manim-video▌
browser-use/video-use · updated Jun 11, 2026
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Production pipeline for creating mathematical animations with Manim.
| 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
| 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
- PLAN — Write
plan.mdwith narrative arc, scene list, visual elements, color palette, voiceover script - CODE — Write
script.pywith one class per scene, each independently renderable - RENDER —
manim -ql script.py Scene1 Scene2 ...for draft,-qhfor production - STITCH — ffmpeg concat of scene clips into
final.mp4 - AUDIO (optional) — Add voiceover and/or background music via ffmpeg. See
references/rendering.md - 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)orsubcaption="text"onself.play() - Shared color constants at file top for cross-scene consistency
self.camera.background_colorset 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
- List what's "standard" about how this topic is visualized (left-to-right, 2D, discrete steps, formal notation)
- Pick the most fundamental assumption
- Reverse it (right-to-left derivation, 3D embedding of a 2D concept, continuous morphing instead of steps, zero notation)
- Explore what the reversal reveals that the standard approach hides
How to use manim-video on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add manim-video
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches manim-video from GitHub repository browser-use/video-use and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate manim-video. Access the skill through slash commands (e.g., /manim-video) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★57 reviews- ★★★★★Dev Kim· Dec 24, 2024
manim-video has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Daniel Flores· Dec 16, 2024
manim-video fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dev Park· Dec 8, 2024
We added manim-video from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Zaid Choi· Dec 8, 2024
Solid pick for teams standardizing on skills: manim-video is focused, and the summary matches what you get after install.
- ★★★★★Zaid Sethi· Dec 4, 2024
Keeps context tight: manim-video is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diego Yang· Nov 27, 2024
Keeps context tight: manim-video is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakshi Patil· Nov 23, 2024
manim-video has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Zara Mehta· Nov 23, 2024
We added manim-video from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Daniel Farah· Nov 7, 2024
manim-video is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chinedu Garcia· Nov 3, 2024
Solid pick for teams standardizing on skills: manim-video is focused, and the summary matches what you get after install.
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