Cosmosdb Best Practices

ClineOfficialCreated by cosmosdb-agent-kitDistributed by Cline

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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

Download the skill as a ZIP:
https://autogineer.com/agent-skills/cline/cosmosdb-best-practices/download

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-`)

model-embed-related.md — Embed related data retrieved together
model-reference-large.md — Reference data when items grow large
model-avoid-2mb-limit.md — Keep items well under 2MB limit
model-id-constraints.md — Follow ID value length and character constraints
model-nesting-depth.md — Stay within 128-level nesting depth limit
model-numeric-precision.md — Understand IEEE 754 numeric precision limits
model-denormalize-reads.md — Denormalize for read-heavy workloads
model-schema-versioning.md — Version your document schemas
model-type-discriminator.md — Use type discriminators for polymorphic data
model-json-serialization.md — Handle JSON serialization correctly
model-relationship-references.md — Use ID references with transient hydration

2. Partition Key Design — CRITICAL (prefix: `partition-`)

partition-high-cardinality.md — Choose high-cardinality partition keys
partition-avoid-hotspots.md — Distribute writes evenly
partition-hierarchical.md — Use hierarchical partition keys for flexibility
partition-query-patterns.md — Align partition key with query patterns
partition-synthetic-keys.md — Create synthetic keys when needed
partition-key-length.md — Respect partition key value length limits
partition-20gb-limit.md — Plan for 20GB logical partition limit

3. Query Optimization — HIGH (prefix: `query-`)

query-avoid-cross-partition.md — Minimize cross-partition queries
query-use-projections.md — Project only needed fields
query-pagination.md — Use continuation tokens for pagination
query-avoid-scans.md — Avoid full container scans
query-parameterize.md — Use parameterized queries
query-order-filters.md — Order filters by selectivity

4. SDK Best Practices — HIGH (prefix: `sdk-`)

sdk-singleton-client.md — Reuse CosmosClient as singleton
sdk-async-api.md — Use async APIs for throughput
sdk-retry-429.md — Handle 429s with retry-after
sdk-connection-mode.md — Use Direct mode for production
sdk-preferred-regions.md — Configure preferred regions
sdk-excluded-regions.md — Exclude regions experiencing issues
sdk-availability-strategy.md — Configure availability strategy for resilience
sdk-circuit-breaker.md — Use circuit breaker for fault tolerance
sdk-diagnostics.md — Log diagnostics for troubleshooting
sdk-serialization-enums.md — Serialize enums as strings not integers
sdk-emulator-ssl.md — Configure SSL and connection mode for Cosmos DB Emulator
sdk-etag-concurrency.md — Use ETags for optimistic concurrency
sdk-java-content-response.md — Enable content response on write operations (Java)
sdk-java-cosmos-config.md — Configure Cosmos DB in Spring Boot with dependent beans
sdk-java-spring-boot-versions.md — Match Java version to Spring Boot requirements
sdk-local-dev-config.md — Configure local development to avoid cloud conflicts
sdk-newtonsoft-dependency.md — Explicitly reference Newtonsoft.Json package (.NET)
sdk-spring-data-annotations.md — Annotate entities for Spring Data Cosmos
sdk-spring-data-repository.md — Use CosmosRepository correctly

5. Indexing Strategies — MEDIUM-HIGH (prefix: `index-`)

index-exclude-unused.md — Exclude paths never queried
index-composite.md — Use composite indexes for ORDER BY
index-spatial.md — Add spatial indexes for geo queries
index-range-vs-hash.md — Choose appropriate index types
index-lazy-consistent.md — Understand indexing modes

6. Throughput & Scaling — MEDIUM (prefix: `throughput-`)

throughput-autoscale.md — Use autoscale for variable workloads
throughput-right-size.md — Right-size provisioned throughput
throughput-serverless.md — Consider serverless for dev/test
throughput-burst.md — Understand burst capacity
throughput-container-vs-database.md — Choose allocation level wisely

7. Global Distribution — MEDIUM (prefix: `global-`)

global-multi-region.md — Configure multi-region writes
global-consistency.md — Choose appropriate consistency level
global-conflict-resolution.md — Implement conflict resolution
global-failover.md — Configure automatic failover
global-read-regions.md — Add read regions near users
global-zone-redundancy.md — Enable zone redundancy for HA

8. Monitoring & Diagnostics — LOW-MEDIUM (prefix: `monitoring-`)

monitoring-ru-consumption.md — Track RU consumption
monitoring-latency.md — Monitor P99 latency
monitoring-throttling.md — Alert on throttling
monitoring-azure-monitor.md — Integrate Azure Monitor
monitoring-diagnostic-logs.md — Enable diagnostic logging

9. Design Patterns — HIGH (prefix: `pattern-`)

pattern-change-feed-materialized-views.md — Use Change Feed for materialized views
pattern-efficient-ranking.md — Use count-based or cached approaches for ranking
pattern-service-layer-relationships.md — Use a service layer to hydrate document references

