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/queue/SKILL.md
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skills/official/microsoft/python/data/queue/SKILL.md
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---
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name: azure-storage-queue-py
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description: |
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Azure Queue Storage SDK for Python. Use for reliable message queuing, task distribution, and asynchronous processing.
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Triggers: "queue storage", "QueueServiceClient", "QueueClient", "message queue", "dequeue".
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package: azure-storage-queue
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---
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# Azure Queue Storage SDK for Python
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Simple, cost-effective message queuing for asynchronous communication.
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## Installation
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```bash
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pip install azure-storage-queue azure-identity
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```
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## Environment Variables
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```bash
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AZURE_STORAGE_ACCOUNT_URL=https://<account>.queue.core.windows.net
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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.storage.queue import QueueServiceClient, QueueClient
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credential = DefaultAzureCredential()
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account_url = "https://<account>.queue.core.windows.net"
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# Service client
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service_client = QueueServiceClient(account_url=account_url, credential=credential)
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# Queue client
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queue_client = QueueClient(account_url=account_url, queue_name="myqueue", credential=credential)
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```
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## Queue Operations
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```python
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# Create queue
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service_client.create_queue("myqueue")
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# Get queue client
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queue_client = service_client.get_queue_client("myqueue")
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# Delete queue
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service_client.delete_queue("myqueue")
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# List queues
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for queue in service_client.list_queues():
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print(queue.name)
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```
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## Send Messages
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```python
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# Send message (string)
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queue_client.send_message("Hello, Queue!")
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# Send with options
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queue_client.send_message(
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content="Delayed message",
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visibility_timeout=60, # Hidden for 60 seconds
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time_to_live=3600 # Expires in 1 hour
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)
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# Send JSON
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import json
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data = {"task": "process", "id": 123}
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queue_client.send_message(json.dumps(data))
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```
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## Receive Messages
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```python
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# Receive messages (makes them invisible temporarily)
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messages = queue_client.receive_messages(
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messages_per_page=10,
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visibility_timeout=30 # 30 seconds to process
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)
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for message in messages:
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print(f"ID: {message.id}")
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print(f"Content: {message.content}")
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print(f"Dequeue count: {message.dequeue_count}")
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# Process message...
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# Delete after processing
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queue_client.delete_message(message)
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```
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## Peek Messages
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```python
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# Peek without hiding (doesn't affect visibility)
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messages = queue_client.peek_messages(max_messages=5)
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for message in messages:
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print(message.content)
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```
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## Update Message
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```python
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# Extend visibility or update content
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messages = queue_client.receive_messages()
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for message in messages:
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# Extend timeout (need more time)
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queue_client.update_message(
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message,
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visibility_timeout=60
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)
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# Update content and timeout
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queue_client.update_message(
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message,
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content="Updated content",
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visibility_timeout=60
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)
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```
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## Delete Message
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```python
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# Delete after successful processing
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messages = queue_client.receive_messages()
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for message in messages:
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try:
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# Process...
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queue_client.delete_message(message)
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except Exception:
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# Message becomes visible again after timeout
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pass
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```
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## Clear Queue
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```python
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# Delete all messages
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queue_client.clear_messages()
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```
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## Queue Properties
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```python
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# Get queue properties
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properties = queue_client.get_queue_properties()
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print(f"Approximate message count: {properties.approximate_message_count}")
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# Set/get metadata
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queue_client.set_queue_metadata(metadata={"environment": "production"})
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properties = queue_client.get_queue_properties()
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print(properties.metadata)
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```
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## Async Client
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```python
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from azure.storage.queue.aio import QueueServiceClient, QueueClient
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from azure.identity.aio import DefaultAzureCredential
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async def queue_operations():
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credential = DefaultAzureCredential()
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async with QueueClient(
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account_url="https://<account>.queue.core.windows.net",
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queue_name="myqueue",
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credential=credential
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) as client:
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# Send
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await client.send_message("Async message")
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# Receive
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async for message in client.receive_messages():
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print(message.content)
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await client.delete_message(message)
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import asyncio
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asyncio.run(queue_operations())
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```
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## Base64 Encoding
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```python
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from azure.storage.queue import QueueClient, BinaryBase64EncodePolicy, BinaryBase64DecodePolicy
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# For binary data
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queue_client = QueueClient(
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account_url=account_url,
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queue_name="myqueue",
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credential=credential,
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message_encode_policy=BinaryBase64EncodePolicy(),
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message_decode_policy=BinaryBase64DecodePolicy()
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)
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# Send bytes
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queue_client.send_message(b"Binary content")
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```
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## Best Practices
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1. **Delete messages after processing** to prevent reprocessing
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2. **Set appropriate visibility timeout** based on processing time
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3. **Handle `dequeue_count`** for poison message detection
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4. **Use async client** for high-throughput scenarios
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5. **Use `peek_messages`** for monitoring without affecting queue
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6. **Set `time_to_live`** to prevent stale messages
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7. **Consider Service Bus** for advanced features (sessions, topics)
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