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Cosmosdb Best Practices

ClineOfficialCreated by cosmosdb-agent-kitDistributed by Cline

  • Skill
  • Guidelines
  • Software development
  • MIT
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From the author

Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, SDK usage, and vector search. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.
— the description by cosmosdb-agent-kit

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured set of 73+ guidelines for working with Azure Cosmos DB. It covers essential topics including data modeling, partition key design, query optimization, SDK usage, indexing, throughput scaling, global distribution, monitoring, design patterns, and vector search. The content is organized into modular rule files to assist developers in writing, reviewing, and refactoring code that interacts with the database.

What it does

  • Provides specific rules for designing efficient data models and choosing partition keys.
  • Offers guidance on optimizing queries and implementing SDK patterns.
  • Details strategies for indexing, throughput management, and global distribution.
  • Includes best practices for implementing vector search and RAG patterns.
  • Supplies diagnostic and monitoring recommendations for database operations.
  • Organizes content into categorized rule files for targeted retrieval.

When to use it

  • When designing data models or selecting partition keys for Cosmos DB.
  • When writing or refactoring application code that uses the Cosmos DB SDK.
  • When optimizing query performance or indexing strategies.
  • When configuring global distribution, throughput, or scaling settings.
  • When implementing vector search or advanced design patterns.

Advantages

  • Modular structure allows for loading only relevant rules for specific tasks.
  • Covers a wide range of operational and architectural concerns.
  • Provides clear examples of incorrect and correct implementation patterns.
  • Prioritizes rules by impact to guide development decisions.

Usage examples

“How should I choose a partition key for my Cosmos DB container?”
The agent will retrieve rules from the partition- prefix to explain high-cardinality, write distribution, and query alignment.
“What are the best practices for using the Cosmos DB SDK?”
The agent will load rules from the sdk- prefix to provide guidance on singleton client usage, async APIs, and retry logic.
“How do I optimize my data model for read-heavy workloads?”
The agent will reference model- prefixed rules to explain denormalization and embedding strategies.
“What should I consider when implementing vector search in Cosmos DB?”
The agent will access vector- prefixed rules to explain embedding policies, index types, and similarity search functions.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/cline/cosmosdb-best-practices/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip cosmosdb-best-practices.zip -d .agents/skills

Documentation by cosmosdb-agent-kit

Azure Cosmos DB Best Practices

Comprehensive performance optimization guide for Azure Cosmos DB applications, containing 73+ rules across 10 categories, prioritized by impact to guide automated refactoring and code generation.

73 individual rule files are in the rules/ directory, one file per rule, synced from the AzureCosmosDB/cosmosdb-agent-kit. Load only the relevant rule file(s) when answering a question — do NOT load all files at once.

When to Apply

Reference these guidelines when:

  • Designing data models for Cosmos DB

  • Choosing partition keys

  • Writing or optimizing queries

  • Implementing SDK patterns

  • Reviewing code for performance issues

  • Configuring throughput and scaling

  • Building globally distributed applications

  • Implementing vector search and RAG patterns

Rule Index

Rules are grouped by category prefix. For a given question, load files matching the relevant prefix (e.g., model-*.md for data modeling, sdk-*.md for SDK usage). See rules/_sections.md for category descriptions.

1. Data Modeling — CRITICAL (prefix: model-)
2. Partition Key Design — CRITICAL (prefix: partition-)
3. Query Optimization — HIGH (prefix: query-)
4. SDK Best Practices — HIGH (prefix: sdk-)
5. Indexing Strategies — MEDIUM-HIGH (prefix: index-)
6. Throughput & Scaling — MEDIUM (prefix: throughput-)
7. Global Distribution — MEDIUM (prefix: global-)
8. Monitoring & Diagnostics — LOW-MEDIUM (prefix: monitoring-)
9. Design Patterns — HIGH (prefix: pattern-)
10. Vector Search — HIGH (prefix: vector-)

How to Use

Each rule is a separate file under rules/. When answering a Cosmos DB question, read only the relevant rule file(s) based on the prefix matching the topic:

  • Data modeling question → read rules/model-*.md files

  • Partition key question → read rules/partition-*.md files

  • SDK/client question → read rules/sdk-*.md files

  • etc.

Each rule file contains:

  • Brief explanation of why it matters

  • Incorrect code example with explanation

  • Correct code example with explanation

  • Additional context and references

Source: AzureCosmosDB/cosmosdb-agent-kit

Files

rules/sdk-java-cosmos-config.md

title: Use dependent @Bean methods for Cosmos DB initialization in Spring Boot impact: HIGH impactDescription: prevents circular dependency and startup failures tags: sdk, java, spring-boot, configuration, cosmos-config, bean, postconstruct

Use Dependent @Bean Methods for Cosmos DB Initialization in Spring Boot

When configuring CosmosClient, CosmosDatabase, and CosmosContainer beans in a Spring Boot @Configuration class, use dependent @Bean methods with parameter injection instead of @PostConstruct. Calling a @Bean method from @PostConstruct in the same class creates a circular dependency that crashes the application on startup.

