awesome-math-prompts

The ultimate prompt engineering toolkit for mathematical operations

Stop wrestling with LLMs! awesome-math-prompts generates perfectly crafted, production-ready prompts that guarantee accurate mathematical results from any language model.

Why This Is The Best Math Prompt Library

✨ Precision Engineered - Every prompt is meticulously designed by mathematicians and prompt engineers to deliver consistent, accurate results

⚡ Zero Configuration - Just call a function, get a world-class prompt. No setup, no fluff.

🎯 Battle Tested - These prompts have been optimized through thousands of LLM interactions to handle edge cases, invalid inputs, and ambiguous scenarios

🚀 Universal Compatibility - Works with OpenAI, Anthropic, Google, and any LLM that eats text prompts

Installation

npm install awesome-math-prompts

Usage

import { add, subtract, multiply, divide, factorial, fibonacci, isPrime, sqr, randomBtw } from 'awesome-math-prompts';

// Get a ready-to-use prompt for any math operation
const prompt = add(15, 27);
// Returns a fully-formatted prompt that any LLM will understand and execute correctly

// Send the prompt to your LLM
const result = await openai.chat.completions.create({
  messages: [{ role: "user", content: prompt }],
  model: "gpt-4"
});
// Result: "42"

API Reference

All functions return a string containing a complete, production-ready prompt.

Function	Parameters	Description
add(a, b)	number, number	Generate a prompt for addition
subtract(a, b)	number, number	Generate a prompt for subtraction
multiply(a, b)	number, number	Generate a prompt for multiplication
divide(a, b)	number, number	Generate a prompt for division
factorial(n)	number	Generate a prompt for factorial calculation
fibonacci(n)	number	Generate a prompt for Fibonacci sequence
isPrime(n)	number	Generate a prompt to check if number is prime
isEven(n)	number	Generate a prompt to check if number is even
sqr(n)	number	Generate a prompt for square root calculation
randomBtw(a, b)	number, number	Generate a prompt for random integer generation

Features

• Input Validation Built-In - Prompts explicitly tell the LLM how to handle invalid inputs
• Error Handling - Standardized error response format across all operations
• Edge Case Coverage - Division by zero, negative factorials, invalid ranges — handled
• Type Safety - Full TypeScript support with proper type definitions
• Zero Dependencies - Lightweight, no runtime dependencies

How It Works

Each function generates a structured prompt that:

1. Establishes the LLM's role as a mathematics expert
2. Clearly defines the expected input format
3. Specifies validation rules and error handling
4. Provides concrete examples
5. Formats the actual operation to perform

License

MIT