cosmosdb-datamodeling

Generate Cosmos DB NoSQL design artifacts from captured requirements.

Updated Mar 18, 2026

Search Tags:#nosql #data-modeling #cosmosdb #aggregate-oriented-design #partition-key #throughput-planning

Ready to run

npx skills add https://github.com/angryconsultant/Copilot-CLI --skill cosmosdb-datamodeling-angryconsultant

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cosmosdb-datamodeling
Source: https://github.com/angryconsultant/Copilot-CLI/tree/main/skills/cosmosdb-datamodeling
Command: npx skills add https://github.com/angryconsultant/Copilot-CLI --skill cosmosdb-datamodeling-angryconsultant

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Solves Cosmos DB NoSQL data modeling challenges by capturing requirements and generating design artifacts such as cosmosdb_requirements.md and cosmosdb_data_model.md.

Core Features & Use Cases

Guided requirements capture and design artifact generation for Cosmos DB NoSQL schemas
Aggregate-oriented design guidance to optimize partitioning, throughput, and indexing
Step-by-step workflow enforcing two key outputs: cosmosdb_requirements.md (working scratchpad) and cosmosdb_data_model.md (final design)

Quick Start

Provide initial project details and I will start capturing requirements and generating the Cosmos DB data model artifacts.

Frequently Asked Questions about cosmosdb-datamodeling

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I design a Cosmos DB NoSQL data model for scalable access patterns?▼

Aggregate-oriented design in Cosmos DB groups related data into single documents to minimize cross-partition queries and optimize throughput. This pattern-driven approach captures access patterns and aggregate boundaries to produce efficient NoSQL schemas with optimal partition key selection.

What's the best way to plan throughput and partition keys for a Cosmos DB container?▼

Throughput planning and partition key selection for Cosmos DB containers are determined by analyzing access patterns and aggregate boundaries. A pattern-driven workflow captures these requirements to document container designs and throughput strategies in a structured data model artifact.

How do I document NoSQL schema requirements and access patterns for Cosmos DB?▼

Documenting Cosmos DB NoSQL schema requirements involves capturing access patterns, aggregate boundaries, and indexing strategies. An evidence-based workflow generates two deliverables: a requirements scratchpad file for iterative capture and a final data model file for container designs and global distribution strategy.

Can I use a pattern-driven workflow to generate Cosmos DB data modeling artifacts?▼

Yes, a pattern-driven workflow enforces the generation of two Cosmos DB data modeling artifacts: a requirements scratchpad and a final data model. This step-by-step process captures project details to produce structured deliverables for container designs and global distribution strategy.

When do I need to capture aggregate boundaries for Cosmos DB NoSQL schemas?▼

Aggregate boundaries for Cosmos DB NoSQL schemas must be captured when designing containers that require optimized partitioning and throughput. This step is necessary before finalizing indexing strategies and global distribution plans to ensure scalable access pattern performance.

Does Cosmos DB NoSQL data modeling support global distribution strategy documentation?▼

Cosmos DB NoSQL data modeling supports global distribution strategy documentation by capturing requirements and generating design artifacts. The workflow produces a final data model file that explicitly includes global distribution strategy alongside container designs and throughput planning.