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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---
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name: azure-monitor-opentelemetry-exporter-py
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description: |
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Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights.
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Triggers: "azure-monitor-opentelemetry-exporter", "AzureMonitorTraceExporter", "AzureMonitorMetricExporter", "AzureMonitorLogExporter".
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package: azure-monitor-opentelemetry-exporter
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---
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# Azure Monitor OpenTelemetry Exporter for Python
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Low-level exporter for sending OpenTelemetry traces, metrics, and logs to Application Insights.
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## Installation
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```bash
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pip install azure-monitor-opentelemetry-exporter
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```
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## Environment Variables
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```bash
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APPLICATIONINSIGHTS_CONNECTION_STRING=InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.com/
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```
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## When to Use
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| Scenario | Use |
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|----------|-----|
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| Quick setup, auto-instrumentation | `azure-monitor-opentelemetry` (distro) |
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| Custom OpenTelemetry pipeline | `azure-monitor-opentelemetry-exporter` (this) |
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| Fine-grained control over telemetry | `azure-monitor-opentelemetry-exporter` (this) |
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## Trace Exporter
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```python
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from opentelemetry import trace
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.sdk.trace.export import BatchSpanProcessor
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from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
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# Create exporter
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exporter = AzureMonitorTraceExporter(
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connection_string="InstrumentationKey=xxx;..."
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)
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# Configure tracer provider
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trace.set_tracer_provider(TracerProvider())
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trace.get_tracer_provider().add_span_processor(
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BatchSpanProcessor(exporter)
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)
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# Use tracer
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tracer = trace.get_tracer(__name__)
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with tracer.start_as_current_span("my-span"):
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print("Hello, World!")
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```
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## Metric Exporter
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```python
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from opentelemetry import metrics
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from opentelemetry.sdk.metrics import MeterProvider
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from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
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from azure.monitor.opentelemetry.exporter import AzureMonitorMetricExporter
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# Create exporter
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exporter = AzureMonitorMetricExporter(
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connection_string="InstrumentationKey=xxx;..."
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)
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# Configure meter provider
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reader = PeriodicExportingMetricReader(exporter, export_interval_millis=60000)
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metrics.set_meter_provider(MeterProvider(metric_readers=[reader]))
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# Use meter
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meter = metrics.get_meter(__name__)
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counter = meter.create_counter("requests_total")
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counter.add(1, {"route": "/api/users"})
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```
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## Log Exporter
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```python
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import logging
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from opentelemetry._logs import set_logger_provider
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from opentelemetry.sdk._logs import LoggerProvider, LoggingHandler
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from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
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from azure.monitor.opentelemetry.exporter import AzureMonitorLogExporter
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# Create exporter
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exporter = AzureMonitorLogExporter(
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connection_string="InstrumentationKey=xxx;..."
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)
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# Configure logger provider
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logger_provider = LoggerProvider()
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logger_provider.add_log_record_processor(BatchLogRecordProcessor(exporter))
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set_logger_provider(logger_provider)
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# Add handler to Python logging
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handler = LoggingHandler(level=logging.INFO, logger_provider=logger_provider)
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logging.getLogger().addHandler(handler)
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# Use logging
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logger = logging.getLogger(__name__)
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logger.info("This will be sent to Application Insights")
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```
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## From Environment Variable
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Exporters read `APPLICATIONINSIGHTS_CONNECTION_STRING` automatically:
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```python
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from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
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# Connection string from environment
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exporter = AzureMonitorTraceExporter()
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```
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## Azure AD Authentication
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```python
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from azure.identity import DefaultAzureCredential
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from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
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exporter = AzureMonitorTraceExporter(
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credential=DefaultAzureCredential()
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)
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```
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## Sampling
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Use `ApplicationInsightsSampler` for consistent sampling:
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```python
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from opentelemetry.sdk.trace import TracerProvider
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from opentelemetry.sdk.trace.sampling import ParentBasedTraceIdRatio
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from azure.monitor.opentelemetry.exporter import ApplicationInsightsSampler
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# Sample 10% of traces
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sampler = ApplicationInsightsSampler(sampling_ratio=0.1)
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trace.set_tracer_provider(TracerProvider(sampler=sampler))
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```
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## Offline Storage
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Configure offline storage for retry:
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```python
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from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
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exporter = AzureMonitorTraceExporter(
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connection_string="...",
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storage_directory="/path/to/storage", # Custom storage path
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disable_offline_storage=False # Enable retry (default)
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)
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```
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## Disable Offline Storage
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```python
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exporter = AzureMonitorTraceExporter(
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connection_string="...",
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disable_offline_storage=True # No retry on failure
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)
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```
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## Sovereign Clouds
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```python
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from azure.identity import AzureAuthorityHosts, DefaultAzureCredential
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from azure.monitor.opentelemetry.exporter import AzureMonitorTraceExporter
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# Azure Government
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credential = DefaultAzureCredential(authority=AzureAuthorityHosts.AZURE_GOVERNMENT)
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exporter = AzureMonitorTraceExporter(
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connection_string="InstrumentationKey=xxx;IngestionEndpoint=https://xxx.in.applicationinsights.azure.us/",
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credential=credential
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)
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```
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## Exporter Types
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| Exporter | Telemetry Type | Application Insights Table |
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|----------|---------------|---------------------------|
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| `AzureMonitorTraceExporter` | Traces/Spans | requests, dependencies, exceptions |
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| `AzureMonitorMetricExporter` | Metrics | customMetrics, performanceCounters |
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| `AzureMonitorLogExporter` | Logs | traces, customEvents |
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## Configuration Options
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| Parameter | Description | Default |
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|-----------|-------------|---------|
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| `connection_string` | Application Insights connection string | From env var |
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| `credential` | Azure credential for AAD auth | None |
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| `disable_offline_storage` | Disable retry storage | False |
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| `storage_directory` | Custom storage path | Temp directory |
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## Best Practices
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1. **Use BatchSpanProcessor** for production (not SimpleSpanProcessor)
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2. **Use ApplicationInsightsSampler** for consistent sampling across services
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3. **Enable offline storage** for reliability in production
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4. **Use AAD authentication** instead of instrumentation keys
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5. **Set export intervals** appropriate for your workload
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6. **Use the distro** (`azure-monitor-opentelemetry`) unless you need custom pipelines
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