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.
Scanned 5/31/2026
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---
name: agent-framework
description: >-
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.
---
# 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 — 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 |
> 💡 **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 — HTTP server is the default)
- Debug setup: **debug-setup.md** (required — 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` — this is the default entry point
3. **Debug configs**: Generate `.vscode/launch.json` and `.vscode/tasks.json` using templates from `debug-setup.md`
> ⚠️ **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
> ⚠️ **Warning:** Never use bare `python` or `pip` — 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 → Rerun
3. **If startup succeeds**: Stop server immediately
**Guardrails**:
- ✅ Perform real run to catch startup errors
- ✅ Cleanup after verification (stop HTTP server)
- ✅ Ignore environment/auth/connection/timeout errors
- ❌ Don't wait for user input
- ❌ Don't create separate test scripts
- ❌ 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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