Manim Video Production Pipeline skill

Manim Video Production Pipeline

Creative Standard

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.

Prerequisites

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.

Modes

Mode	Input	Output	Reference
Concept explainer	Topic/concept	Animated explanation with geometric intuition	references/scene-planning.md
Equation derivation	Math expressions	Step-by-step animated proof	references/equations.md
Algorithm visualization	Algorithm description	Step-by-step execution with data structures	references/graphs-and-data.md
Data story	Data/metrics	Animated charts, comparisons, counters	references/graphs-and-data.md
Architecture diagram	System description	Components building up with connections	references/mobjects.md
Paper explainer	Research paper	Key findings and methods animated	references/scene-planning.md
3D visualization	3D concept	Rotating surfaces, parametric curves, spatial geometry	references/camera-and-3d.md

Stack

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

Layer	Tool	Purpose
Core	Manim Community Edition	Scene rendering, animation engine
Math	LaTeX (texlive/MiKTeX)	Equation rendering via MathTex
Video I/O	ffmpeg	Scene stitching, format conversion, audio muxing
TTS	ElevenLabs / Qwen3-TTS (optional)	Narration voiceover

Pipeline

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

Project Structure

project-name/
  plan.md                # Narrative arc, scene breakdown
  script.py              # All scenes in one file
  concat.txt             # ffmpeg scene list
  final.mp4              # Stitched output
  media/                 # Auto-generated by Manim
    videos/script/480p15/

Creative Direction

Color Palettes

Palette	Background	Primary	Secondary	Accent	Use case
Classic 3B1B	#1C1C1C	#58C4DD (BLUE)	#83C167 (GREEN)	#FFFF00 (YELLOW)	General math/CS
Warm academic	#2D2B55	#FF6B6B	#FFD93D	#6BCB77	Approachable
Neon tech	#0A0A0A	#00F5FF	#FF00FF	#39FF14	Systems, architecture
Monochrome	#1A1A2E	#EAEAEA	#888888	#FFFFFF	Minimalist

Animation Speed

Context	run_time	self.wait() after
Title/intro appear	1.5s	1.0s
Key equation reveal	2.0s	2.0s
Transform/morph	1.5s	1.5s
Supporting label	0.8s	0.5s
FadeOut cleanup	0.5s	0.3s
"Aha moment" reveal	2.5s	3.0s

Typography Scale

Role	Font size	Usage
Title	48	Scene titles, opening text
Heading	36	Section headers within a scene
Body	30	Explanatory text
Label	24	Annotations, axis labels
Caption	20	Subtitles, fine print

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

Workflow

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

Critical Implementation Notes

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

Performance Targets

Quality	Resolution	FPS	Speed
-ql (draft)	854x480	15	5-15s/scene
-qm (medium)	1280x720	30	15-60s/scene
-qh (production)	1920x1080	60	30-120s/scene

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

References

File	Contents
references/animations.md	Core animations, rate functions, composition, .animate syntax, timing patterns
references/mobjects.md	Text, shapes, VGroup/Group, positioning, styling, custom mobjects
references/visual-design.md	12 design principles, opacity layering, layout templates, color palettes
references/equations.md	LaTeX in Manim, TransformMatchingTex, derivation patterns
references/graphs-and-data.md	Axes, plotting, BarChart, animated data, algorithm visualization
references/camera-and-3d.md	MovingCameraScene, ThreeDScene, 3D surfaces, camera control
references/scene-planning.md	Narrative arcs, layout templates, scene transitions, planning template
references/rendering.md	CLI reference, quality presets, ffmpeg, voiceover workflow, GIF export
references/troubleshooting.md	LaTeX errors, animation errors, common mistakes, debugging
references/animation-design-thinking.md	When to animate vs show static, decomposition, pacing, narration sync
references/updaters-and-trackers.md	ValueTracker, add_updater, always_redraw, time-based updaters, patterns
references/paper-explainer.md	Turning research papers into animations — workflow, templates, domain patterns
references/decorations.md	SurroundingRectangle, Brace, arrows, DashedLine, Angle, annotation lifecycle
references/production-quality.md	Pre-code, pre-render, post-render checklists, spatial layout, color, tempo

---

Creative Divergence (use only when user requests experimental/creative/unique output)

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