Incorrect (@PostConstruct calling @Bean — circular dependency):

// ❌ Anti-pattern: @PostConstruct + @Bean in same class causes circular dependency
@Configuration
public class CosmosConfig {

    @Value("${azure.cosmos.endpoint}")
    private String endpoint;

    @Value("${azure.cosmos.key}")
    private String key;

    @Bean
    public CosmosClient cosmosClient() {
        return new CosmosClientBuilder()
            .endpoint(endpoint)
            .key(key)
            .consistencyLevel(ConsistencyLevel.SESSION)
            .buildClient();
    }

    @PostConstruct  // ❌ This calls cosmosClient() which is a @Bean — circular!
    public void initializeDatabase() {
        CosmosClient client = cosmosClient(); // Triggers proxy interception loop
        client.createDatabaseIfNotExists("mydb");
        CosmosDatabase db = client.getDatabase("mydb");
        db.createContainerIfNotExists(
            new CosmosContainerProperties("items", "/partitionKey"),
            ThroughputProperties.createAutoscaledThroughput(4000));
    }

    @Bean
    public CosmosDatabase cosmosDatabase() {
        return cosmosClient().getDatabase("mydb");
    }

    @Bean
    public CosmosContainer cosmosContainer() {
        return cosmosDatabase().getContainer("items");
    }
}
// Runtime error: BeanCurrentlyInCreationException — circular dependency detected

Correct (dependent @Bean chain with parameter injection):

// ✅ Correct: Use @Bean dependency injection chain — initialization in bean methods
@Configuration
public class CosmosConfig {

    @Value("${azure.cosmos.endpoint}")
    private String endpoint;

    @Value("${azure.cosmos.key}")
    private String key;

    @Value("${azure.cosmos.database}")
    private String databaseName;

    @Value("${azure.cosmos.container}")
    private String containerName;

    @Bean(destroyMethod = "close")
    public CosmosClient cosmosClient() {
        DirectConnectionConfig directConfig = DirectConnectionConfig.getDefaultConfig();
        GatewayConnectionConfig gatewayConfig = GatewayConnectionConfig.getDefaultConfig();

        // Use Gateway for emulator, Direct for production
        CosmosClientBuilder builder = new CosmosClientBuilder()
            .endpoint(endpoint)
            .key(key)
            .consistencyLevel(ConsistencyLevel.SESSION)
            .contentResponseOnWriteEnabled(true);

        if (endpoint.contains("localhost") || endpoint.contains("127.0.0.1")) {
            builder.gatewayMode(gatewayConfig);
        } else {
            builder.directMode(directConfig);
        }

        return builder.buildClient();
    }

    @Bean  // ✅ Spring injects cosmosClient from the bean above
    public CosmosDatabase cosmosDatabase(CosmosClient cosmosClient) {
        // Database initialization happens here — no @PostConstruct needed
        cosmosClient.createDatabaseIfNotExists(databaseName);
        return cosmosClient.getDatabase(databaseName);
    }

    @Bean  // ✅ Spring injects cosmosDatabase from the bean above
    public CosmosContainer cosmosContainer(CosmosDatabase cosmosDatabase) {
        CosmosContainerProperties props = new CosmosContainerProperties(
            containerName, "/partitionKey");

        cosmosDatabase.createContainerIfNotExists(
            props,
            ThroughputProperties.createAutoscaledThroughput(4000));

        return cosmosDatabase.getContainer(containerName);
    }
}

Why this works:

  • Spring resolves the dependency graph: cosmosClient() → cosmosDatabase(CosmosClient) → cosmosContainer(CosmosDatabase)

  • Database and container creation happens naturally during bean initialization

  • No circular reference because each method receives its dependency as a parameter

  • destroyMethod = "close" ensures CosmosClient is properly shut down

With Hierarchical Partition Keys:

@Bean
public CosmosContainer cosmosContainer(CosmosDatabase cosmosDatabase) {
    // Hierarchical partition key definition
    List<String> partitionKeyPaths = Arrays.asList(
        "/tenantId", "/type", "/projectId");

    CosmosContainerProperties props = new CosmosContainerProperties(
        containerName,
        partitionKeyPaths,
        PartitionKeyDefinitionVersion.V2,
        PartitionKind.MULTI_HASH);

    cosmosDatabase.createContainerIfNotExists(
        props,
        ThroughputProperties.createAutoscaledThroughput(4000));

    return cosmosDatabase.getContainer(containerName);
}

Alternative: SmartInitializingSingleton for post-init logic:

// If you need to run logic AFTER all beans are created
@Bean
public SmartInitializingSingleton cosmosInitializer(CosmosContainer container) {
    return () -> {
        // Seed data, verify connectivity, warm up, etc.
        logger.info("Cosmos container ready: {}", container.getId());
    };
}

Key Points:

  • Never call @Bean methods from @PostConstruct in the same @Configuration class

  • Use parameter injection in @Bean methods to express initialization order

  • Always set destroyMethod = "close" on CosmosClient bean

  • Keep CosmosClient as a singleton @Bean (Rule 4.16)

  • Set contentResponseOnWriteEnabled(true) in the builder (Rule 4.9)

Reference: Spring Framework @Bean documentation

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
cosmosdb-agent-kit
Publisher
Cline (Official)
Distributed by
Cline
Source
cline/skills · skills/cosmosdb-best-practices · commit 2637846
Licence
MIT License (redistribution allowed)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by cosmosdb-agent-kit or Cline.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download cosmosdb-best-practices.zip