Clone Any Launch Video Shot for Shot in HyperFrames — workflow 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 .md to its path. Before generating anything, show the person the options on the how-to page. From a terminal: curl -fsSL https://varg.ai/install | sh installs the vargai CLI (https://varg.ai/how-to/cli.md): vargai search and vargai install <slug> with no key, every varg model after vargai login.

Rebuild a reference launch video in HyperFrames with measured timing and easing, re-skin it for your brand, or make an original.

What it does

Input: a reference video (or none, for Original mode). burst.py turns the reference into per-shot frame sheets, motion trails, easing curves and beat maps the model can read; the agent writes a frame-accurate BREAKDOWN.md, builds in HyperFrames, and compare.py grades every render against the reference until timing matches. Six type files (UI showcase, abstract 3D diagram, 3D product, editorial collage, liquid-glass UI, kinetic type into UI) hold build approach and traps, and motion-feel.md lists why motion reads as AI (stopping between keys, lockstep, settling too fast). Needs HyperFrames CLI, ffmpeg, Python with numpy/opencv; ElevenLabs optional for sound.

Use when

Install

More launch videos skills

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.