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manim-video

Create animated explanations of mathematical concepts, equation derivations, and algorithms with Manim Community Edition. The skill guides scene planning, Python animation code, rendering, and clip assembly into a finished explainer video.

OriginalShow the original description

Manim CE animations: 3Blue1Brown math/algo videos.

AI rating90/ 100See how to install

Good for

  • Explaining mathematical concepts through animated geometry
  • Showing equation derivations step by step
  • Visualizing how an algorithm runs
  • Turning research findings into animated explanations

Overview

What it does

Turn mathematical and technical material into explainer videos with moving shapes and equations. Using Manim Community Edition, the skill covers concepts, equation derivations, algorithm execution, data comparisons, system architecture diagrams, and 3D shapes. It guides you through organizing the video in plan.md, creating individual scenes in script.py, rendering them, and joining the clips into final.mp4.

When it helps

Use it when equations alone do not communicate a mathematical idea clearly, or when you need to show the order of a process visually. The workflow considers showing geometry before equations, along with colors, text sizes, and pauses between animations. This lets you build educational material or explanations of research one scene at a time, with attention to both the structure of the explanation and its visual presentation.

Example requests

  • “Make a video that explains Fourier series through moving shapes.”
  • “Show this algorithm running, including changes to its data structures.”
  • “Explain the main findings of this paper with animation.”

Notes

Python 3.10 or later, Manim Community Edition v0.20 or later, LaTeX, and ffmpeg are required. Linux, macOS, and Windows are supported; no GPU is needed. Narration is optional, with configurations using ElevenLabs or Qwen3-TTS described.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodThe material explicitly names mathematical explanations, equation derivations, and algorithm visualization, with video as the output.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodThe workflow specifies plan.md, script.py, rendering commands, and assembly into final.mp4.
SafetyAre sending data, deleting files, and running commands disclosed?
BPartly lackingThe material requires running scripts/setup.sh but does not include the script's operations.
Easy setupDoes it need few tools or API keys, and are they documented?
AGoodRequired Python and Manim versions, LaTeX, ffmpeg, installation examples, and a dependency-check method are provided.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (17)

  • SKILL.md11.9 KB
  • README.md886 B
  • references/animation-design-thinking.md7.0 KB
  • references/animations.md8.6 KB
  • references/camera-and-3d.md4.0 KB
  • references/decorations.md4.9 KB
  • references/equations.md5.9 KB
  • references/graphs-and-data.md4.5 KB
  • references/mobjects.md9.5 KB
  • references/paper-explainer.md9.1 KB
  • references/production-quality.md5.8 KB
  • references/rendering.md5.2 KB
  • references/scene-planning.md2.7 KB
  • references/troubleshooting.md4.2 KB
  • references/updaters-and-trackers.md8.3 KB
  • references/visual-design.md4.7 KB
  • scripts/setup.sh921 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Manim Video Production Pipeline

When to use

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.

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

ModeInputOutputReference
Concept explainerTopic/conceptAnimated explanation with geometric intuitionreferences/scene-planning.md
Equation derivationMath expressionsStep-by-step animated proofreferences/equations.md
Algorithm visualizationAlgorithm descriptionStep-by-step execution with data structuresreferences/graphs-and-data.md
Data storyData/metricsAnimated charts, comparisons, countersreferences/graphs-and-data.md
Architecture diagramSystem descriptionComponents building up with connectionsreferences/mobjects.md
Paper explainerResearch paperKey findings and methods animatedreferences/scene-planning.md
3D visualization3D conceptRotating surfaces, parametric curves, spatial geometryreferences/camera-and-3d.md

Stack

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

LayerToolPurpose
CoreManim Community EditionScene rendering, animation engine
MathLaTeX (texlive/MiKTeX)Equation rendering via MathTex
Video I/OffmpegScene stitching, format conversion, audio muxing
TTSElevenLabs / 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

PaletteBackgroundPrimarySecondaryAccentUse case
Classic 3B1B#1C1C1C#58C4DD (BLUE)#83C167 (GREEN)#FFFF00 (YELLOW)General math/CS
Warm academic#2D2B55#FF6B6B#FFD93D#6BCB77Approachable
Neon tech#0A0A0A#00F5FF#FF00FF#39FF14Systems, architecture
Monochrome#1A1A2E#EAEAEA#888888#FFFFFFMinimalist

Animation Speed

Contextrun_timeself.wait() after
Title/intro appear1.5s1.0s
Key equation reveal2.0s2.0s
Transform/morph1.5s1.5s
Supporting label0.8s0.5s
FadeOut cleanup0.5s0.3s
"Aha moment" reveal2.5s3.0s

Typography Scale

RoleFont sizeUsage
Title48Scene titles, opening text
Heading36Section headers within a scene
Body30Explanatory text
Label24Annotations, axis labels
Caption20Subtitles, 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

QualityResolutionFPSSpeed
-ql (draft)854x480155-15s/scene
-qm (medium)1280x7203015-60s/scene
-qh (production)1920x10806030-120s/scene

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

References

FileContents
references/animations.mdCore animations, rate functions, composition, .animate syntax, timing patterns
references/mobjects.mdText, shapes, VGroup/Group, positioning, styling, custom mobjects
references/visual-design.md12 design principles, opacity layering, layout templates, color palettes
references/equations.mdLaTeX in Manim, TransformMatchingTex, derivation patterns
references/graphs-and-data.mdAxes, plotting, BarChart, animated data, algorithm visualization
references/camera-and-3d.mdMovingCameraScene, ThreeDScene, 3D surfaces, camera control
references/scene-planning.mdNarrative arcs, layout templates, scene transitions, planning template
references/rendering.mdCLI reference, quality presets, ffmpeg, voiceover workflow, GIF export
references/troubleshooting.mdLaTeX errors, animation errors, common mistakes, debugging
references/animation-design-thinking.mdWhen to animate vs show static, decomposition, pacing, narration sync
references/updaters-and-trackers.mdValueTracker, add_updater, always_redraw, time-based updaters, patterns
references/paper-explainer.mdTurning research papers into animations — workflow, templates, domain patterns
references/decorations.mdSurroundingRectangle, Brace, arrows, DashedLine, Angle, annotation lifecycle
references/production-quality.mdPre-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

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