manim-video
affaan-m/ECC
使用 Manim 制作动画技术讲解视频,用于展示图表、工作流程、系统图和产品演示,实现精准的动态效果和清晰的场景规划。
...展开全部Manim 视频
在制作技术类讲解视频时,若动态效果、结构和清晰度比逼真度更为重要,请使用 Manim。
何时启用
- 用户需要制作技术讲解动画时
- 概念涉及图表、工作流程、架构、指标变化或系统图
- 用户需要为 X 制作简短的产品或发布说明动画,或用于着陆页
- 视觉效果应给人以精准而非泛泛的电影感
工具要求
manim用于场景渲染的命令行工具ffmpeg如有需要,用于后期处理video-editing用于最终合成或润色remotion-video-creation当最终成片需要合成UI、字幕或额外动态图层时
默认输出格式
- 16:9 短版 MP4
- 一张缩略图或海报帧
- 分镜脚本加场景规划
工作流程
- 用一句话定义核心视觉主张。
- 将概念分解为3至6个场景。
- 确定每个场景要阐明什么。
- 在编写 Manim 代码之前,先撰写场景大纲。
- 先渲染最简的可运行版本。
- 在渲染效果稳定后,进一步优化排版、间距、色彩和节奏。
- 仅当能带来附加价值时,才将其移交至更广泛的视频处理流程。
场景规划规则
- 每个场景应只证明一件事
- 避免图表内容过于冗杂
- 优先采用渐进式展示,而非满屏杂乱
- 利用动态效果来阐释状态变化,而非仅仅为了让画面显得繁忙
- 标题卡应简短且寓意深远
网络图默认样式
针对社交图谱和网络优化类讲解内容:
- 先展示当前图,再展示优化后的图
- 区分信号微弱的冗余连接与信号强烈的连接桥梁
- 突出显示“暖路径”节点和目标聚类
- 如有必要,添加一个最终场景,展示为该技能提供依据的自我提升脉络
渲染规范
- 除非用户要求竖屏模式,否则默认采用16:9横屏模式
- 首先进行低质量的初步测试渲染
- 仅在合成和时间轴稳定后才提升渲染质量
- 导出一张符合社交媒体尺寸的清晰缩略图帧
可复用的启动模板
将 assets/network_graph_scene.py 作为网络图解释性视频的起点。
烟雾测试示例:
manim -ql assets/network_graph_scene.py NetworkGraphExplainer
输出格式
返回:
- 核心视觉概念
- 故事板
- 场景大纲
- 渲染方案
- 后续润色建议
相关技能
video-editing用于最终润色remotion-video-creation适用于动作密集型后期处理或合成content-engine当动画是更广泛发布活动的一部分时
---
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
安装 manim-video
下载技能文件并将其解压到 .claude/skills/ 目录中。
下载ZIP克隆仓库并复制技能文件到您的项目中。
git clone https://github.com/affaan-m/ECC/tree/main/skills/manim-video # Copy SKILL.md to your .claude/skills/ directory
复制





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