Manim Video
- 4.5k installs
- 238k repo stars
- Updated August 5, 2026
- affaan-m/everything-claude-code
manim-video is an agent skill for build reusable manim explainers for technical concepts, graphs, and system diagrams with render handoff.
About
The manim-video skill Build reusable Manim explainers for technical concepts, graphs, system diagrams, and product walkthroughs, then hand off to the wider ECC video stack if needed. Use when the user wants a clean animated explainer rather than a generic talking-head script. Use Manim for technical explainers where motion, structure, and clarity matter more than photorealism. - the user wants a technical explainer animation - the concept is a graph, workflow, architecture, metric progression, or system diagram - the user wants a short product or launch explainer for X or a landing page - the visual should feel precise instead of generically cinematic - manim CLI for scene rendering - ffmpeg for post-processing if needed - video-editing for final assembly or polish - remotion-video-creation when the final package needs composited UI, captions, or additional motion layers - short 16:9 MP4 - one thumbnail or poster frame - storyboard plus scene plan
- the user wants a technical explainer animation
- the concept is a graph, workflow, architecture, metric progression, or system diagram
- the user wants a short product or launch explainer for X or a landing page
- the visual should feel precise instead of generically cinematic
- manim CLI for scene rendering
Manim Video by the numbers
- 4,461 all-time installs (skills.sh)
- +256 installs in the week ending Aug 4, 2026 (Skillselion tracking)
- Ranked #115 of 1,335 Generative Media skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
manim-video capabilities & compatibility
- Capabilities
- the user wants a technical explainer animation · the concept is a graph, workflow, architecture, · the user wants a short product or launch explain · the visual should feel precise instead of generi · manim cli for scene rendering
- Use cases
- video generation · presentations
What manim-video says it does
Use Manim for technical explainers where motion, structure, and clarity matter more than photorealism.
1. Define the core visual thesis in one sentence.
2. Break the concept into 3 to 6 scenes.
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| Installs | 4.5k |
|---|---|
| repo stars | ★ 238k |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 5, 2026 |
| Repository | affaan-m/everything-claude-code ↗ |
How do I build reusable manim explainers for technical concepts, graphs, and system diagrams with render handoff with documented agent guidance?
Build reusable Manim explainers for technical concepts, graphs, and system diagrams with render handoff.
Who is it for?
Developers who need generative media help during build work.
Skip if: Skip when the task falls outside Generative Media scope described in SKILL.md.
When should I use this skill?
Build reusable Manim explainers for technical concepts, graphs, and system diagrams with render handoff.
What you get
Completed generative media workflow aligned with SKILL.md steps and validation.
- Manim Scene Python script
- Rendered animated video
By the numbers
- the user wants a technical explainer animation
- the concept is a graph, workflow, architecture, metric progression, or system diagram
- the user wants a short product or launch explainer for X or a landing page
Files
Manim Video
Use Manim for technical explainers where motion, structure, and clarity matter more than photorealism.
When to Activate
- the user wants a technical explainer animation
- the concept is a graph, workflow, architecture, metric progression, or system diagram
- the user wants a short product or launch explainer for X or a landing page
- the visual should feel precise instead of generically cinematic
Tool Requirements
manimCLI for scene renderingffmpegfor post-processing if neededvideo-editingfor final assembly or polishremotion-video-creationwhen the final package needs composited UI, captions, or additional motion layers
Default Output
- short 16:9 MP4
- one thumbnail or poster frame
- storyboard plus scene plan
Workflow
1. Define the core visual thesis in one sentence. 2. Break the concept into 3 to 6 scenes. 3. Decide what each scene proves. 4. Write the scene outline before writing Manim code. 5. Render the smallest working version first. 6. Tighten typography, spacing, color, and pacing after the render works. 7. Hand off to the wider video stack only if it adds value.
Scene Planning Rules
- each scene should prove one thing
- avoid overstuffed diagrams
- prefer progressive reveal over full-screen clutter
- use motion to explain state change, not just to keep the screen busy
- title cards should be short and loaded with meaning
Network Graph Default
For social-graph and network-optimization explainers:
- show the current graph before showing the optimized graph
- distinguish low-signal follow clutter from high-signal bridges
- highlight warm-path nodes and target clusters
- if useful, add a final scene showing the self-improvement lineage that informed the skill
Render Conventions
- default to 16:9 landscape unless the user asks for vertical
- start with a low-quality smoke test render
- only push to higher quality after composition and timing are stable
- export one clean thumbnail frame that reads at social size
Reusable Starter
Use assets/network_graph_scene.py as a starting point for network-graph explainers.
