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RojiosRojios/everything-claude-code/skills/manim-video/SKILL.md

manim-video

Skill1 starsChanged 7 months agoMITView on GitHub

Build reusable Manim explainers for technical concepts, graphs, system diagrams, and product walkthroughs, then hand off to the wider ECC video stack if needed. Use when the user wants a clean animated explainer rather than a generic talking-head script.

29 other projects use a version of this, 4 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use songwriting-and-ai-music, p5js and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 8 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 27 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

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

    line 9
  2. Distinctive:

    Write the scene outline before writing Manim code.

    line 36
  3. Distinctive:

    prefer progressive reveal over full-screen clutter

    line 45
  4. Distinctive:

    use motion to explain state change, not just to keep the screen busy

    line 46
  5. Distinctive:

    if useful, add a final scene showing the self-improvement lineage that informed the skill

    line 56
  6. Distinctive:

    default to 16:9 landscape unless the user asks for vertical

    line 60
  7. Distinctive:

    start with a low-quality smoke test render

    line 61
  8. Distinctive:

    only push to higher quality after composition and timing are stable

    line 62
  9. Very specific:

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

    line 67

“Common” is measured: kept by at least 6 in 10 of the 27 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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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