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Cosmosdb Best Practices

ClineOfficialCreated by cosmosdb-agent-kitDistributed by Cline

  • Skill
  • Guidelines
  • Software development
  • MIT
  • No issues found

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/model-json-serialization.md


title: Handle JSON serialization correctly for Cosmos DB documents impact: HIGH impactDescription: prevents data loss, null constructor errors, and serialization failures tags: model, serialization, json, jackson, jsonignore, jsonproperty, bigdecimal

Handle JSON Serialization Correctly for Cosmos DB

Cosmos DB stores documents as JSON. Every field on an entity that must be persisted needs to be serializable. Incorrect use of @JsonIgnore, missing constructors, or incompatible field types (like BigDecimal on JDK 17+) cause silent data loss or runtime failures.

Incorrect (common serialization mistakes):

@Container(containerName = "users")
public class User {

    @Id
    private String id;

    @PartitionKey
    private String partitionKey = "user";

    private String login;

    @JsonIgnore  // ❌ WRONG: Password will NOT be saved to Cosmos DB
    private String password;

    @JsonIgnore  // ❌ WRONG: Authorities will NOT be saved to Cosmos DB
    private Set<String> authorities = new HashSet<>();

    private BigDecimal accountBalance;  // ❌ Fails on JDK 17+ with reflection errors
}

Correct (proper serialization for Cosmos DB):

@Container(containerName = "users")
public class User {

    @Id
    private String id;

    @PartitionKey
    private String partitionKey = "user";

    private String login;

    // ✅ No @JsonIgnore — field is persisted to Cosmos DB
    private String password;

    // ✅ Use @JsonProperty for explicit field naming, NOT @JsonIgnore
    @JsonProperty("authorities")
    private Set<String> authorities = new HashSet<>();

    // ✅ Use Double instead of BigDecimal for JDK 17+ compatibility
    private Double accountBalance;
}

Rule 1: Never @JsonIgnore persisted fields

@JsonIgnore prevents a field from being written to Cosmos DB. This is the #1 cause of "Cannot pass null or empty values to constructor" errors after reading a document back:

// ❌ Data loss: field is not stored in Cosmos
@JsonIgnore
private String password;

// ✅ Field is stored in Cosmos
private String password;

// ✅ Rename in JSON but still store
@JsonProperty("pwd")
private String password;

Only use @JsonIgnore on transient/computed fields that should NOT be stored in Cosmos DB (e.g., hydrated relationship objects — see model-relationship-references).

Rule 2: BigDecimal fails on JDK 17+

Java 17+ module system restricts reflection access to BigDecimal internal fields during Jackson serialization:

Unable to make field private final java.math.BigInteger
java.math.BigDecimal.intVal accessible

Solutions (in order of preference):

  1. Replace with Double — sufficient for most use cases:

    private Double amount; // Instead of BigDecimal
  2. Replace with String — for high-precision requirements:

    private String amount; // Store "1500.00"
    
    public BigDecimal getAmountAsBigDecimal() {
        return new BigDecimal(amount);
    }
  3. Add JVM argument — if BigDecimal must be kept:

    --add-opens java.base/java.math=ALL-UNNAMED

Rule 3: Provide a default constructor

Cosmos DB deserialization requires a no-arg constructor. If you add parameterized constructors, always keep the default:

@Container(containerName = "items")
public class Item {
    // ✅ Default constructor required for deserialization
    public Item() {}

    public Item(String name, Double price) {
        this.name = name;
        this.price = price;
    }
}

Rule 4: Store complex objects as simple types

For complex Cosmos DB compatibility, prefer simple types over JPA entity references:

// ❌ Complex nested entity — may cause serialization issues
private Set<Authority> authorities;

// ✅ Simple string set — reliable serialization
private Set<String> authorities;

Convert between simple and complex types in the service layer, not in the entity.

Reference: Jackson annotations guide

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