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
manim CLI for scene renderingffmpeg for post-processing if neededvideo-editing for final assembly or polishremotion-video-creation when 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
- Define the core visual thesis in one sentence.
- Break the concept into 3 to 6 scenes.
- Decide what each scene proves.
- Write the scene outline before writing Manim code.
- Render the smallest working version first.
- Tighten typography, spacing, color, and pacing after the render works.
- 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 NetworkGraphExplainer
Output Format
Return:
- core visual thesis
- storyboard
- scene outline
- render plan
- any follow-on polish recommendations
Related Skills
video-editing for final polishremotion-video-creation for motion-heavy post-processing or compositingcontent-engine when the animation is part of a broader launch
---
name: manim-video
description: Create animated technical explainers using Manim for graphs, workflows, system diagrams, and product walkthroughs with precise motion and clear scene planning.
---
# 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
- `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
## 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](assets/network_graph_scene.py) as a starting point for network-graph explainers.
Example smoke test:
```bash
manim -ql assets/network_graph_scene.py NetworkGraphExplainer
```
## Output Format
Return:
- core visual thesis
- storyboard
- scene outline
- render plan
- any follow-on polish recommendations
## Related Skills
- `video-editing` for final polish
- `remotion-video-creation` for motion-heavy post-processing or compositing
- `content-engine` when the animation is part of a broader launch
