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.
2026-02-11 20:16:23 +05:00
parent 167d7c97c7
commit 17bce709de
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--- a/skills/official/microsoft/python/foundry/projects/SKILL.md
+++ b/skills/official/microsoft/python/foundry/projects/SKILL.md
@@ -0,0 +1,295 @@
+---
+name: azure-ai-projects-py
+description: Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.
+package: azure-ai-projects
+---
+
+# Azure AI Projects Python SDK (Foundry SDK)
+
+Build AI applications on Microsoft Foundry using the `azure-ai-projects` SDK.
+
+## Installation
+
+```bash
+pip install azure-ai-projects azure-identity
+```
+
+## Environment Variables
+
+```bash
+AZURE_AI_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
+AZURE_AI_MODEL_DEPLOYMENT_NAME="gpt-4o-mini"
+```
+
+## Authentication
+
+```python
+import os
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects import AIProjectClient
+
+credential = DefaultAzureCredential()
+client = AIProjectClient(
+    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+    credential=credential,
+)
+```
+
+## Client Operations Overview
+
+| Operation | Access | Purpose |
+|-----------|--------|---------|
+| `client.agents` | `.agents.*` | Agent CRUD, versions, threads, runs |
+| `client.connections` | `.connections.*` | List/get project connections |
+| `client.deployments` | `.deployments.*` | List model deployments |
+| `client.datasets` | `.datasets.*` | Dataset management |
+| `client.indexes` | `.indexes.*` | Index management |
+| `client.evaluations` | `.evaluations.*` | Run evaluations |
+| `client.red_teams` | `.red_teams.*` | Red team operations |
+
+## Two Client Approaches
+
+### 1. AIProjectClient (Native Foundry)
+
+```python
+from azure.ai.projects import AIProjectClient
+
+client = AIProjectClient(
+    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+    credential=DefaultAzureCredential(),
+)
+
+# Use Foundry-native operations
+agent = client.agents.create_agent(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    name="my-agent",
+    instructions="You are helpful.",
+)
+```
+
+### 2. OpenAI-Compatible Client
+
+```python
+# Get OpenAI-compatible client from project
+openai_client = client.get_openai_client()
+
+# Use standard OpenAI API
+response = openai_client.chat.completions.create(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    messages=[{"role": "user", "content": "Hello!"}],
+)
+```
+
+## Agent Operations
+
+### Create Agent (Basic)
+
+```python
+agent = client.agents.create_agent(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    name="my-agent",
+    instructions="You are a helpful assistant.",
+)
+```
+
+### Create Agent with Tools
+
+```python
+from azure.ai.agents import CodeInterpreterTool, FileSearchTool
+
+agent = client.agents.create_agent(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    name="tool-agent",
+    instructions="You can execute code and search files.",
+    tools=[CodeInterpreterTool(), FileSearchTool()],
+)
+```
+
+### Versioned Agents with PromptAgentDefinition
+
+```python
+from azure.ai.projects.models import PromptAgentDefinition
+
+# Create a versioned agent
+agent_version = client.agents.create_version(
+    agent_name="customer-support-agent",
+    definition=PromptAgentDefinition(
+        model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+        instructions="You are a customer support specialist.",
+        tools=[],  # Add tools as needed
+    ),
+    version_label="v1.0",
+)
+```
+
+See [references/agents.md](references/agents.md) for detailed agent patterns.
+
+## Tools Overview
+
+| Tool | Class | Use Case |
+|------|-------|----------|
+| Code Interpreter | `CodeInterpreterTool` | Execute Python, generate files |
+| File Search | `FileSearchTool` | RAG over uploaded documents |
+| Bing Grounding | `BingGroundingTool` | Web search (requires connection) |
+| Azure AI Search | `AzureAISearchTool` | Search your indexes |
+| Function Calling | `FunctionTool` | Call your Python functions |
+| OpenAPI | `OpenApiTool` | Call REST APIs |
+| MCP | `McpTool` | Model Context Protocol servers |
+| Memory Search | `MemorySearchTool` | Search agent memory stores |
+| SharePoint | `SharepointGroundingTool` | Search SharePoint content |
+
+See [references/tools.md](references/tools.md) for all tool patterns.
