Manim Video

Manim CE animations: 3Blue1Brown math/algo videos.

Use when users request: animated explanations, math animations, concept visualizations, algorithm walkthroughs, technical explainers, 3Blue1Brown style videos, or any programmatic animation with geometric/mathematical content. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories using Manim Community Edition.

This is educational cinema. Every frame teaches. Every animation reveals structure.

Before writing a single line of code, articulate the narrative arc. What misconception does this correct? What is the "aha moment"? What visual story takes the viewer from confusion to understanding? The user's prompt is a starting point — interpret it with pedagogical ambition.

Geometry before algebra. Show the shape first, the equation second. Visual memory encodes faster than symbolic memory. When the viewer sees the geometric pattern before the formula, the equation feels earned.

First-render excellence is non-negotiable. The output must be visually clear and aesthetically cohesive without revision rounds. If something looks cluttered, poorly timed, or like "AI-generated slides," it is wrong.

Opacity layering directs attention. Never show everything at full brightness. Primary elements at 1.0, contextual elements at 0.4, structural elements (axes, grids) at 0.15. The brain processes visual salience in layers.

Breathing room. Every animation needs self.wait() after it. The viewer needs time to absorb what just appeared. Never rush from one animation to the next. A 2-second pause after a key reveal is never wasted.

Cohesive visual language. All scenes share a color palette, consistent typography sizing, matching animation speeds. A technically correct video where every scene uses random different colors is an aesthetic failure.

Run scripts/setup.sh to verify all dependencies. Requires: Python 3.10+, Manim Community Edition v0.20+ (pip install manim), LaTeX (texlive-full on Linux, mactex on macOS), and ffmpeg. Reference docs tested against Manim CE v0.20.1.

Single Python script per project. No browser, no Node.js, no GPU required.

PLAN --> CODE --> RENDER --> STITCH --> AUDIO (optional) --> REVIEW

1. PLAN — Write plan.md with narrative arc, scene list, visual elements, color palette, voiceover script
2. CODE — Write script.py with one class per scene, each independently renderable
3. RENDER — manim -ql script.py Scene1 Scene2 ... for draft, -qh for production
4. STITCH — ffmpeg concat of scene clips into final.mp4
5. AUDIO (optional) — Add voiceover and/or background music via ffmpeg. See references/rendering.md
6. REVIEW — Render preview stills, verify against plan, adjust

Color Palettes

Animation Speed

Typography Scale

Fonts

Use monospace fonts for all text. Manim's Pango renderer produces broken kerning with proportional fonts at all sizes. See references/visual-design.md for full recommendations.

MONO = "Menlo"  # define once at top of file

Text("Fourier Series", font_size=48, font=MONO, weight=BOLD)  # titles
Text("n=1: sin(x)", font_size=20, font=MONO)                  # labels
MathTex(r"\nabla L")                                            # math (uses LaTeX)

Minimum font_size=18 for readability.

Per-Scene Variation

Never use identical config for all scenes. For each scene:

• Different dominant color from the palette
• Different layout — don't always center everything
• Different animation entry — vary between Write, FadeIn, GrowFromCenter, Create
• Different visual weight — some scenes dense, others sparse

Step 1: Plan (plan.md)

Before any code, write plan.md. See references/scene-planning.md for the comprehensive template.

Step 2: Code (script.py)

One class per scene. Every scene is independently renderable.

from manim import *

BG = "#1C1C1C"
PRIMARY = "#58C4DD"
SECONDARY = "#83C167"
ACCENT = "#FFFF00"
MONO = "Menlo"

class Scene1_Introduction(Scene):
    def construct(self):
        self.camera.background_color = BG
        title = Text("Why Does This Work?", font_size=48, color=PRIMARY, weight=BOLD, font=MONO)
        self.add_subcaption("Why does this work?", duration=2)
        self.play(Write(title), run_time=1.5)
        self.wait(1.0)
        self.play(FadeOut(title), run_time=0.5)

Key patterns:

• Subtitles on every animation: self.add_subcaption("text", duration=N) or subcaption="text" on self.play()
• Shared color constants at file top for cross-scene consistency
• self.camera.background_color set in every scene
• Clean exits — FadeOut all mobjects at scene end: self.play(FadeOut(Group(*self.mobjects)))

Step 3: Render

manim -ql script.py Scene1_Introduction Scene2_CoreConcept  # draft
manim -qh script.py Scene1_Introduction Scene2_CoreConcept  # production

Step 4: Stitch

cat > concat.txt << 'EOF'
file 'media/videos/script/480p15/Scene1_Introduction.mp4'
file 'media/videos/script/480p15/Scene2_CoreConcept.mp4'
EOF
ffmpeg -y -f concat -safe 0 -i concat.txt -c copy final.mp4

Step 5: Review

manim -ql --format=png -s script.py Scene2_CoreConcept  # preview still

Raw Strings for LaTeX

# WRONG: MathTex("\frac{1}{2}")
# RIGHT:
MathTex(r"\frac{1}{2}")

buff >= 0.5 for Edge Text

label.to_edge(DOWN, buff=0.5)  # never < 0.5

FadeOut Before Replacing Text

self.play(ReplacementTransform(note1, note2))  # not Write(note2) on top

Never Animate Non-Added Mobjects

self.play(Create(circle))  # must add first
self.play(circle.animate.set_color(RED))  # then animate

Always iterate at -ql. Only render -qh for final output.

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If the user asks for creative, experimental, or unconventional explanatory approaches, select a strategy and reason through it BEFORE designing the animation.

• SCAMPER — when the user wants a fresh take on a standard explanation
• Assumption Reversal — when the user wants to challenge how something is typically taught

SCAMPER Transformation

Take a standard mathematical/technical visualization and transform it:

• Substitute: replace the standard visual metaphor (number line → winding path, matrix → city grid)
• Combine: merge two explanation approaches (algebraic + geometric simultaneously)
• Reverse: derive backward — start from the result and deconstruct to axioms
• Modify: exaggerate a parameter to show why it matters (10x the learning rate, 1000x the sample size)
• Eliminate: remove all notation — explain purely through animation and spatial relationships

Assumption Reversal

1. List what's "standard" about how this topic is visualized (left-to-right, 2D, discrete steps, formal notation)
2. Pick the most fundamental assumption
3. Reverse it (right-to-left derivation, 3D embedding of a 2D concept, continuous morphing instead of steps, zero notation)
4. Explore what the reversal reveals that the standard approach hides