Generate Mongoose Schema for MongoDB Collections

Use this AI prompt to generate MongoDB Mongoose schemas with validation, indexes, timestamps, and references between collections for scalable data modeling.

🧠 What This Prompt Does

This prompt helps you generate a complete MongoDB schema using Mongoose.
It includes field types, default values, validation rules, and timestamps — ideal for rapid data modeling.

💬 The Prompt

You are a MongoDB expert.
Generate a Mongoose schema for the given collection.

Requirements:

- Include data types, validation, and required fields
- Add timestamps and indexes
- Support relationships via ObjectId references
- Provide model export

Collection:
{{collection_name}}

⚙️ Example Input

{
  "collection_name": "User with fields name, email, password, role, and posts reference"
}

🚀 Example Output (AI Generated)

import mongoose from 'mongoose';

const userSchema = new mongoose.Schema(
  {
    name: { type: String, required: true, trim: true },
    email: { type: String, required: true, unique: true },
    password: { type: String, required: true },
    role: { type: String, enum: ['admin', 'user'], default: 'user' },
    posts: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Post' }],
  },
  { timestamps: true }
);

userSchema.index({ email: 1 });

export default mongoose.model('User', userSchema);

📘 When to Use This Prompt

• While setting up new MongoDB models.
• When normalizing or restructuring data schemas.
• To ensure strong data typing and validation.

💡 Best Practices

• Use trim and lowercase for text normalization.
• Add unique indexes for frequently queried fields.
• Use ref for relationships instead of embedding when scalable.
• Enable { timestamps: true } for consistent audit tracking.

🏁 Summary

This prompt generates production-ready Mongoose schemas for MongoDB, ensuring clean, validated, and scalable data structures.