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/java/foundry/projects/SKILL.md
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skills/official/microsoft/java/foundry/projects/SKILL.md
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---
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name: azure-ai-projects-java
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description: |
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Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.
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Triggers: "AIProjectClient java", "azure ai projects java", "Foundry project java", "ConnectionsClient", "DatasetsClient", "IndexesClient".
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package: com.azure:azure-ai-projects
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---
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# Azure AI Projects SDK for Java
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High-level SDK for Azure AI Foundry project management with access to connections, datasets, indexes, and evaluations.
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## Installation
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```xml
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<dependency>
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<groupId>com.azure</groupId>
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<artifactId>azure-ai-projects</artifactId>
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<version>1.0.0-beta.1</version>
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</dependency>
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```
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## Environment Variables
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```bash
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PROJECT_ENDPOINT=https://<resource>.services.ai.azure.com/api/projects/<project>
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```
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## Authentication
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```java
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import com.azure.ai.projects.AIProjectClientBuilder;
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import com.azure.identity.DefaultAzureCredentialBuilder;
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AIProjectClientBuilder builder = new AIProjectClientBuilder()
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.endpoint(System.getenv("PROJECT_ENDPOINT"))
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.credential(new DefaultAzureCredentialBuilder().build());
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```
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## Client Hierarchy
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The SDK provides multiple sub-clients for different operations:
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| Client | Purpose |
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|--------|---------|
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| `ConnectionsClient` | Enumerate connected Azure resources |
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| `DatasetsClient` | Upload documents and manage datasets |
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| `DeploymentsClient` | Enumerate AI model deployments |
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| `IndexesClient` | Create and manage search indexes |
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| `EvaluationsClient` | Run AI model evaluations |
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| `EvaluatorsClient` | Manage evaluator configurations |
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| `SchedulesClient` | Manage scheduled operations |
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```java
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// Build sub-clients from builder
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ConnectionsClient connectionsClient = builder.buildConnectionsClient();
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DatasetsClient datasetsClient = builder.buildDatasetsClient();
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DeploymentsClient deploymentsClient = builder.buildDeploymentsClient();
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IndexesClient indexesClient = builder.buildIndexesClient();
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EvaluationsClient evaluationsClient = builder.buildEvaluationsClient();
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```
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## Core Operations
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### List Connections
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```java
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import com.azure.ai.projects.models.Connection;
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import com.azure.core.http.rest.PagedIterable;
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PagedIterable<Connection> connections = connectionsClient.listConnections();
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for (Connection connection : connections) {
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System.out.println("Name: " + connection.getName());
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System.out.println("Type: " + connection.getType());
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System.out.println("Credential Type: " + connection.getCredentials().getType());
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}
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```
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### List Indexes
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```java
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indexesClient.listLatest().forEach(index -> {
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System.out.println("Index name: " + index.getName());
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System.out.println("Version: " + index.getVersion());
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System.out.println("Description: " + index.getDescription());
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});
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```
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### Create or Update Index
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```java
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import com.azure.ai.projects.models.AzureAISearchIndex;
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import com.azure.ai.projects.models.Index;
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String indexName = "my-index";
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String indexVersion = "1.0";
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String searchConnectionName = System.getenv("AI_SEARCH_CONNECTION_NAME");
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String searchIndexName = System.getenv("AI_SEARCH_INDEX_NAME");
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Index index = indexesClient.createOrUpdate(
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indexName,
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indexVersion,
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new AzureAISearchIndex()
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.setConnectionName(searchConnectionName)
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.setIndexName(searchIndexName)
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);
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System.out.println("Created index: " + index.getName());
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```
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### Access OpenAI Evaluations
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The SDK exposes OpenAI's official SDK for evaluations:
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```java
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import com.openai.services.EvalService;
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EvalService evalService = evaluationsClient.getOpenAIClient();
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// Use OpenAI evaluation APIs directly
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```
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## Best Practices
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1. **Use DefaultAzureCredential** for production authentication
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2. **Reuse client builder** to create multiple sub-clients efficiently
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3. **Handle pagination** when listing resources with `PagedIterable`
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4. **Use environment variables** for connection names and configuration
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5. **Check connection types** before accessing credentials
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## Error Handling
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```java
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import com.azure.core.exception.HttpResponseException;
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import com.azure.core.exception.ResourceNotFoundException;
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try {
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Index index = indexesClient.get(indexName, version);
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} catch (ResourceNotFoundException e) {
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System.err.println("Index not found: " + indexName);
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} catch (HttpResponseException e) {
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System.err.println("Error: " + e.getResponse().getStatusCode());
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}
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```
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## Reference Links
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| Resource | URL |
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|----------|-----|
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| Product Docs | https://learn.microsoft.com/azure/ai-studio/ |
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| API Reference | https://learn.microsoft.com/rest/api/aifoundry/aiprojects/ |
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| GitHub Source | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-projects |
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| Samples | https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/ai/azure-ai-projects/src/samples |
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