgsfield Open-Source Video): Higgsfield's 106 s launch video for Seed Audio 1.0 (voice cloning, cinematic sound): bold motion design, comedic tone.
- Onetake: Launch films that never cut to the next slide: one continuous camera, measured moves, motion blur, a slideshow oracle.
- Guizang Product Video: Software promos and release-notes videos built from your real product components, with original music and SFX.
- Opus 5.5 Motion Studio Harness: Eight .md files that turn Claude Code + Remotion into a launch-film studio: brief, style, storyboard, motion, sound, render.
Run the generation on varg
varg is one API key for the models these skills drive — Seedance 2.5, Kling 4, Veo 3.1, Wan 3, Nano Banana 2.1, GPT Image 2.5, ElevenLabs v4 and 200+ more — billed in credits, with a cost estimate before anything runs.
- Any agent with a terminal:
curl -fsSL https://varg.ai/install | sh(Windows:irm https://varg.ai/install.ps1 | iex), thenvargai loginand every model is a command —vargai generate_video …,vargai estimate_cost …(https://varg.ai/how-to/cli/) - Claude Code:
claude plugin marketplace add vargHQ/skills && claude plugin install varg@varg(skill + hosted MCP) - Codex, Cursor, Gemini CLI, OpenClaw:
npx skills add vargHQ/skills --skill varg-ai -a <agent> -y - Grok and any agent that reads SKILL.md:
npx skills add vargHQ/skills --skill varg-ai, or point it at the skill's SKILL.md - Claude.ai, ChatGPT, any MCP client: connect
https://mcp.varg.ai/mcp - API key: https://varg.ai/dashboard/api · Model specs: https://varg.ai/models/llms.txt