10. Vector Search — HIGH (prefix: `vector-`)

vector-enable-feature.md — Enable vector search feature on account
vector-embedding-policy.md — Define vector embedding policy on container
vector-index-type.md — Configure vector indexes (QuantizedFlat or DiskANN)
vector-distance-query.md — Use VectorDistance() for similarity search
vector-normalize-embeddings.md — Normalize embeddings for cosine similarity
vector-repository-pattern.md — Implement repository pattern for vector search

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

ATTRIBUTION.mdAdded by AutoGineer876 B
SKILL.md10.1 KiB
rules/_sections.md2.1 KiB
rules/_template.md802 B
rules/global-conflict-resolution.md4.0 KiB
rules/global-consistency.md3.7 KiB
rules/global-failover.md3.7 KiB
rules/global-multi-region.md3.2 KiB
rules/global-read-regions.md3.9 KiB
rules/global-zone-redundancy.md3.5 KiB
rules/index-composite.md6.0 KiB
rules/index-exclude-unused.md3.1 KiB
rules/index-lazy-consistent.md3.1 KiB
rules/index-range-vs-hash.md3.4 KiB
rules/index-spatial.md3.1 KiB
rules/model-avoid-2mb-limit.md2.0 KiB
rules/model-denormalize-reads.md3.4 KiB
rules/model-embed-related.md2.5 KiB
rules/model-id-constraints.md2.9 KiB
rules/model-json-serialization.md4.0 KiB
rules/model-nesting-depth.md3.3 KiB
rules/model-numeric-precision.md3.2 KiB
rules/model-reference-large.md2.3 KiB
rules/model-relationship-references.md3.6 KiB
rules/model-schema-versioning.md2.4 KiB
rules/model-type-discriminator.md3.5 KiB
rules/monitoring-azure-monitor.md4.4 KiB
rules/monitoring-diagnostic-logs.md5.1 KiB
rules/monitoring-latency.md4.2 KiB
rules/monitoring-ru-consumption.md4.2 KiB
rules/monitoring-throttling.md4.4 KiB
rules/partition-20gb-limit.md2.8 KiB
rules/partition-avoid-hotspots.md3.4 KiB
rules/partition-hierarchical.md2.7 KiB
rules/partition-high-cardinality.md2.2 KiB
rules/partition-key-length.md2.8 KiB
rules/partition-query-patterns.md2.7 KiB
rules/partition-synthetic-keys.md3.8 KiB
rules/pattern-change-feed-materialized-views.md7.2 KiB
rules/pattern-efficient-ranking.md5.8 KiB
rules/pattern-service-layer-relationships.md4.8 KiB
rules/query-avoid-cross-partition.md2.5 KiB
rules/query-avoid-scans.md2.5 KiB
rules/query-order-filters.md2.6 KiB
rules/query-pagination.md6.2 KiB
rules/query-parameterize.md2.9 KiB
rules/query-use-projections.md2.7 KiB
rules/sdk-async-api.md3.2 KiB
rules/sdk-availability-strategy.md5.3 KiB
rules/sdk-circuit-breaker.md8.4 KiB
rules/sdk-connection-mode.md2.9 KiB
rules/sdk-diagnostics.md3.6 KiB
rules/sdk-emulator-ssl.md7.8 KiB
rules/sdk-etag-concurrency.md8.1 KiB
rules/sdk-excluded-regions.md4.9 KiB
rules/sdk-java-content-response.md3.9 KiB
rules/sdk-java-cosmos-config.md5.9 KiB
rules/sdk-java-spring-boot-versions.md4.8 KiB
rules/sdk-local-dev-config.md5.4 KiB
rules/sdk-newtonsoft-dependency.md3.9 KiB
rules/sdk-preferred-regions.md3.2 KiB
rules/sdk-retry-429.md3.7 KiB
rules/sdk-serialization-enums.md2.8 KiB
rules/sdk-singleton-client.md3.7 KiB
rules/sdk-spring-data-annotations.md3.4 KiB
rules/sdk-spring-data-repository.md3.4 KiB
rules/throughput-autoscale.md2.6 KiB
rules/throughput-burst.md2.7 KiB
rules/throughput-container-vs-database.md3.2 KiB
rules/throughput-right-size.md3.1 KiB
rules/throughput-serverless.md2.7 KiB
rules/vector-distance-query.md4.8 KiB
rules/vector-embedding-policy.md3.8 KiB
rules/vector-enable-feature.md3.0 KiB
rules/vector-index-type.md4.7 KiB
rules/vector-normalize-embeddings.md8.6 KiB
rules/vector-repository-pattern.md12.9 KiB

rules/sdk-local-dev-config.md

title: Configure local development environment to avoid cloud connection conflicts impact: MEDIUM impactDescription: prevents accidental connections to production instead of emulator tags: sdk, local-development, emulator, configuration, environment-variables

Configure Local Development Environment Properly

When developing locally with the Cosmos DB Emulator, system-level environment variables pointing to Azure cloud accounts can override your local configuration, causing unexpected connections to production resources instead of the emulator.

