Agent skill

Manim Video Production

by browser-use in browser-use/video-use

Produces math and technical explainer videos with Manim Community Edition: concept animations, equation derivations, algorithm walkthroughs and data stories.

MITAuto-check passedMedia & Creative

Install Manim Video Production

skills CLI
$ npx skills add browser-use/video-use --skill manim-video -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install browser-use/video-use manim-video --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/browser-use/video-use.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/manim-video .claude/skills/manim-video && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
manim-video
GitHub stars
28k
Used in
6 other repos
Token cost
~3k tokens
SKILL.md length
1,042 words
Files
17 (incl. scripts, references)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Produces math and technical explainer videos with Manim Community Edition: concept animations, equation derivations, algorithm walkthroughs and data stories.

  • Works in 5 steps: Plan (plan.md) → Code (script.py) → Render → …
  • Explaining a math or algorithm concept with an animation
  • SKILL.md covers Creative Standard, Prerequisites, Modes and Stack, plus 8 more sections
  • Runs Shell scripts from its folder; calls ffmpeg and pip

What it does

This skill turns a topic into an animated explainer in the style of 3Blue1Brown, using Manim Community Edition. It opens with creative rules: decide the narrative and the moment of insight before coding, show geometry before algebra, layer opacity so the eye knows where to look, pause after each reveal and keep one color palette and type scale across scenes.

It supports several modes, including concept explainers, step-by-step equation derivations, algorithm visualizations, animated data stories and architecture diagrams, each linked to a reference file. Further references cover cameras and 3D, equations, graphs, rendering, scene planning and troubleshooting, and a setup script checks the dependencies before the first render.

When your agent uses it

  • Explaining a math or algorithm concept with an animation
  • Animating an equation derivation step by step
  • Turning metrics into a short animated data story

Example prompts

  • “Make a short animation that shows why the Pythagorean theorem works.”
  • “Visualize how quicksort partitions an array, step by step.”
  • “Animate the derivation of the quadratic formula for my students.”

Requirements

  • Python 3.10 or later
  • Manim Community Edition v0.20 or later
  • LaTeX
  • ffmpeg

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Plan (plan.md)
  2. Code (script.py)
  3. Render
  4. Stitch
  5. Review

What it can do on your machine

Read from SKILL.md and the folder at commit 43cfc56. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • ffmpeg
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Manim Video Production loads about 3k tokens when it runs, and up to ~25k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 1,042 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~25k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from browser-use/video-use at commit 43cfc56, republished under its MIT licence (© browser-use). 1,042 words, ~2,987 tokens.

Download SKILL.mdSave it as .claude/skills/manim-video/SKILL.md (or your agent's skills folder). This skill also uses 16 other files; get the full folder from GitHub.
name
manim-video
description
Production pipeline for mathematical and technical animations using Manim Community Edition. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories. 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.
version
1.0.0

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. 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.

python
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.

Show full SKILL.md (412 more words)Show less
Step 2: Code (script.py)

One class per scene. Every scene is independently renderable.

python
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
bash
manim -ql script.py Scene1_Introduction Scene2_CoreConcept  # draft
manim -qh script.py Scene1_Introduction Scene2_CoreConcept  # production
Step 4: Stitch
bash
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
bash
manim -ql --format=png -s script.py Scene2_CoreConcept  # preview still

Critical Implementation Notes

Raw Strings for LaTeX
python
# WRONG: MathTex("\frac{1}{2}")
# RIGHT:
MathTex(r"\frac{1}{2}")
buff >= 0.5 for Edge Text
python
label.to_edge(DOWN, buff=0.5)  # never < 0.5
FadeOut Before Replacing Text
python
self.play(ReplacementTransform(note1, note2))  # not Write(note2) on top
Never Animate Non-Added Mobjects
python
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

© browser-use, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 16 other files (scripts, references) in skills/manim-video of browser-use/video-use.

  • SKILL.md
  • README.md
  • references/animation-design-thinking.md
  • references/animations.md
  • references/camera-and-3d.md
  • references/decorations.md
  • references/equations.md
  • references/graphs-and-data.md
  • references/mobjects.md
  • references/paper-explainer.md
  • references/production-quality.md
  • references/rendering.md
  • references/scene-planning.md
  • references/troubleshooting.md
  • references/updaters-and-trackers.md
  • references/visual-design.md
  • scripts/setup.sh

Open the folder on GitHubat commit 43cfc56

Used in 6 other repositories

We found 8 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 6 other GitHub owners. This page covers the copy in browser-use/video-use, which our catalogue first saw on October 7, 2026.

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Qiaomu Cutjoeseesun/qiaomu-cut-skill372—~6.8kAutomated safety check: NotesMIT
ShowtimeFavioVazquez/showtime206—~3kAutomated safety check: PassMIT

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Questions about Manim Video Production

What does Manim Video Production do?

Produces math and technical explainer videos with Manim Community Edition: concept animations, equation derivations, algorithm walkthroughs and data stories. This skill turns a topic into an animated explainer in the style of 3Blue1Brown, using Manim Community Edition. It opens with creative rules: decide the narrative and the moment of insight before coding, show geometry before algebra, layer opacity so the eye knows where to look, pause after each reveal and keep one color palette and type scale across scenes.

When should I use Manim Video Production?

Manim Video Production fits situations like: explaining a math or algorithm concept with an animation; animating an equation derivation step by step; turning metrics into a short animated data story.

How do I install Manim Video Production in Claude Code?

Run `npx skills add browser-use/video-use --skill manim-video -a claude-code`. Or copy the skill folder (skills/manim-video in browser-use/video-use) into .claude/skills/manim-video in your project. Claude Code loads it when a task matches its description.

How do I install Manim Video Production in Codex?

Run `npx skills add browser-use/video-use --skill manim-video -a codex`. Or copy the skill folder (skills/manim-video in browser-use/video-use) into .agents/skills/manim-video in your project. Codex loads it when a task matches its description.

Can I use Manim Video Production in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add browser-use/video-use --skill manim-video -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/manim-video, .gemini/skills/manim-video, .github/skills/manim-video and .opencode/skills/manim-video in your project.

What does Manim Video Production need to run?

Going by SKILL.md and its folder, Manim Video Production needs a shell for the scripts in its folder and the command-line tools its instructions call (ffmpeg and pip). Our summary lists: Python 3.10 or later; Manim Community Edition v0.20 or later; LaTeX; ffmpeg.

Does Manim Video Production access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Manim Video Production safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Manim Video Production use?

Manim Video Production is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Manim Video Production use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 22k tokens, read only when the agent opens those files.

What are the alternatives to Manim Video Production?

Skills that share tags, products or a category with Manim Video Production: Manim Explainer Videos (Prismer-AI/PrismerCloud, 1.6k stars), Manim Animation Creator (Yusuke710/manim-skill, 167 stars), Hand-Drawn Explainer Video Maker (hi-nikola/hand-drawn-explainer-video-nikola, 369 stars) and Qiaomu Cut (joeseesun/qiaomu-cut-skill, 372 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Manim Video Production?

browser-use (a GitHub organization) maintains it in browser-use/video-use, which has 28,471 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on October 8, 2026.

Source: browser-use/video-use on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.