feat: Add Official Microsoft & Gemini Skills (845+ Total)
🚀 Impact Significantly expands the capabilities of **Antigravity Awesome Skills** by integrating official skill collections from **Microsoft** and **Google Gemini**. This update increases the total skill count to **845+**, making the library even more comprehensive for AI coding assistants. ✨ Key Changes 1. New Official Skills - **Microsoft Skills**: Added a massive collection of official skills from [microsoft/skills](https://github.com/microsoft/skills). - Includes Azure, .NET, Python, TypeScript, and Semantic Kernel skills. - Preserves the original directory structure under `skills/official/microsoft/`. - Includes plugin skills from the `.github/plugins` directory. - **Gemini Skills**: Added official Gemini API development skills under `skills/gemini-api-dev/`. 2. New Scripts & Tooling - **`scripts/sync_microsoft_skills.py`**: A robust synchronization script that: - Clones the official Microsoft repository. - Preserves the original directory heirarchy. - Handles symlinks and plugin locations. - Generates attribution metadata. - **`scripts/tests/inspect_microsoft_repo.py`**: Debug tool to inspect the remote repository structure. - **`scripts/tests/test_comprehensive_coverage.py`**: Verification script to ensure 100% of skills are captured during sync. 3. Core Improvements - **`scripts/generate_index.py`**: Enhanced frontmatter parsing to safely handle unquoted values containing `@` symbols and commas (fixing issues with some Microsoft skill descriptions). - **`package.json`**: Added `sync:microsoft` and `sync:all-official` scripts for easy maintenance. 4. Documentation - Updated `README.md` to reflect the new skill counts (845+) and added Microsoft/Gemini to the provider list. - Updated `CATALOG.md` and `skills_index.json` with the new skills. 🧪 Verification - Ran `scripts/tests/test_comprehensive_coverage.py` to verify all Microsoft skills are detected. - Validated `generate_index.py` fixes by successfully indexing the new skills.
This commit is contained in:
Ahmed Rehan
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skills/official/microsoft/python/data/cosmos/SKILL.md
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skills/official/microsoft/python/data/cosmos/SKILL.md
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---
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name: azure-cosmos-py
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description: |
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Azure Cosmos DB SDK for Python (NoSQL API). Use for document CRUD, queries, containers, and globally distributed data.
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Triggers: "cosmos db", "CosmosClient", "container", "document", "NoSQL", "partition key".
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package: azure-cosmos
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---
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# Azure Cosmos DB SDK for Python
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Client library for Azure Cosmos DB NoSQL API — globally distributed, multi-model database.
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## Installation
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```bash
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pip install azure-cosmos azure-identity
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```
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## Environment Variables
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```bash
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COSMOS_ENDPOINT=https://<account>.documents.azure.com:443/
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COSMOS_DATABASE=mydb
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COSMOS_CONTAINER=mycontainer
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```
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## Authentication
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```python
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from azure.identity import DefaultAzureCredential
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from azure.cosmos import CosmosClient
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credential = DefaultAzureCredential()
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endpoint = "https://<account>.documents.azure.com:443/"
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client = CosmosClient(url=endpoint, credential=credential)
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```
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## Client Hierarchy
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| Client | Purpose | Get From |
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|--------|---------|----------|
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| `CosmosClient` | Account-level operations | Direct instantiation |
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| `DatabaseProxy` | Database operations | `client.get_database_client()` |
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| `ContainerProxy` | Container/item operations | `database.get_container_client()` |
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## Core Workflow
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### Setup Database and Container
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```python
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# Get or create database
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database = client.create_database_if_not_exists(id="mydb")
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# Get or create container with partition key
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container = database.create_container_if_not_exists(
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id="mycontainer",
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partition_key=PartitionKey(path="/category")
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)
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# Get existing
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database = client.get_database_client("mydb")
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container = database.get_container_client("mycontainer")
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```
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### Create Item
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```python
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item = {
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"id": "item-001", # Required: unique within partition
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"category": "electronics", # Partition key value
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"name": "Laptop",
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"price": 999.99,
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"tags": ["computer", "portable"]
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}
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created = container.create_item(body=item)
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print(f"Created: {created['id']}")
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```
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### Read Item
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```python
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# Read requires id AND partition key
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item = container.read_item(
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item="item-001",
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partition_key="electronics"
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)
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print(f"Name: {item['name']}")
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```
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### Update Item (Replace)
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```python
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item = container.read_item(item="item-001", partition_key="electronics")
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item["price"] = 899.99
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item["on_sale"] = True
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updated = container.replace_item(item=item["id"], body=item)
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```
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### Upsert Item
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```python
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# Create if not exists, replace if exists
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item = {
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"id": "item-002",
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"category": "electronics",
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"name": "Tablet",
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"price": 499.99
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}
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result = container.upsert_item(body=item)
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```
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### Delete Item
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```python
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container.delete_item(
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item="item-001",
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partition_key="electronics"
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)
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```
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## Queries
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### Basic Query
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```python
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# Query within a partition (efficient)