+
+## Thread and Message Flow
+
+```python
+# 1. Create thread
+thread = client.agents.threads.create()
+
+# 2. Add message
+client.agents.messages.create(
+    thread_id=thread.id,
+    role="user",
+    content="What's the weather like?",
+)
+
+# 3. Create and process run
+run = client.agents.runs.create_and_process(
+    thread_id=thread.id,
+    agent_id=agent.id,
+)
+
+# 4. Get response
+if run.status == "completed":
+    messages = client.agents.messages.list(thread_id=thread.id)
+    for msg in messages:
+        if msg.role == "assistant":
+            print(msg.content[0].text.value)
+```
+
+## Connections
+
+```python
+# List all connections
+connections = client.connections.list()
+for conn in connections:
+    print(f"{conn.name}: {conn.connection_type}")
+
+# Get specific connection
+connection = client.connections.get(connection_name="my-search-connection")
+```
+
+See [references/connections.md](references/connections.md) for connection patterns.
+
+## Deployments
+
+```python
+# List available model deployments
+deployments = client.deployments.list()
+for deployment in deployments:
+    print(f"{deployment.name}: {deployment.model}")
+```
+
+See [references/deployments.md](references/deployments.md) for deployment patterns.
+
+## Datasets and Indexes
+
+```python
+# List datasets
+datasets = client.datasets.list()
+
+# List indexes
+indexes = client.indexes.list()
+```
+
+See [references/datasets-indexes.md](references/datasets-indexes.md) for data operations.
+
+## Evaluation
+
+```python
+# Using OpenAI client for evals
+openai_client = client.get_openai_client()
+
+# Create evaluation with built-in evaluators
+eval_run = openai_client.evals.runs.create(
+    eval_id="my-eval",
+    name="quality-check",
+    data_source={
+        "type": "custom",
+        "item_references": [{"item_id": "test-1"}],
+    },
+    testing_criteria=[
+        {"type": "fluency"},
+        {"type": "task_adherence"},
+    ],
+)
+```
+
+See [references/evaluation.md](references/evaluation.md) for evaluation patterns.
+
+## Async Client
+
+```python
+from azure.ai.projects.aio import AIProjectClient
+
+async with AIProjectClient(
+    endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
+    credential=DefaultAzureCredential(),
+) as client:
+    agent = await client.agents.create_agent(...)
+    # ... async operations
+```
+
+See [references/async-patterns.md](references/async-patterns.md) for async patterns.
+
+## Memory Stores
+
+```python
+# Create memory store for agent
+memory_store = client.agents.create_memory_store(
+    name="conversation-memory",
+)
+
+# Attach to agent for persistent memory
+agent = client.agents.create_agent(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    name="memory-agent",
+    tools=[MemorySearchTool()],
+    tool_resources={"memory": {"store_ids": [memory_store.id]}},
+)
+```
+
+## Best Practices
+
+1. **Use context managers** for async client: `async with AIProjectClient(...) as client:`
+2. **Clean up agents** when done: `client.agents.delete_agent(agent.id)`
+3. **Use `create_and_process`** for simple runs, **streaming** for real-time UX
+4. **Use versioned agents** for production deployments
+5. **Prefer connections** for external service integration (AI Search, Bing, etc.)
+
+## SDK Comparison
+
+| Feature | `azure-ai-projects` | `azure-ai-agents` |
+|---------|---------------------|-------------------|
+| Level | High-level (Foundry) | Low-level (Agents) |
+| Client | `AIProjectClient` | `AgentsClient` |
+| Versioning | `create_version()` | Not available |
+| Connections | Yes | No |
+| Deployments | Yes | No |
+| Datasets/Indexes | Yes | No |
+| Evaluation | Via OpenAI client | No |
+| When to use | Full Foundry integration | Standalone agent apps |
+
+## Reference Files
+
+- [references/agents.md](references/agents.md): Agent operations with PromptAgentDefinition
+- [references/tools.md](references/tools.md): All agent tools with examples
+- [references/evaluation.md](references/evaluation.md): Evaluation operations overview
+- [references/built-in-evaluators.md](references/built-in-evaluators.md): Complete built-in evaluator reference
+- [references/custom-evaluators.md](references/custom-evaluators.md): Code and prompt-based evaluator patterns
+- [references/connections.md](references/connections.md): Connection operations
+- [references/deployments.md](references/deployments.md): Deployment enumeration
+- [references/datasets-indexes.md](references/datasets-indexes.md): Dataset and index operations
+- [references/async-patterns.md](references/async-patterns.md): Async client usage
+- [references/api-reference.md](references/api-reference.md): Complete API reference for all 373 SDK exports (v2.0.0b4)
+- [scripts/run_batch_evaluation.py](scripts/run_batch_evaluation.py): CLI tool for batch evaluations