SaaS Launch Films Cut to a Music Bar Grid — 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.

SaaS launch film in the style of Cursor, Notion and Higgsfield: real product rebuilt as Remotion components, every scene on a music bar.

What it does

Distilled from 17 reviewed cuts of one real launch film. Study 4-6 reference films frame by frame, source only real material (demo routes recorded with Playwright, internal-account data, the brand deck), then pick the music, detect BPM and write the story as a list of bars with one ANCHOR drop. The Remotion kit holds the devices that survived review: Composer, StreamText, Cursor2 (arrive, pause, dip, page reacts), ProcessButton (Apply, spinner, check, toast), Wall, Tour, dark bookends. stemscore2.py arranges Demucs stems per scene; output is 1080p60 at -14 LUFS with contact-sheet QA.

Use when

Install

Example output

https://github.com/nawneet77/launch-film/raw/main/docs/launch-film-demo.mp4 — example (credit: nawneet77)

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.