/microsoft-agent-framework

name: microsoft-agent-framework
description: "Build .NET AI agents, harnesses, and multi-agent workflows with Microsoft Agent Framework using the right agent type, sessions, tools, workflows, hosting protocols, and enterprise guardrails. USE FOR: building or reviewing .NET code that uses Microsoft.Agents.*, Microsoft.Extensions.AI, AIAgent, HarnessAgent, AgentThread, AgentSession, or Agent Framework hosting packages; choosing agent, harness, workflow, and hosting shapes. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made."
compatibility: "Requires current Microsoft Agent Framework packages and a .NET application that truly needs agentic or workflow orchestration; declarative, hosting, and advanced Harness surfaces may remain preview or experimental."

Microsoft Agent Framework

Trigger On

• building or reviewing `.NET` code that uses `Microsoft.Agents.*`, `Microsoft.Extensions.AI`, `AIAgent`, `HarnessAgent`, `AgentThread`, `AgentSession`, or Agent Framework hosting packages
• choosing between `ChatClientAgent`, Responses agents, hosted agents, custom agents, Anthropic agents, workflows, or durable agents
• adding the batteries-included `Microsoft.Agents.AI.Harness` surface for planning, todos, compaction, file memory/access, tool approvals, skills, shell execution, or background agents
• authoring preview-era `Microsoft.Agents.AI.Workflows.Declarative*` packages or wrapping a workflow with `workflow.AsAIAgent()`
• adding tools, MCP, A2A, OpenAI-compatible hosting, AG-UI, DevUI, background responses, or OpenTelemetry
• migrating from Semantic Kernel agent APIs or aligning AutoGen-style multi-agent patterns to Agent Framework
• using Anthropic Claude models (haiku, sonnet, opus) via `AnthropicClient` or through Azure Foundry with `AnthropicFoundryClient`

Workflow

1. Decide whether the problem should stay deterministic. If plain code or a typed workflow without LLM autonomy is enough, do that instead of adding an agent. 2. Choose the execution shape first: single `AIAgent`, batteries-included `HarnessAgent`, explicit programmatic `Workflow`, workflow-as-agent wrapper, declarative workflow when YAML portability is explicitly required, Azure Functions durable agent, ASP.NET Core hosted agent, AG-UI remote UI, or DevUI local debugging. 3. Choose the agent type and provider intentionally. Prefer the simplest agent that satisfies the threading, tooling, and hosting requirements. 4. Keep agents stateless and keep conversation or long-lived state in provider-owned session objects. Most persistence guidance still centers on `AgentThread`, while newer middleware and background-response examples may surface `AgentSession`. Treat both as opaque provider-specific state. 5. Add only the tools and middleware that the scenario needs. Narrow the tool surface, require approval for side effects, and treat MCP, A2A, and third-party services as trust boundaries. 6. For workflows, model executors, edges, typed `RequestPort` boundaries, checkpoints, shared state, and human-in-the-loop explicitly rather than hiding control flow in prompts. 7. Prefer Responses-based protocols for new remote/OpenAI-compatible integrations unless you specifically need Chat Completions compatibility. 8. Use durable agents only when you truly need Azure Functions serverless hosting, durable thread storage, or deterministic long-running orchestrations. 9. Verify preview status, package maturity, docs recency, and provider-specific limitations before locking a production architecture.

Current Upstream Notes

• `dotnet-1.15.0` adds public OpenAI Responses protocol helpers, session deletion, and hosted workflow state. The application still owns routing, authorization, and durable storage.
• `dotnet-1.14.0` graduates the core Harness API but keeps its package and advanced options prerelease or experimental. It also makes file access opt-in, binds approvals to surfaced requests, and splits AG-UI packages and server registration. See [harness.md](references/harness.md) and [hosting.md](references/hosting.md).
• The August 2026 documentation set now treats middleware, background responses, durable agents, AG-UI frontend and backend tools, MCP-hosted agents, observability, support, upgrades, and Semantic Kernel or AutoGen migration as first-class paths. Load the matching reference file before implementation and verify package maturity plus exact signatures against the linked official page; the expanded documentation does not make every provider or preview feature interchangeable.

Architecture

flowchart LR
  A["Task"] --> B{"Deterministic code is enough?"}
  B -->|Yes| C["Write normal .NET code or a plain workflow"]
  B -->|No| D{"One dynamic decision-maker is enough?"}
  D -->|Yes| O{"Needs a packaged long-task runtime?"}
  O -->|No| E["Use an `AIAgent` / `ChatClientAgent`"]
  O -->|Yes| P["Use `HarnessAgent` with scoped capabilities"]
  D -->|No| F["Use a typed `Workflow`"]
  F --> G{"Needs durable Azure hosting or week-long execution?"}
  G -->|Yes| H["Use durable agents on Azure Functions"]
  G -->|No| I["Use in-process workflows"]
  E --> J{"Need a remote protocol or UI?"}
  P --> J
  F --> J
  J -->|OpenAI-compatible HTTP| K["ASP.NET Core Hosting.OpenAI"]
  J -->|Agent-to-agent protocol| L["A2A hosting"]
  J -->|Web UI protocol| M["AG-UI"]
  J -->|Local debug shell| N["DevUI (dev only)"]

Core Knowledge

• `AIAgent` is the common runtime abstraction. It should stay mostly stateless.
• `AgentThread` still anchors most persisted conversation guidance, but some newer runtime surfaces now pass `AgentSession` instead. Treat either state object as opaque provider-owned data and verify exact callback signatures against the current official page.
• `AgentResponse` and `AgentResponseUpdate` are not just text containers. They