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Skill

manim-video

Builds Manim animations for technical concepts, graphs, system diagrams, and product walkthroughs. Activates for precise animated explainers instead of talking-head scripts.

From everything-claude-code
Install
1
Run in your terminal
$
npx claudepluginhub affaan-m/everything-claude-code --plugin everything-claude-code
Tool Access

This skill uses the workspace's default tool permissions.

Supporting Assets
View in Repository
assets/network_graph_scene.py
Skill Content

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
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Stats
Stars134683
Forks19648
Last CommitApr 2, 2026
Actions
View SourceView PluginView on GitHubView README
Stats
Stars134683
Forks19648
Last CommitApr 2, 2026
Actions
View SourceView PluginView on GitHubView README