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Manim Video Production

Free

Create engaging mathematical animations effortlessly.

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Free · Opens the source repo

What Manim Video Production does

The Manim Video Production skill provides a structured pipeline for creating high-quality mathematical and technical animations, particularly in the style of 3Blue1Brown. This skill is designed for educators, content creators, and anyone needing to visualize complex concepts through engaging animations. By following a clear workflow, users can transform abstract ideas into visually appealing narratives that enhance understanding and retention.

At its core, the skill emphasizes the importance of narrative in educational content. Before diving into coding, users are encouraged to outline the learning objectives and the visual story they want to tell. This approach ensures that every animation serves a pedagogical purpose, guiding viewers from confusion to clarity. With a focus on visual memory, the skill advocates for presenting geometric shapes before introducing algebraic expressions, making the learning process more intuitive.

The production pipeline is straightforward, consisting of planning, coding, rendering, and reviewing stages. Users begin by drafting a plan that includes the narrative arc and visual elements. The coding phase involves creating a Python script using the Manim Community Edition, where each scene is modular and can be rendered independently. The final output is generated by stitching together the rendered scenes, with optional audio narration for added engagement. The skill also provides detailed guidance on color palettes, typography, and animation timing to ensure a cohesive visual language throughout the project.

Whether you're creating explainer videos for a classroom, visualizing algorithms, or producing content for social media, this skill equips you with the tools and best practices to produce professional-grade animations that effectively communicate complex ideas.

When to use it

Use this skill when you need to produce educational animations that explain mathematical or technical concepts clearly and engagingly.

When not to use it

This skill may not be suitable for general-purpose video editing or non-educational content that doesn't require mathematical visualization.

What you can build with it

Creating Educational Videos

Use the Manim Video Production skill to develop explainer videos for classroom settings, making complex topics more accessible.

Visualizing Algorithms

Generate step-by-step algorithm visualizations that help viewers understand data structures and processes in real-time.

Producing Research Paper Summaries

Transform key findings from research papers into animated summaries that highlight important concepts and methods.

How to install Manim Video Production

View source

1. Install with the skills CLI

npx skills add browser-use/video-use/manim-video --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by browser-use

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

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. RENDERmanim -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

Frequently asked questions about Manim Video Production

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