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.

skills/official/microsoft/python/monitoring/opentelemetry/SKILL.md

@@ -0,0 +1,224 @@
+---
+name: azure-monitor-opentelemetry-py
+description: |
+  Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.
+  Triggers: "azure-monitor-opentelemetry", "configure_azure_monitor", "Application Insights", "OpenTelemetry distro", "auto-instrumentation".
+package: azure-monitor-opentelemetry
+---
+
+# Azure Monitor OpenTelemetry Distro for Python
+
+One-line setup for Application Insights with OpenTelemetry auto-instrumentation.
+
+## Installation
+
+```bash
+pip install azure-monitor-opentelemetry
+```
+
+## Environment Variables
+
+```bash
+APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/
+```
+
+## Quick Start
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+# One-line setup - reads connection string from environment
+configure_azure_monitor()
+
+# Your application code...
+```
+
+## Explicit Configuration
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor(
+    connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/"
+)
+```
+
+## With Flask
+
+```python
+from flask import Flask
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+app = Flask(__name__)
+
+@app.route("/")
+def hello():
+    return "Hello, World!"
+
+if __name__ == "__main__":
+    app.run()
+```
+
+## With Django
+
+```python
+# settings.py
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+# Django settings...
+```
+
+## With FastAPI
+
+```python
+from fastapi import FastAPI
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+app = FastAPI()
+
+@app.get("/")
+async def root():
+    return {"message": "Hello World"}
+```
+
+## Custom Traces
+
+```python
+from opentelemetry import trace
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+tracer = trace.get_tracer(__name__)
+
+with tracer.start_as_current_span("my-operation") as span:
+    span.set_attribute("custom.attribute", "value")
+    # Do work...
+```
+
+## Custom Metrics
+
+```python
+from opentelemetry import metrics
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+meter = metrics.get_meter(__name__)
+counter = meter.create_counter("my_counter")
+
+counter.add(1, {"dimension": "value"})
+```
+
+## Custom Logs
+
+```python
+import logging
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor()
+
+logger = logging.getLogger(__name__)
+logger.setLevel(logging.INFO)
+
+logger.info("This will appear in Application Insights")
+logger.error("Errors are captured too", exc_info=True)
+```
+
+## Sampling
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+# Sample 10% of requests
+configure_azure_monitor(
+    sampling_ratio=0.1
+)
+```
+
+## Cloud Role Name
+
+Set cloud role name for Application Map:
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+from opentelemetry.sdk.resources import Resource, SERVICE_NAME
+
+configure_azure_monitor(
+    resource=Resource.create({SERVICE_NAME: "my-service-name"})
+)
+```
+
+## Disable Specific Instrumentations
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor(
+    instrumentations=["flask", "requests"]  # Only enable these
+)
+```
+
+## Enable Live Metrics
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+
+configure_azure_monitor(
+    enable_live_metrics=True
+)
+```
+
+## Azure AD Authentication
+
+```python
+from azure.monitor.opentelemetry import configure_azure_monitor
+from azure.identity import DefaultAzureCredential
+
+configure_azure_monitor(
+    credential=DefaultAzureCredential()
+)
+```
+
+## Auto-Instrumentations Included
+
+| Library | Telemetry Type |
+|---------|---------------|
+| Flask | Traces |
+| Django | Traces |
+| FastAPI | Traces |
+| Requests | Traces |
+| urllib3 | Traces |
+| httpx | Traces |
+| aiohttp | Traces |
+| psycopg2 | Traces |
+| pymysql | Traces |
+| pymongo | Traces |
+| redis | Traces |
+
+## Configuration Options
+
+| Parameter | Description | Default |
+|-----------|-------------|---------|
+| `connection_string` | Application Insights connection string | From env var |
+| `credential` | Azure credential for AAD auth | None |
+| `sampling_ratio` | Sampling rate (0.0 to 1.0) | 1.0 |
+| `resource` | OpenTelemetry Resource | Auto-detected |
+| `instrumentations` | List of instrumentations to enable | All |
+| `enable_live_metrics` | Enable Live Metrics stream | False |
+
+## Best Practices
+
+1. **Call configure_azure_monitor() early** — Before importing instrumented libraries
+2. **Use environment variables** for connection string in production
+3. **Set cloud role name** for multi-service applications
+4. **Enable sampling** in high-traffic applications
+5. **Use structured logging** for better log analytics queries
+6. **Add custom attributes** to spans for better debugging
+7. **Use AAD authentication** for production workloads