Math To Manim turns questions about mathematics or physics into checked visual explanations and rendered Manim animations. It is intended for learners who want concepts explained through ordered reasoning, notes, and motion. Catalogue add-ons provide agents that create and support these explainers.
Borrowing it
Nothing to install: this file belongs to HarleyCoops/Math-To-Manim. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/HarleyCoops/Math-To-Manim/main/legacy/Math-To-Manim/.github/instructions/examples.instructions.mdgit clone --depth 1 https://github.com/HarleyCoops/Math-To-ManimWrote 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/instructions/harleycoops/math-to-manim/examples)<a href="https://agentmods.dev/instructions/harleycoops/math-to-manim/examples"><img src="https://agentmods.dev/badge/instructions/harleycoops/math-to-manim/examples/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/instructions/harleycoops/math-to-manim/examples"><img src="https://agentmods.dev/badge/instructions/harleycoops/math-to-manim/examples.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.01784 | $0.01784 |
| Opus 5.5 | $0.00714 | $0.00714 |
| Sonnet 5.5 | $0.00357 | $0.00357 |
| Haiku 4.5 | $0.00178 | $0.00178 |
Grade A, and why
Math-To-Manim examples.instructions.md 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Animation Examples Guidelines
Purpose
This directory contains 55+ working Manim animations demonstrating various mathematical, physical, and computational concepts. Each animation serves as both a working example and educational reference.
Creating New Animation Examples
File Organization
- Place animations in the appropriate category directory:
examples/physics/- Physics concepts (quantum, gravity, nuclear, particle physics)examples/mathematics/- Math concepts (geometry, analysis, fractals, statistics)examples/computer_science/- CS concepts (ML, algorithms, spatial reasoning)examples/cosmology/- Cosmology and astrophysicsexamples/finance/- Financial mathematicsexamples/misc/- Experimental or uncategorized
Naming Conventions
- Use descriptive, lowercase names with underscores:
schrodinger_equation.py, notscene1.py - Name should clearly indicate the concept being visualized
- Scene class name should be descriptive and in PascalCase:
SchrodingerEquationScene
Required Components
- Module Docstring: Every animation file must start with a comprehensive docstring:
"""
Visualization of the Schrödinger equation in quantum mechanics.
Shows:
- Wave function evolution
- Probability density interpretation
- Energy eigenstates
- Potential well scenarios
Mathematical Concepts:
- Time-independent Schrödinger equation: Hψ = Eψ
- Time-dependent form: iℏ ∂ψ/∂t = Hψ
- Wave function normalization
- Expectation values
Generated using: Claude Sonnet 4.5 / DeepSeek R1 / etc.
"""
- Import Organization:
from manim import *
import numpy as np
# Other standard library imports
# Then project-specific imports if needed
- Scene Class with Docstring:
class SchrodingerEquationScene(Scene):
"""
Main scene for Schrödinger equation visualization.
Demonstrates wave function evolution in a potential well.
"""
def construct(self):
# Implementation
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.
- 1mo ago First seen · 223 lines · 1,784 tokens per session scan A 87d953d5db20
Math-To-Manim examples.instructions.md is an instructions file published in the GitHub repository HarleyCoops/Math-To-Manim (2,804 stars, last pushed 2d ago), licensed MIT. It adds 1,784 tokens to every session, about $0.0071 per session on Opus 5.5. 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.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.