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Manim composer

Skill adithya-s-k/manim_skill/skills/manim-composer

Trigger when: (1) User wants to create an educational/explainer video, (2) User has a vague concept they want visualized, (3) User mentions "3b1b style" or "explain like 3Blue1Brown", (4) User wants to plan a Manim video or animation sequence, (5) User asks to "compose" or "plan" a math/science visualization. Transforms vague video ideas into detailed scene-by-scene plans (scenes.md). Conducts research, asks clarifying questions about audience/scope/focus, and outputs comprehensive scene specifications ready for implementation with ManimCE or ManimGL. Use this BEFORE writing any Manim code. This skill plans the video; use manimce-best-practices or manimgl-best-practices for implementation.From its SKILL.md

Install
npx -y skills add adithya-s-k/manim_skill --skill manim-composer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

4.6 KB, 907 tokens by cl100k_base, as published. Nobody here has run it

Workflow

Phase 1: Understand the Concept

  1. Research the topic deeply before asking questions

    • Use web search to understand the core concepts
    • Identify the key insights that make this topic interesting
    • Find the "aha moment" - what makes this click for learners
    • Note common misconceptions to address
  2. Identify the narrative hook

    • What question does this video answer?
    • Why should the viewer care?
    • What's the surprising or counterintuitive element?

Phase 2: Clarify with User

Ask targeted questions (not all at once - adapt based on responses):

Audience & Scope

  • What math/science background should I assume? (e.g., "knows calculus" or "high school algebra")
  • Target video length? (short: 5-10min, medium: 15-20min, long: 30min+)
  • Should this be self-contained or part of a series?

Focus & Depth

  • Any specific aspects to emphasize or skip?
  • Proof-heavy or intuition-focused?
  • Real-world applications to include?

Style Preferences

  • Color scheme preferences?
  • Narration style? (casual, formal, playful)
  • Any specific visual metaphors you have in mind?

Phase 3: Create scenes.md

Output a comprehensive scenes.md file with this structure:

# [Video Title]

## Overview
- **Topic**: [Core concept]
- **Hook**: [Opening question/mystery]
- **Target Audience**: [Prerequisites]
- **Estimated Length**: [X minutes]
- **Key Insight**: [The "aha moment"]

## Narrative Arc
[2-3 sentences describing the journey from confusion to understanding]

---

## Scene 1: [Scene Name]
**Duration**: ~X seconds
**Purpose**: [What this scene accomplishes]

### Visual Elements
- [List of mobjects needed]
- [Animations to use]
- [Camera movements]

### Content
[Detailed description of what happens, what's shown, what's explained]

### Narration Notes
[Key points to convey, tone, pacing notes]

### Technical Notes
- [Specific Manim classes/methods to use]
- [Any tricky implementations to note]

---

## Scene 2: [Scene Name]
...

---

## Transitions & Flow
[Notes on how scenes connect, recurring visual motifs]

## Color Palette
- Primary: [color] - used for [purpose]
- Secondary: [color] - used for [purpose]
- Accent: [color] - used for [purpose]
- Background: [color]

## Mathematical Content
[List of equations, formulas, or mathematical objects that need to be rendered]

## Implementation Order
[Suggested order for implementing scenes, noting dependencies]

3b1b Style Principles

Apply these principles when composing scenes:

Visual Storytelling

  • Show, don't just tell - Every concept needs a visual representation
  • Progressive revelation - Build complexity gradually, don't show everything at once
  • Visual continuity - Transform objects rather than replacing them when possible

Pacing & Rhythm

  • Pause for insight - Give viewers time to absorb key moments
  • Vary the pace - Mix quick sequences with slower explanations
  • End scenes with resolution - Each scene should feel complete

Mathematical Beauty

  • Emphasize elegance - Highlight when math is surprisingly simple or beautiful
  • Connect representations - Show the same concept multiple ways (algebraic, geometric, intuitive)
  • Embrace abstraction gradually - Start concrete, then generalize

Engagement Techniques

  • Pose questions - Make viewers curious before revealing answers
  • Acknowledge difficulty - "This might seem confusing at first..."
  • Celebrate insight - Make the "aha moment" feel earned

References

Templates

What ships with it: 4 files

17.7 KB alongside SKILL.md

templates/

Gives 0 of the 12 instructions most explainers skills give in 907 tokens

Counted across 274 of the 289 authors here whose files we hold, read 2026-09-06

  • Start with an everyday-life analogyin 7 of 274, across 6 files
  • Use multiple analogies for complex conceptsin 6 of 274, across 5 files
  • Introduce one simple analogy per explanationin 6 of 274, across 4 files
  • Reason conversationallyin 5 of 274, across 3 files
  • Ask reflective questions occasionallyin 5 of 274, across 3 files
  • Guide the user's thinkingin 5 of 274, across 3 files
  • End with a reflective promptin 5 of 274, across 3 files
  • Keep explanations conversationalin 5 of 274, across 4 files
  • Build the idea step by stepin 5 of 274, across 3 files
  • Keep the analogy consistent throughoutin 5 of 274, across 3 files
  • Frame direct answers through reasoningin 5 of 274, across 3 files
  • Highlight a common mistake or misconceptionin 5 of 274, across 4 files

Said here and by no other author read

  • Research the topic before asking questions
  • Identify the narrative hook
  • Ask clarifying questions about audience, scope, and style
  • Adapt questions based on user responses
  • Plan before writing any Manim code
  • Write a comprehensive scenes.md file

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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