Problem - System environment variables override local config:

# Your .env file (local config)
COSMOS_ENDPOINT=https://localhost:8081
COSMOS_KEY=C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==

# But system environment has (from Azure CLI or other tools):
# COSMOS_ENDPOINT=https://my-prod-account.documents.azure.com:443/

# Default dotenv loading does NOT override existing env vars!
from dotenv import load_dotenv
load_dotenv()  # ❌ System COSMOS_ENDPOINT wins - connects to production!

Solution - Force override of environment variables:

Python:

from dotenv import load_dotenv
import os

# Force .env values to override system environment variables
load_dotenv(override=True)  # ✅ .env values take precedence

# Or use explicit defaults for emulator
COSMOS_ENDPOINT = os.getenv("COSMOS_ENDPOINT", "https://localhost:8081")
COSMOS_KEY = os.getenv(
    "COSMOS_KEY", 
    "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
)

Node.js:

// dotenv also has override option
require('dotenv').config({ override: true });

// Or with explicit defaults
const endpoint = process.env.COSMOS_ENDPOINT || 'https://localhost:8081';
const key = process.env.COSMOS_KEY || 
    'C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==';

.NET:

// appsettings.Development.json takes precedence over appsettings.json
// in Development environment

// appsettings.Development.json
{
  "CosmosDb": {
    "Endpoint": "https://localhost:8081",
    "Key": "C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw=="
  }
}

// Program.cs - Environment-specific config loaded automatically
var builder = WebApplication.CreateBuilder(args);
// Configuration precedence: appsettings.{Environment}.json > appsettings.json > env vars

// Or use explicit emulator detection
public static class CosmosConfig
{
    public static bool IsEmulator(string endpoint) => 
        endpoint.Contains("localhost") || endpoint.Contains("127.0.0.1");
    
    public static CosmosClientOptions GetClientOptions(string endpoint)
    {
        var options = new CosmosClientOptions();
        
        if (IsEmulator(endpoint))
        {
            options.ConnectionMode = ConnectionMode.Gateway;  // Required for emulator
            options.HttpClientFactory = () => new HttpClient(
                new HttpClientHandler
                {
                    ServerCertificateCustomValidationCallback = 
                        HttpClientHandler.DangerousAcceptAnyServerCertificateValidator
                });
        }
        else
        {
            options.ConnectionMode = ConnectionMode.Direct;  // Production
        }
        
        return options;
    }
}

Java (Spring Boot):

# application.yml - Profile-specific configuration
spring:
  profiles:
    active: local  # Set via SPRING_PROFILES_ACTIVE env var

---
# application-local.yml (local development profile)
azure:
  cosmos:
    endpoint: https://localhost:8081
    key: C2y6yDjf5/R+ob0N8A7Cgv30VRDJIWEHLM+4QDU5DE2nQ9nDuVTqobD4b8mGGyPMbIZnqyMsEcaGQy67XIw/Jw==

---
# application-prod.yml (production profile)
azure:
  cosmos:
    endpoint: ${COSMOS_ENDPOINT}  # From environment
    key: ${COSMOS_KEY}  # From Key Vault ideally

Best practices for local development:

Use profile/environment-specific configuration files
- .env.local, appsettings.Development.json, application-local.yml

Log the endpoint at startup (without the key!)

print(f"Connecting to Cosmos DB at: {COSMOS_ENDPOINT}")
# Never log the key!

Validate you're connecting to emulator

if "localhost" not in COSMOS_ENDPOINT and "127.0.0.1" not in COSMOS_ENDPOINT:
    print("⚠️ WARNING: Not connecting to local emulator!")
    print(f"Endpoint: {COSMOS_ENDPOINT}")

Use different database names for dev/prod

DATABASE_NAME = os.getenv("COSMOS_DATABASE", "dev-database")
# Production uses: prod-ecommerce
# Local uses: dev-database (default)

Clear conflicting system environment variables

# PowerShell - temporarily clear for this session
$env:COSMOS_ENDPOINT = $null
$env:COSMOS_KEY = $null

# Or unset permanently
[Environment]::SetEnvironmentVariable("COSMOS_ENDPOINT", $null, "User")

Key Points:

System environment variables take precedence over .env files by default
Use load_dotenv(override=True) in Python to force local config
Use environment/profile-specific configuration files
Log the endpoint (not the key!) at startup to verify correct connection
The emulator uses a well-known key - don't use this in production!

Reference: Azure Cosmos DB Emulator

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

2026-11-09

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

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by cosmosdb-agent-kit

Azure Cosmos DB Best Practices

When to Apply

Rule Index

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-)