通过1Password CLI,将保存的密码和API密钥用于命令及配置模板,完成安装、认证、秘密值读取,并通过环境变量向命令传递凭据。
- 安装并配置1Password CLI
- 使用已保存的API密钥运行命令
- 向配置模板填入秘密值
将数学概念、公式推导和算法执行过程制作成动画解说视频。使用Manim Community Edition,从内容规划、场景绘制到视频拼接,以图形辅助理解。
Manim CE animations: 3Blue1Brown math/algo videos.
使用Manim Community Edition,将数学和技术内容制作成图形与公式动态呈现的解说视频。可表现概念、公式推导、算法执行过程、数据比较、系统架构图和三维形状。流程包括在plan.md中整理内容结构,在script.py中创建各个场景,渲染后将片段拼接成final.mp4。
适合仅靠公式难以讲清数学思路,或需要直观展示处理顺序的情况。制作时会考虑先展示图形再引入公式,并安排配色、文字大小和停顿,便于逐个场景组织教材或研究内容的讲解。
需要Python 3.10或更高版本、Manim Community Edition v0.20或更高版本、LaTeX和ffmpeg。支持Linux、macOS和Windows,无需GPU。旁白为可选项,资料介绍了使用ElevenLabs或Qwen3-TTS的配置。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。
总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月19日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
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. Creates 3Blue1Brown-style explainer videos, algorithm visualizations, equation derivations, architecture diagrams, and data stories using Manim Community Edition.
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.
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.
| 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 |
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 |
PLAN --> CODE --> RENDER --> STITCH --> AUDIO (optional) --> REVIEW
plan.md with narrative arc, scene list, visual elements, color palette, voiceover scriptscript.py with one class per scene, each independently renderablemanim -ql script.py Scene1 Scene2 ... for draft, -qh for productionfinal.mp4references/rendering.mdproject-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/
| 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 |
| 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 |
| 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 |
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.
Never use identical config for all scenes. For each scene:
Before any code, write plan.md. See references/scene-planning.md for the comprehensive template.
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:
self.add_subcaption("text", duration=N) or subcaption="text" on self.play()self.camera.background_color set in every sceneself.play(FadeOut(Group(*self.mobjects)))manim -ql script.py Scene1_Introduction Scene2_CoreConcept # draft
manim -qh script.py Scene1_Introduction Scene2_CoreConcept # production
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
manim -ql --format=png -s script.py Scene2_CoreConcept # preview still
# WRONG: MathTex("\frac{1}{2}")
# RIGHT:
MathTex(r"\frac{1}{2}")
label.to_edge(DOWN, buff=0.5) # never < 0.5
self.play(ReplacementTransform(note1, note2)) # not Write(note2) on top
self.play(Create(circle)) # must add first
self.play(circle.animate.set_color(RED)) # then animate
| 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.
| 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 |
If the user asks for creative, experimental, or unconventional explanatory approaches, select a strategy and reason through it BEFORE designing the animation.
Take a standard mathematical/technical visualization and transform it:
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通过1Password CLI,将保存的密码和API密钥用于命令及配置模板,完成安装、认证、秘密值读取,并通过环境变量向命令传递凭据。
创建用公式联动利润表、资产负债表和现金流量表的 Excel 模型,分阶段填入历史实际数据与预测假设,比较不同情景,并检查三张报表之间的一致性。
以少量修改让现有PyTorch训练代码适用于多GPU或多台机器,指导混合精度、节省内存的DeepSpeed与FSDP配置,以及训练启动方法。
帮助配置Hermes,通过Actual Computer在自己的设备上运行AI模型。支持加密中继与本地连接,涵盖模型选择、响应测试,以及请求报错或空响应的排查。
扮演不擅长技术、容易不满的用户测试应用,发现难懂的操作和导致放弃使用的障碍。将实际可改进的问题与个人抱怨分开,整理截图、修复建议和任务单。
从中立立场解决两个智能体分别修改代码产生的Git冲突,对照双方差异和意图,记录每处冲突的取舍理由,并通过构建或测试验证合并结果。