agent-framework
Create AI agents and workflows using Microsoft Agent Framework SDK. Supports single-agent and multi-agent workflow patterns. USE FOR: create agent, build agent, scaffold agent, new agent, agent framework, workflow pattern, multi-agent, MCP tools, create workflow. DO NOT USE FOR: deploying agents (use deploy), evaluating agents (use agent/evaluate), Azure AI Foundry agents without Agent Framework SDK.
What this skill does
# Create Agent with Microsoft Agent Framework Build AI agents, agentic apps, and multi-agent workflows using Microsoft Agent Framework SDK. ## Quick Reference | Property | Value | |----------|-------| | **SDK** | Microsoft Agent Framework (Python) | | **Patterns** | Single Agent, Multi-Agent Workflow | | **Server** | Azure AI Agent Server SDK (HTTP) | | **Debug** | AI Toolkit Agent Inspector + VSCode | | **Best For** | Enterprise agents with type safety, checkpointing, orchestration | ## When to Use This Skill Use when the user wants to: - **Create** a new AI agent or agentic application - **Scaffold** an agent with tools (MCP, function calling) - **Build** multi-agent workflows with orchestration patterns - **Add** HTTP server mode to an existing agent - **Configure** F5/debug support for VSCode ## Defaults - **Language**: Python - **SDK**: Microsoft Agent Framework (pin version `1.0.0b260107`) - **Server**: HTTP via Azure AI Agent Server SDK - **Environment**: Virtual environment (create or detect existing) ## References | Topic | File | Description | |-------|------|-------------| | Server Pattern | [references/agent-as-server.md](references/agent-as-server.md) | HTTP server wrapping (production) | | Debug Setup | [references/debug-setup.md](references/debug-setup.md) | VS Code configs for Agent Inspector | | Agent Samples | [references/agent-samples.md](references/agent-samples.md) | Single agent, tools, MCP, threads | | Workflow Basics | [references/workflow-basics.md](references/workflow-basics.md) | Executor types, handler signatures, edges, WorkflowBuilder โ start here for any workflow | | Workflow Agents | [references/workflow-agents.md](references/workflow-agents.md) | Agents as executor nodes, linear pipeline, run_stream event consumption | | Workflow Foundry | [references/workflow-foundry.md](references/workflow-foundry.md) | Foundry agents with bidirectional edges, loop control, register_executor factories | > ๐ก **Tip:** For advanced patterns (Reflection, Switch-Case, Fan-out/Fan-in, Loop, Human-in-Loop), search `microsoft/agent-framework` on GitHub. ## MCP Tools This skill delegates to `microsoft-foundry` MCP tools for model and project operations: | Tool | Purpose | |------|---------| | `foundry_models_list` | Browse model catalog for selection | | `foundry_models_deployments_list` | List deployed models for selection | | `foundry_resource_get` | Get project endpoint | ## Creation Workflow 1. Gather context (read agent-as-server.md + debug-setup.md + code samples) 2. Select model & configure environment 3. Implement agent/workflow code + HTTP server mode + `.vscode/` configs 4. Install dependencies (venv + requirements.txt) 5. Verify startup (Run-Fix loop) 6. Documentation ### Step 1: Gather Context Read reference files based on user's request: **Always read these references:** - Server pattern: **agent-as-server.md** (required โ HTTP server is the default) - Debug setup: **debug-setup.md** (required โ always generate `.vscode/` configs) **Read the relevant code sample:** - Code samples: agent-samples.md, workflow-basics.md, workflow-agents.md, or workflow-foundry.md **Model Selection**: Use `microsoft-foundry` skill's model catalog to help user select and deploy a model. **Recommended**: Search `microsoft/agent-framework` on GitHub for advanced patterns. ### Step 2: Select Model & Configure Environment *Decide on the model BEFORE coding.* If user hasn't specified a model, use `microsoft-foundry` skill to list deployed models or help deploy one. **ALWAYS create/update `.env` file**: ```bash FOUNDRY_PROJECT_ENDPOINT=<project-endpoint> FOUNDRY_MODEL_DEPLOYMENT_NAME=<model-deployment-name> ``` - **Standard flow**: Populate with real values from user's Foundry project - **Deferred Config**: Use placeholders, remind user to update before running ### Step 3: Implement Code **All three are required by default:** 1. **Agent/Workflow code**: Use gathered context to structure the agent or workflow 2. **HTTP Server mode**: Wrap with Agent-as-Server pattern from `agent-as-server.md` โ this is the default entry point 3. **Debug configs**: Generate `.vscode/launch.json` and `.vscode/tasks.json` using templates from `debug-setup.md` > โ ๏ธ **Warning:** Only skip server mode or debug configs if the user explicitly requests a "minimal" or "no server" setup. ### Step 4: Install Dependencies 1. Generate/update `requirements.txt` ```text # pin version to avoid breaking changes # agent framework agent-framework-azure-ai==1.0.0b260107 agent-framework-core==1.0.0b260107 # agent server (for HTTP server mode) azure-ai-agentserver-core==1.0.0b10 azure-ai-agentserver-agentframework==1.0.0b10 # debugging support debugpy agent-dev-cli ``` 2. Use a virtual environment to avoid polluting the global Python installation > โ ๏ธ **Warning:** Never use bare `python` or `pip` โ always use the venv-activated versions or full paths (e.g., `.venv/bin/pip`). ### Step 5: Verify Startup (Run-Fix Loop) Enter a run-fix loop until no startup errors: 1. Run the main entrypoint using the venv's Python (e.g., `.venv/Scripts/python main.py` on Windows, `.venv/bin/python main.py` on macOS/Linux) 2. **If startup fails**: Fix error โ Rerun 3. **If startup succeeds**: Stop server immediately **Guardrails**: - โ Perform real run to catch startup errors - โ Cleanup after verification (stop HTTP server) - โ Ignore environment/auth/connection/timeout errors - โ Don't wait for user input - โ Don't create separate test scripts - โ Don't mock configuration ### Step 6: Documentation Create/update `README.md` with setup instructions and usage examples. ## Error Handling | Error | Cause | Resolution | |-------|-------|------------| | `ModuleNotFoundError` | Missing SDK | Run `pip install agent-framework-azure-ai==1.0.0b260107` in venv | | `AgentRunResponseUpdate` not found | Wrong SDK version | Pin to `1.0.0b260107` (breaking rename in newer versions) | | Agent name validation error | Invalid characters | Use alphanumeric + hyphens, start/end with alphanumeric, max 63 chars | | Async credential error | Wrong import | Use `azure.identity.aio.DefaultAzureCredential` (not `azure.identity`) |
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