Can I implement human oversight in these agent graphs?

Absolutely. The skill includes patterns for Human-in-the-Loop (HITL) nodes that pause execution for manual review or approval.

What is the Microsoft Agent Framework?

It is an open-source SDK that unifies research-grade patterns from AutoGen and enterprise foundations from Semantic Kernel to build robust multi-agent systems.

Does it support the Model Context Protocol (MCP)?

Yes, it includes specific implementation guides for connecting agents to external tools and services using MCP clients.

How does this skill help with long-running workflows?

It provides patterns for Checkpointing and Recovery, allowing agents to persist state to backends like Redis and resume workflows after failures.

Microsoft Agent Patterns

Name: Microsoft Agent Patterns
Author: pagerguild

bypagerguild

Ciencia de Datos y ML

Orchestrates complex multi-agent systems using Microsoft Agent Framework patterns like AutoGen and Semantic Kernel.

Acerca de

This skill provides Claude Code with expert guidance and implementation patterns for the Microsoft Agent Framework, bridging the gap between research-grade orchestration and enterprise production. It enables the creation of sophisticated agentic workflows—including sequential flows, parallel fan-out/fan-in, and autonomous group chats—with built-in support for the Model Context Protocol (MCP). Use this skill to architect durable, observable, and secure multi-agent systems that leverage OpenTelemetry and Entra ID for production-ready AI applications.

Características Principales

Stateful workflow management with Checkpointing and Recovery systems
Unified integration for AutoGen, Semantic Kernel, and Model Context Protocol (MCP)
Advanced orchestration patterns including Group Chat and Conditional Handoff
Declarative configuration for modular connectors and pluggable memory
Production-ready observability via OpenTelemetry and Azure Monitor
0 GitHub stars

Casos de Uso

Designing complex RAG pipelines that coordinate multiple research and analysis agents
Building automated software development squads with specialized planner, developer, and tester agents
Implementing enterprise support systems with human-in-the-loop approval and routing logic

Acerca de

Características Principales

Stateful workflow management with Checkpointing and Recovery systems
Unified integration for AutoGen, Semantic Kernel, and Model Context Protocol (MCP)
Advanced orchestration patterns including Group Chat and Conditional Handoff
Declarative configuration for modular connectors and pluggable memory
Production-ready observability via OpenTelemetry and Azure Monitor
0 GitHub stars

Casos de Uso

Designing complex RAG pipelines that coordinate multiple research and analysis agents
Building automated software development squads with specialized planner, developer, and tester agents
Implementing enterprise support systems with human-in-the-loop approval and routing logic