Tracing Beam Through Steps — effect skill for AI agent flows
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.
A glowing dash travels one path through numbered steps, lighting each as it passes.
- Type: Effect · AI agent flows
- Slug:
tracing-beam-through-steps - Status: live
- Publisher: HeyGen (community)
- License: Apache-2.0
- Source: https://github.com/heygen-com/hyperframes/tree/main/registry/components/tracing-beam
- 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 Tracing Beam by HeyGen (HyperFrames), Apache-2.0. The write-up and recipes below are varg's.
A thin rail connects 3–5 step cards; a bright head with a short tail moves along it and each card lifts and brightens on contact.
When: Explain a 3–5 step workflow (connect → generate → publish) in one continuous move.
Watch out: Do not exceed 5 steps; split longer flows into two scenes.
Timing: 1–1.5 s per segment, power2.inOut; card lift 0.25 s on arrival.
Also called: stepper, progress path, onboarding steps
In HyperFrames
npx hyperframes add tracing-beam
npx hyperframes add onboarding-stepper-flow
In Remotion
// npx shadcn@latest add @remocn/stepper (progress = continuous step index)
const step = interpolate(frame,[0,120],[0,4],{extrapolateRight:'clamp'});
In CapCut
Line shape with a glowing dot sticker keyframed along it; each step card with Animation In timed to the dot.
Ready-made components
- Tracing Beam (hyperframes): npx hyperframes add tracing-beam
- Onboarding Stepper Flow (hyperframes): npx hyperframes add onboarding-stepper-flow
- Flowchart Vertical (hyperframes): npx hyperframes add flowchart-vertical
- UI Stepper (remocn): npx shadcn@latest add @remocn/stepper
Where this comes from
Use when
- Explain a 3–5 step workflow (connect → generate → publish) in one continuous move.
Not for
- Do not exceed 5 steps; split longer flows into two scenes.
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/643996847b5b/take-tracing-beam-through-steps.mp4 — The Tracing Beam component rendered as installed (npx hyperframes add tracing-beam), defaults only (credit: Rendered by varg · HyperFrames Tracing Beam, https://hyperframes.heygen.com/catalog/components/tracing-beam)
More AI agent flows skills
- Prompt Typed, Then Generate: A real task types into the prompt box, the Generate button is pressed, and the result starts to build.
- Answer Streams In: The assistant's reply arrives in uneven token bursts, the way a real model streams.
- Tool Calls as Status Rows: Each tool call appears as a row with an icon and label that goes spinner → check, building a visible plan.
- Nodes Wire Up on a Canvas: Nodes pop onto a canvas and connectors draw between them as the camera pulls back to show the whole pipeline.
- Beams Into the Agent Hub: Light pulses run along curved lines from tool icons into a central agent and back out to a result.
- Thinking… Shimmer Label: A muted "Thinking…" label with a moving shine shows the model working between prompt and answer.
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