Cosmosdb Datamodeling
This skill helps you design efficient Cosmos DB data models for optimal performance and cost savings by leveraging its flexible schema.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add cosmosdb-datamodeling npx -- -y @trustedskills/cosmosdb-datamodeling
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"cosmosdb-datamodeling": {
"command": "npx",
"args": [
"-y",
"@trustedskills/cosmosdb-datamodeling"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The cosmosdb-datamodeling skill enables AI agents to design and optimize data models for Azure Cosmos DB, a globally distributed NoSQL database. It supports schema design, query optimization, and partition key selection tailored for high-performance, scalable applications.
When to use it
- Designing a new data model for an application that requires low-latency access across multiple regions.
- Optimizing existing queries to reduce cost and improve performance in Cosmos DB.
- Preparing data structures for time-series or hierarchical data storage in a NoSQL environment.
Key capabilities
- Schema design for document, key-value, and graph data models
- Partition key selection and indexing strategies
- Query optimization for efficient data retrieval
Example prompts
- "Design a Cosmos DB data model for storing user activity logs with time-series data."
- "Optimize this query to reduce RU consumption in Azure Cosmos DB."
- "Suggest partition key options for a global e-commerce application using Cosmos DB."
Tips & gotchas
- Ensure you have a clear understanding of your data access patterns before modeling.
- Use the skill alongside Azure Cosmos DB documentation for best practices and limitations.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🏢 Official
Published by the company or team that built the technology.