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Manim Video

affaan-m/everything-claude-code

Turns technical concepts into clean Manim animations instead of generic explainer videos. Best for graphs, system diagrams, architecture walkthroughs, or product launches where you need precise motion over stock footage. The workflow pushes you to write a one-sentence visual thesis and break it into 3 to 6 scenes before touching code, which prevents the usual mistake of overstuffed diagrams. It includes a reusable network graph starter and defaults to low-quality smoke tests until timing is stable. Hands off to the wider video stack only when compositing or captions actually add value. Honest take: this is the right tool when motion should explain state change, not just keep the screen busy.

installs
3.8K
GitHub stars
229.1K
last updated
Jul 14, 2026
View on GitHubSave

Install

$ npx -y skills add affaan-m/everything-claude-code --skill manim-video --agent claude-code

Installs into .claude/skills of the current project.

Files

Manim Video

Use Manim for technical explainers where motion, structure, and clarity matter more than photorealism.

When to Activate

  • the user wants a technical explainer animation
  • the concept is a graph, workflow, architecture, metric progression, or system diagram
  • the user wants a short product or launch explainer for X or a landing page
  • the visual should feel precise instead of generically cinematic

Tool Requirements

  • manim CLI for scene rendering
  • ffmpeg for post-processing if needed
  • video-editing for final assembly or polish
  • remotion-video-creation when the final package needs composited UI, captions, or additional motion layers

Default Output

  • short 16:9 MP4
  • one thumbnail or poster frame
  • storyboard plus scene plan

Workflow

  1. Define the core visual thesis in one sentence.
  2. Break the concept into 3 to 6 scenes.
  3. Decide what each scene proves.
  4. Write the scene outline before writing Manim code.
  5. Render the smallest working version first.
  6. Tighten typography, spacing, color, and pacing after the render works.
  7. Hand off to the wider video stack only if it adds value.

Scene Planning Rules

  • each scene should prove one thing
  • avoid overstuffed diagrams
  • prefer progressive reveal over full-screen clutter
  • use motion to explain state change, not just to keep the screen busy
  • title cards should be short and loaded with meaning

Network Graph Default

For social-graph and network-optimization explainers:

  • show the current graph before showing the optimized graph
  • distinguish low-signal follow clutter from high-signal bridges
  • highlight warm-path nodes and target clusters
  • if useful, add a final scene showing the self-improvement lineage that informed the skill

Render Conventions

  • default to 16:9 landscape unless the user asks for vertical
  • start with a low-quality smoke test render
  • only push to higher quality after composition and timing are stable
  • export one clean thumbnail frame that reads at social size

Reusable Starter

Use assets/network_graph_scene.py as a starting point for network-graph explainers.

Example smoke test:

manim -ql assets/network_graph_scene.py NetworkGraphExplainer

Output Format

Return:

  • core visual thesis
  • storyboard
  • scene outline
  • render plan
  • any follow-on polish recommendations

Related Skills

  • video-editing for final polish
  • remotion-video-creation for motion-heavy post-processing or compositing
  • content-engine when the animation is part of a broader launch
SKILL.md on GitHub

Sponsors

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Details

Repository
github.com/affaan-m/everything-claude-code
First seen
Apr 16, 2026

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