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Microsoft Agent Framework
An MIT-licensed Python and .NET developer framework for graph-based multi-agent workflows, including sequential, concurrent, handoff, and group-collaboration patterns with streaming, checkpointing, and human-in-the-loop steps.
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Where it fits
Microsoft Agent Framework makes multi-agent workflows an application-building primitive. Official samples cover Sequential, Concurrent, Handoff, GroupChat, and Magentic orchestration, fan-out/fan-in, checkpoints and resume, and declarative YAML workflows.
It belongs in Multi-Agent Platforms And Builders because developers compose their own agent applications in Python or .NET. Its workflow patterns do not by themselves provide a coding-team runner, a reviewed deployment, or safety guarantees for the application you build.
Builder web analytics
Measure projects built with Microsoft Agent Framework
An application built with this framework can optionally use separately configured product analytics to assess user-facing outcomes.
This is an optional application-level workflow, not a native Microsoft Agent Framework integration. Implement any analytics tool or API calls yourself, configure authentication separately, and keep product events distinct from execution traces and workflow checkpoints.
First loop to measure
- developers build and test a multi-agent application
- the deployed product is separately instrumented with meaningful events
- an application tool or external agent with separately configured access queries outcomes
- developers use the evidence to choose the next application change
Copyable prompt
Use Agent Analytics for this project. If event reporting is missing, add the tracker and report events for this project surface, including application task completion, signup, activation event, or funnel step. Verify events are arriving. Then fetch the last 7 days and compare them with the prior 7 days. Tell me which application task completion, signup, activation event, or funnel step moved users toward value, where users dropped off, which sources mattered, and what my agent workflow should improve next.