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cosmos-provisioning

Automate Azure Cosmos DB container provisioning, configuration, and validation.

Updated May 7, 2026
Search Tags:#dotnet#database-configuration#partition-key#infrastructure-automation#azure-cosmos-db#container-provisioning#index-policy
One-click install
npx skills add https://github.com/tmalcolm-0607/mad-council-claw --skill cosmos-provisioning
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cosmos-provisioning
Source: https://github.com/tmalcolm-0607/mad-council-claw/tree/main/.claude/skills/cosmos-provisioning
Command: npx skills add https://github.com/tmalcolm-0607/mad-council-claw --skill cosmos-provisioning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually provisioning and configuring Azure Cosmos DB containers is error-prone, with misconfigured partition keys, index policies, or throughput settings leading to poor performance, high costs, and scalability issues. This Skill eliminates those risks by automating the entire setup process with validated best practices.

Core Features & Use Cases

  • Intelligent Partition Key Design: Validates and recommends high-cardinality partition keys aligned with your application's query patterns to avoid hot partitions and costly cross-partition queries.
  • Optimized Index Policy Generation: Creates tailored index policies (included paths, composite indexes) based on your read/write workload to minimize RU consumption and improve query performance.
  • Use Case: For .NET development teams building applications with Azure Cosmos DB, use this Skill to provision production-ready containers in minutes instead of manually configuring each parameter via the Azure portal or SDK, reducing setup time and avoiding costly misconfigurations.

Quick Start

Use the cosmos-provisioning skill to provision a new Cosmos DB container for your orders entity using the partition key and query patterns defined in your project's data-model.md file.

Frequently Asked Questions about cosmos-provisioning

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

FAQPage Schema
How do I automate Azure Cosmos DB container provisioning in a .NET workflow?▼

Automate Azure Cosmos DB container provisioning by using a skill that validates partition keys, tunes index policies, and configures throughput settings. This eliminates manual portal setup errors and ensures repeatable, production-ready infrastructure aligned with Azure best practices.

What is the best way to design a partition key for Azure Cosmos DB?▼

Designing a partition key for Azure Cosmos DB requires validating high-cardinality keys against your query patterns. This prevents hot partitions and costly cross-partition queries by ensuring an even distribution of data and read/write workloads.

How do I optimize index policies in Azure Cosmos DB to reduce RU consumption?▼

Optimize index policies in Azure Cosmos DB by generating tailored included paths and composite indexes based on your read/write workload. This minimizes Request Unit consumption and improves query performance for .NET applications.

Can I validate existing Azure Cosmos DB container configurations against best practices?▼

Yes, you can validate existing Azure Cosmos DB container configurations. The automation checks current partition key design, index policies, and throughput settings against Azure best practices to identify and correct costly misconfigurations.

Does Azure Cosmos DB provisioning support autoscale throughput configuration?▼

Yes, Azure Cosmos DB provisioning supports autoscale throughput configuration. This allows your .NET application containers to scale request capacity automatically, optimizing cost and performance for development and production environments.

Why does my Azure Cosmos DB container have high cross-partition query costs?▼

High cross-partition query costs in Azure Cosmos DB usually result from a poorly designed partition key or missing composite indexes. Validating your partition key cardinality and tuning the index policy for your workload resolves these performance bottlenecks.

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