Rapid Screenshot Burst — effect skill for grids & carousels
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.
Full-screen images slam in one on top of another on the beat, landing on the final hero shot.
- Type: Effect · Grids & carousels
- Slug:
rapid-screenshot-burst - Status: live
- Publisher: Codrops (community)
- License: MIT (per demo repo)
- Source: https://github.com/codrops/RapidLayersAnimation
- Works in: Claude Code, Claude.ai, Codex, Cursor, OpenClaw, Gemini CLI, Any MCP client, varg Studio
- Requires: ffmpeg, 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 Rapid Image Layers Animation by codrops, MIT (per demo repo). The write-up and recipes below are varg's.
6–12 images, each held 2–4 frames, slight scale punch per layer, then the last one holds and settles.
When: Hype moments: "everything you can make" or the drop in the music.
Watch out: Do not hold each image so short that colors strobe; 2 frames minimum at 30 fps, avoid high-contrast flashing.
Timing: 2–4 frames per image (beat-synced), final settle 0.4 s.
Also called: rapid layers, flash montage, image slam
In FFmpeg
# 0.1 s per image from a list, then concat
ffmpeg -f concat -safe 0 -i list.txt -vf "fps=30,scale=1920:1080:force_original_aspect_ratio=increase,crop=1920:1080" burst.mp4
# list.txt: file 'a.jpg'\nduration 0.1 ...
In HyperFrames
npx hyperframes add velocity-throw-snap
Or stack <img class="clip"> elements with data-start on each beat and data-duration of 2–4 frames.
In Remotion
<Series>{imgs.map((src,i)=><Series.Sequence key={i} durationInFrames={i===imgs.length-1?30:3}><Img src={src} style={{transform:`scale(${1.06 - (frame%3)*0.02})`}}/></Series.Sequence>)}</Series>
In CapCut
Drop images on the track, select all → set duration 0.1 s; use Beats (auto beat markers) to align; add a zoom-in animation.
Ready-made components
- Rapid Image Layers Animation (codrops): git clone https://github.com/codrops/RapidLayersAnimation
- Velocity Throw Snap (hyperframes): npx hyperframes add velocity-throw-snap
Where this comes from
Use when
- Hype moments: "everything you can make" or the drop in the music.
Not for
- Do not hold each image so short that colors strobe; 2 frames minimum at 30 fps, avoid high-contrast flashing.
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/1b9880c6836c/lib-codrops-rapid-layers-animation.mp4 — Preview of the Rapid Image Layers Animation component that builds this take (credit: From the library’s repo (Codrops — Manoela Ilic), https://tympanus.net/Development/RapidLayersAnimation/)
More grids & carousels skills
- Bento Feature Grid: Features land in a grid of differently sized rounded tiles — one hero tile, smaller supporting ones.
- Camera Drifts Across a Bento: An oversized grid of screenshots fills the frame and the camera drifts diagonally across it.
- Tilted Screenshot Wall: A wall of screenshots seen at an isometric angle, columns scrolling up and down at different speeds.
- Stacked Cards Fan Out: A pile of cards or photos shuffles, then fans or settles one forward into focus.
- App Screens on a Rail: Two to five app screens ride a horizontal rail: one centered and sharp, neighbors smaller and receded.
- Cards Orbit in a Ring: Image cards ride a circle, larger in front and smaller behind, sweeping fast-slow-fast.
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