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query = "SELECT * FROM c WHERE c.price < @max_price"
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items = container.query_items(
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query=query,
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parameters=[{"name": "@max_price", "value": 500}],
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partition_key="electronics"
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)
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for item in items:
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print(f"{item['name']}: ${item['price']}")
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```
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### Cross-Partition Query
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```python
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# Cross-partition (more expensive, use sparingly)
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query = "SELECT * FROM c WHERE c.price < @max_price"
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items = container.query_items(
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query=query,
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parameters=[{"name": "@max_price", "value": 500}],
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enable_cross_partition_query=True
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)
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for item in items:
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print(item)
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```
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### Query with Projection
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```python
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query = "SELECT c.id, c.name, c.price FROM c WHERE c.category = @category"
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items = container.query_items(
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query=query,
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parameters=[{"name": "@category", "value": "electronics"}],
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partition_key="electronics"
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)
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```
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### Read All Items
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```python
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# Read all in a partition
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items = container.read_all_items() # Cross-partition
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# Or with partition key
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items = container.query_items(
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query="SELECT * FROM c",
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partition_key="electronics"
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)
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```
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## Partition Keys
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**Critical**: Always include partition key for efficient operations.
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```python
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from azure.cosmos import PartitionKey
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# Single partition key
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container = database.create_container_if_not_exists(
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id="orders",
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partition_key=PartitionKey(path="/customer_id")
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)
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# Hierarchical partition key (preview)
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container = database.create_container_if_not_exists(
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id="events",
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partition_key=PartitionKey(path=["/tenant_id", "/user_id"])
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)
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```
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## Throughput
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```python
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# Create container with provisioned throughput
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container = database.create_container_if_not_exists(
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id="mycontainer",
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partition_key=PartitionKey(path="/pk"),
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offer_throughput=400 # RU/s
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)
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# Read current throughput
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offer = container.read_offer()
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print(f"Throughput: {offer.offer_throughput} RU/s")
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# Update throughput
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container.replace_throughput(throughput=1000)
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```
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## Async Client
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```python
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from azure.cosmos.aio import CosmosClient
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from azure.identity.aio import DefaultAzureCredential
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async def cosmos_operations():
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credential = DefaultAzureCredential()
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async with CosmosClient(endpoint, credential=credential) as client:
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database = client.get_database_client("mydb")
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container = database.get_container_client("mycontainer")
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# Create
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await container.create_item(body={"id": "1", "pk": "test"})
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# Read
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item = await container.read_item(item="1", partition_key="test")
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# Query
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async for item in container.query_items(
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query="SELECT * FROM c",
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partition_key="test"
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):
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print(item)
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import asyncio
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asyncio.run(cosmos_operations())
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```
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## Error Handling
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```python
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from azure.cosmos.exceptions import CosmosHttpResponseError
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try:
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item = container.read_item(item="nonexistent", partition_key="pk")
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except CosmosHttpResponseError as e:
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if e.status_code == 404:
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print("Item not found")
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elif e.status_code == 429:
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print(f"Rate limited. Retry after: {e.headers.get('x-ms-retry-after-ms')}ms")
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else:
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raise
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```
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## Best Practices
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1. **Always specify partition key** for point reads and queries
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2. **Use parameterized queries** to prevent injection and improve caching
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3. **Avoid cross-partition queries** when possible
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4. **Use `upsert_item`** for idempotent writes
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5. **Use async client** for high-throughput scenarios
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6. **Design partition key** for even data distribution
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7. **Use `read_item`** instead of query for single document retrieval
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## Reference Files
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| File | Contents |
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|------|----------|
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| [references/partitioning.md](references/partitioning.md) | Partition key strategies, hierarchical keys, hot partition detection and mitigation |
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| [references/query-patterns.md](references/query-patterns.md) | Query optimization, aggregations, pagination, transactions, change feed |
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| [scripts/setup_cosmos_container.py](scripts/setup_cosmos_container.py) | CLI tool for creating containers with partitioning, throughput, and indexing |
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