Azure Cosmos Db Py
Azure Cosmos Db Py is an code AI skill with a core value of Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. It
helps developers solve real-world problems in the code domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service...
Quick Facts
mkdir -p ./skills/azure-cosmos-db-py && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-cosmos-db-py/SKILL.md -o ./skills/azure-cosmos-db-py/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Cosmos DB Service Implementation
Build production-grade Azure Cosmos DB NoSQL services following clean code, security best practices, and TDD principles.
Installation
pip install azure-cosmos azure-identityEnvironment Variables
COSMOS_ENDPOINT=https://<account>.documents.azure.com:443/
COSMOS_DATABASE_NAME=<database-name>
COSMOS_CONTAINER_ID=<container-id>
# For emulator only (not production)
COSMOS_KEY=<emulator-key>Authentication
**DefaultAzureCredential (preferred)**:
from azure.cosmos import CosmosClient
from azure.identity import DefaultAzureCredential
client = CosmosClient(
url=os.environ["COSMOS_ENDPOINT"],
credential=DefaultAzureCredential()
)**Emulator (local development)**:
from azure.cosmos import CosmosClient
client = CosmosClient(
url="https://localhost:8081",
credential=os.environ["COSMOS_KEY"],
connection_verify=False
)Architecture Overview
┌─────────────────────────────────────────────────────────────────┐
│ FastAPI Router │
│ - Auth dependencies (get_current_user, get_current_user_required)
│ - HTTP error responses (HTTPException) │
└──────────────────────────────┬──────────────────────────────────┘
│
┌──────────────────────────────▼──────────────────────────────────┐
│ Service Layer │
│ - Business logic and validation │
│ - Document ↔ Model conversion │
│ - Graceful degradation when Cosmos unavailable │
└──────────────────────────────┬──────────────────────────────────┘
│
┌──────────────────────────────▼──────────────────────────────────┐
│ Cosmos DB Client Module │
│ - Singleton container initialization │
│ - Dual auth: DefaultAzureCredential (Azure) / Key (emulator) │
│ - Async wrapper via run_in_threadpool │
└─────────────────────────────────────────────────────────────────┘Quick Start
1. Client Module Setup
Create a singleton Cosmos client with dual authentication:
# db/cosmos.py
from azure.cosmos import CosmosClient
from azure.identity import DefaultAzureCredential
from starlette.concurrency import run_in_threadpool
_cosmos_container = None
def _is_emulator_endpoint(endpoint: str) -> bool:
return "localhost" in endpoint or "127.0.0.1" in endpoint
async def get_container():
global _cosmos_container
if _cosmos_container is None:
if _is_emulator_endpoint(settings.cosmos_endpoint):
client = CosmosClient(
url=settings.cosmos_endpoint,
credential=settings.cosmos_key,
connection_verify=False
)
else:
client = CosmosClient(
url=settings.cosmos_endpoint,
credential=DefaultAzureCredential()
)
db = client.get_database_client(settings.cosmos_database_name)
_cosmos_container = db.get_container_client(settings.cosmos_container_id)
return _cosmos_container**Full implementation**: See references/client-setup.md
2. Pydantic Model Hierarchy
Use five-tier model pattern for clean separation:
class ProjectBase(BaseModel): # Shared fields
name: str = Field(..., min_length=1, max_length=200)
class ProjectCreate(ProjectBase): # Creation request
workspace_id: str = Field(..., alias="workspaceId")
class ProjectUpdate(BaseModel): # Partial updates (all optional)
name: Optional[str] = Field(None, min_length=1)
class Project(ProjectBase): # API response
id: str
created_at: datetime = Field(..., alias="createdAt")
class ProjectInDB(Project): # Internal with docType
doc_type🎯 Best For
- UI designers
- Product designers
- Claude users
- Software engineers
- Development teams
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Python code quality enforcement
- Dependency management
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Cosmos Db Py to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
Is Azure Cosmos Db Py compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Azure Cosmos Db Py?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Azure Cosmos Db Py?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-cosmos-db-py/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.