Can I add human intervention to these agent workflows?

Yes, the skill includes patterns for 'Human-in-the-loop' using ApprovalGate for manual reviews and InputGate for gathering additional information during execution.

What orchestration patterns does this skill support?

It supports five main patterns: Sequential (linear steps), Concurrent (parallel execution), Handoff (conditional routing), Group Chat (multi-agent discussion), and Magentic (dynamic orchestration based on capabilities).

How does this skill handle workflow failures?

It provides implementation patterns for RetryStrategy with exponential backoff and FallbackStrategy to handle timeouts or specific agent errors gracefully.

Is it possible to combine different workflow types?

Absolutely. The skill covers Workflow Composition, allowing you to nest a concurrent research workflow inside a sequential content production pipeline.

Does it support state persistence and recovery?

Yes, it includes guidance for checkpointing using Redis, allowing long-running workflows to resume from the last successful step if an error occurs.

Microsoft Agent Workflows

Name: Microsoft Agent Workflows
Author: pagerguild

bypagerguild

생산성 및 워크플로

Builds and orchestrates complex multi-agent workflows using the Microsoft Agent Framework within Claude Code.

소개

This skill provides expert guidance for designing and implementing advanced multi-agent systems using the Microsoft Agent Framework. It enables developers to construct sophisticated orchestration patterns including sequential steps, parallel processing, conditional handoffs, and collaborative group chats. With built-in support for human-in-the-loop gates, robust error handling strategies, and dynamic magentic orchestration, it streamlines the creation of production-grade AI applications that require multiple specialized agents working in concert to solve complex problems.

주요 기능

Human-in-the-loop integration with approval and input gates
0 GitHub stars
State management via Redis checkpointing and shared memory
Five orchestration patterns: Sequential, Concurrent, Handoff, Group Chat, and Magentic
Advanced error handling with retry and fallback strategies
Workflow composition for nesting and combining multiple agent logic structures

사용 사례

Creating an automated customer support system that routes queries based on intent classification
Building a multi-stage research and reporting pipeline with specialized writing and review agents
Developing collaborative software engineering workflows where agents discuss, code, and test in a group chat

소개

주요 기능

Human-in-the-loop integration with approval and input gates
0 GitHub stars
State management via Redis checkpointing and shared memory
Five orchestration patterns: Sequential, Concurrent, Handoff, Group Chat, and Magentic
Advanced error handling with retry and fallback strategies
Workflow composition for nesting and combining multiple agent logic structures

사용 사례

Creating an automated customer support system that routes queries based on intent classification
Building a multi-stage research and reporting pipeline with specialized writing and review agents
Developing collaborative software engineering workflows where agents discuss, code, and test in a group chat