Diagram Animation logo

Diagram Animation

Organization
iart-ai
diagram-animation

This skill should be used when the user asks to "animate this diagram", "build a flowchart that reveals step by step", "animate an architecture/sequence diagram", "make a chart animate in", "grow the bars / draw the line / count up the number", "show data flowing along a connector", or "turn a static diagram into a guided reveal". Covers SVG, Framer Motion, D3, and Remotion.

Overview

Publisheriart-ai
Repositoryexplainer-video-skills
Skill namediagram-animation
Stars
73
Forks
14
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by iart-ai on GitHub. Read the source before you install it.

Installation

Install the Diagram Animation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/iart-ai/explainer-video-skills/tree/main/skills/diagram-animation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/iart-ai/explainer-video-skills.git /tmp/explainer-video-skills
mkdir -p .claude/skills
cp -r /tmp/explainer-video-skills/skills/diagram-animation .claude/skills/diagram-animation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Diagram Animation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Diagram Animation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Diagram Animation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Diagram & Data Animation

Make structure and data legible by revealing it over time — one idea per beat. Build progressive node/edge reveals, flowing connectors, and animated charts (bars grow, lines draw, numbers count up) for web or video.

When to use

  • Architecture, flow, or sequence diagrams that build step by step.
  • Animated charts: bars grow, lines draw on, numbers count up.
  • "How it works" walkthroughs and process explainers.
  • Showing data or signal flowing along connectors.

Core principle: progressive disclosure

Never show everything at once. Reveal in this order: nodes → edges → labels. Highlight the active element and dim the rest (focus + context). Pace to comprehension, not flash — hold each step 0.5–1.5s so it lands. Keep a consistent visual grammar: color means meaning, and that mapping never changes mid-piece.

Quick reference

GoalMechanismEasing
Node appearscale 0.8→1 + opacity, transform-origin:centerback.out(1.5) / easeOut
Edge connectstroke-dashoffset len→0easeInOut, 0.4–0.7s
Flowing dataanimate stroke-dashoffset looping + traveling dotlinear, infinite
Bar growscaleY 0→1, transform-origin:bottomeaseOut, stagger 0.06s
Line chartpath stroke-dashoffset len→0easeInOut, 0.8–1.2s
Count-upinterpolate value with eased teaseOutCubic
Highlightactive full-opacity, others opacity:.350.3s

Progressive node/edge reveal (SVG + GSAP)

html
<svg viewBox="0 0 400 200" id="flow">
  <g class="node" opacity="0"><circle cx="60" cy="100" r="28" fill="#0A84FF"/></g>
  <g class="node" opacity="0"><circle cx="200" cy="100" r="28" fill="#0A84FF"/></g>
  <g class="node" opacity="0"><circle cx="340" cy="100" r="28" fill="#0A84FF"/></g>
  <path class="edge" d="M88 100 H172" stroke="#888" stroke-width="3" fill="none" pathLength="1"/>
  <path class="edge" d="M228 100 H312" stroke="#888" stroke-width="3" fill="none" pathLength="1"/>
</svg>
<script type="module">
  import gsap from "https://cdn.jsdelivr.net/npm/gsap/+esm";
  gsap.set(".edge", { strokeDasharray: 1, strokeDashoffset: 1 });
  const tl = gsap.timeline({ defaults: { ease: "power2.out" } });
  tl.to(".node", { opacity: 1, scale: 1, transformOrigin: "center",
                   duration: .45, stagger: .35, ease: "back.out(1.6)", startAt: { scale: .8 } })
    .to(".edge", { strokeDashoffset: 0, duration: .5, stagger: .35 }, "-=0.9");
</script>

pathLength="1" lets one dash value drive any edge length. Reveal nodes first, then draw edges between the now-visible nodes.

Flowing connector (marching dash + traveling dot)

css
.flow-line { stroke-dasharray: 8 8; animation: march 0.6s linear infinite; }
@keyframes march { to { stroke-dashoffset: -16; } }   /* = sum of dash pattern */
@media (prefers-reduced-motion: reduce){ .flow-line { animation: none; } }

Traveling dot along the path (offset-path, no JS):

css
.packet { offset-path: path("M88 100 H312"); animation: travel 1.4s linear infinite; }
@keyframes travel { to { offset-distance: 100%; } }

Charts

Bar grow (scaleY from the baseline):

css
.bar { transform: scaleY(0); transform-origin: bottom; }
.bar.in { transform: scaleY(1); transition: transform .6s cubic-bezier(.22,1,.36,1); }
/* stagger via inline transition-delay per bar */

Line chart draw-on (the whole series path strokes in):

js
const len = pathEl.getTotalLength();
pathEl.style.strokeDasharray = len;
pathEl.style.strokeDashoffset = len;
pathEl.getBoundingClientRect();                 // force reflow
pathEl.style.transition = "stroke-dashoffset 1s ease-in-out";
pathEl.style.strokeDashoffset = "0";

