Manim Skills is a collection of agent instructions, examples, and practices for creating mathematical animations with Manim Community Edition or ManimGL, the animation framework associated with 3Blue1Brown. It helps agents produce educational and mathematical videos while accounting for the two incompatible Manim variants; the catalogue skills provide those workflows.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add adithya-s-k/manim_skill --skill manim-composergit clone --depth 1 https://github.com/adithya-s-k/manim_skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/adithya-s-k/manim_skill/manim-composer)<a href="https://agentmods.dev/skills/adithya-s-k/manim_skill/manim-composer"><img src="https://agentmods.dev/badge/skills/adithya-s-k/manim_skill/manim-composer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/adithya-s-k/manim_skill/manim-composer"><img src="https://agentmods.dev/badge/skills/adithya-s-k/manim_skill/manim-composer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00174 | $0.01090 |
| Opus 5 | $0.00087 | $0.00545 |
| Sonnet 5 | $0.00035 | $0.00218 |
| Haiku 4.5 | $0.00017 | $0.00109 |
Grade A, and why
manim-composer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- manim-composer — 94% identical, 9 lines differ
- manim-composer — 92% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow
Phase 1: Understand the Concept
-
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
-
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]
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 139 lines · 174 tokens per session scan A 79e7c224fa89
manim-composer is a skill published in the GitHub repository adithya-s-k/manim_skill (1,102 stars, last pushed 7mo ago), licensed MIT. It adds 174 tokens to every session and 1,090 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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