agent-framework-azure-ai-py
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
Profile →npx skills add microsoft/skills --skill agent-framework-azure-ai-py --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Agent Framework Azure Hosted Agents Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK. ## Architecture ``` User Query → AzureAIAgentsProvider → Azure AI Agent Service (Persistent) ↓ Agent.run() / Agent.run_stream() ↓ Tools: Functions | Hosted (Code/Search/Web) | MCP ↓ AgentThread (conversation persistence) ``` ## Installation ```bash # Full framework (rec
What does the agent-framework-azure-ai-py skill do?
Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.
How do I install it?
Run `npx skills add microsoft/skills --skill agent-framework-azure-ai-py --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From microsoft/skills, a repository with 2,860 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.