Example smoke test:
manim -ql assets/network_graph_scene.py NetworkGraphExplainerOutput Format
Return:
- core visual thesis
- storyboard
- scene outline
- render plan
- any follow-on polish recommendations
Related Skills
video-editingfor final polishremotion-video-creationfor motion-heavy post-processing or compositingcontent-enginewhen the animation is part of a broader launch
from manim import DOWN, LEFT, RIGHT, UP, Circle, Create, FadeIn, FadeOut, Scene, Text, VGroup, CurvedArrow
class NetworkGraphExplainer(Scene):
def construct(self):
title = Text("Connections Optimizer", font_size=40).to_edge(UP)
subtitle = Text("Prune low-signal follows. Strengthen warm paths.", font_size=20).next_to(title, DOWN)
you = Circle(radius=0.45, color="#4F8EF7").shift(LEFT * 4 + DOWN * 0.5)
you_label = Text("You", font_size=22).move_to(you.get_center())
stale_a = Circle(radius=0.32, color="#7A7A7A").shift(LEFT * 1.6 + UP * 1.2)
stale_b = Circle(radius=0.32, color="#7A7A7A").shift(LEFT * 1.2 + DOWN * 1.4)
bridge = Circle(radius=0.38, color="#21A179").shift(RIGHT * 0.2 + UP * 0.2)
target = Circle(radius=0.42, color="#FF9F1C").shift(RIGHT * 3.2 + UP * 0.7)
new_target = Circle(radius=0.42, color="#FF9F1C").shift(RIGHT * 3.0 + DOWN * 1.4)
stale_a_label = Text("stale", font_size=18).move_to(stale_a.get_center())
stale_b_label = Text("noise", font_size=18).move_to(stale_b.get_center())
bridge_label = Text("bridge", font_size=18).move_to(bridge.get_center())
target_label = Text("target", font_size=18).move_to(target.get_center())
new_target_label = Text("add", font_size=18).move_to(new_target.get_center())
edge_stale_a = CurvedArrow(you.get_right(), stale_a.get_left(), angle=0.2, color="#7A7A7A")
edge_stale_b = CurvedArrow(you.get_right(), stale_b.get_left(), angle=-0.2, color="#7A7A7A")
edge_bridge = CurvedArrow(you.get_right(), bridge.get_left(), angle=0.0, color="#21A179")
edge_target = CurvedArrow(bridge.get_right(), target.get_left(), angle=0.1, color="#21A179")
edge_new_target = CurvedArrow(bridge.get_right(), new_target.get_left(), angle=-0.12, color="#21A179")
self.play(FadeIn(title), FadeIn(subtitle))
self.play(
Create(you),
FadeIn(you_label),
Create(stale_a),
Create(stale_b),
Create(bridge),
Create(target),
FadeIn(stale_a_label),
FadeIn(stale_b_label),
FadeIn(bridge_label),
FadeIn(target_label),
)
self.play(Create(edge_stale_a), Create(edge_stale_b), Create(edge_bridge), Create(edge_target))
optimize = Text("Optimize the graph", font_size=24).to_edge(DOWN)
self.play(FadeIn(optimize))
self.play(FadeOut(stale_a), FadeOut(stale_b), FadeOut(stale_a_label), FadeOut(stale_b_label), FadeOut(edge_stale_a), FadeOut(edge_stale_b))
self.play(Create(new_target), FadeIn(new_target_label), Create(edge_new_target))
final_group = VGroup(you, you_label, bridge, bridge_label, target, target_label, new_target, new_target_label)
self.play(final_group.animate.shift(UP * 0.1))
self.wait(1)
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Manim Video has 1 known copy in the catalog totaling 1.4k installs. They canonicalize to this original listing.
- affaan-m - 1.4k installs
How it compares
manim-video is an agent skill for build reusable manim explainers for technical concepts, graphs, and system diagrams with render handoff, not a generic alternative.
FAQ
Who is manim-video for?
Developers using Generative Media workflows with agent-guided SKILL.md steps.
When should I use manim-video?
Build reusable Manim explainers for technical concepts, graphs, and system diagrams with render handoff.
Is manim-video safe to install?
Review the Security Audits panel on this page before installing in production.