Brand-Color Silk Waves — effect skill for backdrops
For AI agents: find the right skill in one call —
curl -s "https://skills.varg.ai/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://skills.varg.ai/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.
Smooth silk-like folds or wave bands in brand colors flow slowly behind the content.
- Type: Effect · Backdrops
- Slug:
brand-silk-waves - Status: live
- Publisher: David Haz (community)
- License: MIT + Commons Clause
- Source: https://github.com/DavidHDev/react-bits/blob/main/src/content/Backgrounds/Silk/Silk.jsx
- Works in: Claude Code, Claude.ai, Codex, Cursor, OpenClaw, Gemini CLI, Any MCP client, varg Studio
- Requires: HyperFrames (npx hyperframes), Remotion, CapCut (by hand)
- Cost: Free — the take renders locally; generated footage, if any, bills by the model
What it does
Built on Silk by react-bits, MIT + Commons Clause. The write-up and recipes below are varg's.
Soft satin folds or broad blurred waves; one hue family, subtle highlights, slow motion.
When: Consumer and creative brands; music, audio and design tools.
Watch out: Do not pick more than two hues; rainbow silk reads as a screensaver.
Timing: Flow speed low (one fold crossing per 4–6 s).
Also called: silk background, wavy gradient, flowing bands
In HyperFrames
npx hyperframes add flowing-gradient
WebGPU shader; set the two brand colors as variables.
In Remotion
// npx shadcn@latest add @aceternity/wavy-background (seed its noise with frame for seek-safety)
In CapCut
Search Media → Library "silk"/"waves background"; apply Adjust → HSL to shift to brand hue.
Ready-made components
- Silk (react-bits): npx shadcn@latest add @react-bits/Silk-JS-CSS
- Wavy Background (aceternity): npx shadcn@latest add @aceternity/wavy-background
- Flowing Gradient (hyperframes): npx hyperframes add flowing-gradient
Where this comes from
Use when
- Consumer and creative brands; music, audio and design tools.
Not for
- Do not pick more than two hues; rainbow silk reads as a screensaver.
Install
- Claude Code:
claude plugin marketplace add vargHQ/skills && claude plugin install varg@varg - Codex:
npx skills add vargHQ/skills --skill varg-video-edit-library -a codex -y - Cursor:
npx skills add vargHQ/skills --skill varg-video-edit-library -a cursor -y
Example output
https://s3.varg.ai/how-to/previews/0c9046598c5a/lib-react-bits-silk.mp4 — Preview of the Silk component that builds this take (credit: Captured from the library’s own demo page (React Bits), https://reactbits.dev/backgrounds/silk)
More backdrops skills
- Slow Mesh Gradient: Soft brand-colored fields blend and drift slowly behind titles and UI.
- Aurora Behind the Title: Blurred light streaks drift sideways across a dark frame behind a centered title.
- Faint Grid or Dot Field: A very faint line grid or dot field gives structure behind UI and code, with a soft radial fade.
- Spotlight From Above: Soft light cones fall from the top of a dark frame onto the product or title.
- Film Grain Over Gradient: A fine animated grain sits over the gradient so it feels printed, removes banding and looks less digital.
- Blurred Product Behind Text: The product UI itself, heavily blurred and dimmed, becomes the backdrop for a title or quote.
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.
- 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