Count-up with eased interpolation (rAF):

js
function countUp(el, to, dur = 1200) {
  const t0 = performance.now();
  const fmt = new Intl.NumberFormat();
  (function tick(now){
    const k = Math.min(1, (now - t0) / dur);
    const e = 1 - Math.pow(1 - k, 3);           // easeOutCubic
    el.textContent = fmt.format(Math.round(to * e));
    if (k < 1) requestAnimationFrame(tick);
  })(t0);
}

Build-tool choice

  • Inline animated SVG + GSAP/CSS: best for bespoke diagrams and full control on the web.
  • Framer Motion (React): declarative reveals via variants + staggerChildren; pairs with Visx/Recharts for charts.
  • D3 + transitions: data-bound charts; .transition().duration().attr() for grow/draw, tween for count-up.
  • Mermaid / Excalidraw: author the diagram structure fast, render to SVG, then animate the SVG.
  • Remotion (React): data-driven, deterministic renders for video output and repeatable exports.

Output checklist

  • Reveal order is nodes → edges → labels; nothing dumps in all at once.
  • Each step holds long enough to read (0.5–1.5s).
  • Color grammar is consistent and meaningful.
  • Active element highlighted, context dimmed.
  • prefers-reduced-motion path shows the final composed diagram without looping motion.

Deliver & verify (standalone HTML)

Packaged helper (scripts/): scripts/seek-shot.sh anim.html 0 1.5 3 freezes the ?t=N harness and screenshots each moment; scripts/contact-sheet.sh sheet.png frame-*.png tiles them for one-glance review. See scripts/README.md.

For a self-contained diagram (reveal, flowing connector, animated chart) the deliverable is one HTML file that opens directly in a browser — no build step, no render pipeline. A single file is the right tier for web motion. (If the diagram is part of a rendered video, build it as a Remotion composition instead and verify via remotion still — see remotion-video.)

Output contract:

  • One .html file: SVG inline; Framer Motion / D3 / anime / GSAP from CDN; the animation in one inline <script> (one driver).
  • A way to freeze an exact moment for screenshots, matched to how the diagram animates:
    • GSAP / JS timeline: build one master tl, then ?t=N → tl.pause(); tl.seek(N).
    • SVG SMIL: svg.pauseAnimations(); svg.setCurrentTime(N).
    • CSS keyframes: drive reveal order with animationDelay; freeze by pausing/seeking the equivalent JS timeline.
html
<script>
  // ... build your master timeline as `tl` ...
  const t = new URLSearchParams(location.search).get("t");
  if (t !== null) { tl.pause(); tl.seek(parseFloat(t)); }  // frozen at t seconds
  window.__ready = true;                                    // ready signal for headless wait
  console.log("duration", tl.duration());
</script>

Verify loop — render → freeze → screenshot → check:

  1. Open the file at start / mid / end: …/diagram.html?t=0, ?t=<dur/2>, ?t=<dur> (read tl.duration() from the console).
  2. Headless-screenshot each frozen frame:
    bash
    npx playwright screenshot --wait-for-timeout=500 "file://$PWD/diagram.html?t=1.2" frame-mid.png
  3. Check fidelity — the step-by-step reveal appears in order (nodes → edges → labels, each step present at its frame), connectors point at the right nodes, count-ups land on the EXACT values — and artifacts (clipped labels, off-canvas nodes, FOUC before fonts, jank at seams).

Before you finish:

  1. Opens standalone in a browser — no console errors, no missing CDN.
  2. One driver/master timeline; the freeze (?t=N / setCurrentTime) lands on a deterministic still.
  3. Screenshotted at start / mid / end — reveal order correct, connectors land on the right nodes, numbers exact.
  4. prefers-reduced-motion shows the final composed diagram without looping motion.
  5. Color grammar consistent; active element highlighted, context dimmed; nothing dumps in all at once.

Reference files

  • references/diagram-and-chart-recipes.md — fuller runnable code: staged node/edge reveal with labels, flowing-dash + traveling-dot connectors, bar/line/count-up chart recipes, sequence-diagram and architecture build patterns, and D3 / Framer Motion / Remotion implementations with easing notes.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Diagram Animation AI skill do?

This skill should be used when the user asks to "animate this diagram", "build a flowchart that reveals step by step", "animate an architecture/sequence diagram", "make a chart animate in", "grow the bars / draw the line / count up the number", "show data flowing along a connector", or "turn a static diagram into a guided reveal". Covers SVG, Framer Motion, D3, and Remotion.

Why use Diagram Animation on TypingMind?

Because you install it once and use it with any model. Diagram Animation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Diagram Animation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/iart-ai/explainer-video-skills/tree/main/skills/diagram-animation. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Diagram Animation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Diagram Animation?

As many as you like. As long as a model supports skills, you can use Diagram Animation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Diagram Animation AI skill free?

Yes. It is published on GitHub by iart-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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