Design scalable NoSQL schemas for MongoDB (document) and DynamoDB (key-value). Covers data modeling patterns, denormalization strategies, and query optimization for NoSQL systems.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnosql-database-designExecute the skills CLI command in your project's root directory to begin installation:
Fetches nosql-database-design from aj-geddes/useful-ai-prompts and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate nosql-database-design. Access via /nosql-database-design in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Design scalable NoSQL schemas for MongoDB (document) and DynamoDB (key-value). Covers data modeling patterns, denormalization strategies, and query optimization for NoSQL systems.
Minimal working example:
// Single document with embedded arrays
db.createCollection("users");
db.users.insertOne({
_id: ObjectId("..."),
email: "[email protected]",
name: "John Doe",
createdAt: new Date(),
// Embedded address
address: {
street: "123 Main St",
city: "New York",
state: "NY",
zipCode: "10001",
},
// Embedded array of items
orders: [
{
orderId: ObjectId("..."),
date: new Date(),
total: 149.99,
},
{
// ... (see reference guides for full implementation)
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Document Structure Design | Document Structure Design |
| Indexing in MongoDB | Indexing in MongoDB |
| Schema Validation | Schema Validation |
| Table Structure | Table Structure |
| Global Secondary Indexes (GSI) | Global Secondary Indexes (GSI) |
| DynamoDB Item Operations | DynamoDB Item Operations |
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Keeps context tight: nosql-database-design is the kind of skill you can hand to a new teammate without a long onboarding doc.
nosql-database-design is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for nosql-database-design matched our evaluation — installs cleanly and behaves as described in the markdown.
nosql-database-design reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend nosql-database-design for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in nosql-database-design — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for nosql-database-design matched our evaluation — installs cleanly and behaves as described in the markdown.
nosql-database-design reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for nosql-database-design matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: nosql-database-design is focused, and the summary matches what you get after install.
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