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/manim-video

Manim CE animations: 3Blue1Brown math/algo videos.

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hermes-agent
246k58 skills
Install
$ npx -y skills add NousResearch/hermes-agent --skill manim-video --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/manim-video

Context preview

The summary Claude sees to decide when to auto-load this skill.

Manim CE animations: 3Blue1Brown math/algo videos.

SKILL.md

manim-video.SKILL.md
name: manim-video
description: "Manim CE animations: 3Blue1Brown math/algo videos."
version: 1.0.0
author: SHL0MS, Hermes Agent
license: MIT
platforms: [linux, macos, windows]
metadata:
  hermes:
    tags: [Manim, Animation, Math, Video]
    related_skills: []

Manim Video Production Pipeline

When to use

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.

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

1. **PLAN** — Write `plan.md` with narrative arc, scene list, visual elements, color palette, voiceover script 2. **CODE** — Write `script.py` with one class per scene, each independently renderable 3. **RENDER** — `manim -ql script.py Scene1 Scene2 ...` for draft, `-qh` for production 4. **STITCH** — ffmpeg concat of scene clips into `final.mp4` 5. **AUDIO** (optional) — Add voiceover and/or background music via ffmpeg. See `references/rendering.md` 6. **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 proportion

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The self-improving AI agent built by Nous Research. It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a

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