What problem does it solve?
This Skill addresses the complexity of building and managing multi-agent AI systems by providing tools to define, compose, and orchestrate intricate workflows, ensuring efficient and reliable execution of agentic tasks.
Core Features & Use Cases
- Sequential & Parallel Execution: Define workflows using intuitive
| (sequential) and & (parallel) operators.
- Layered Composition (L1/L2): Structure workflows by composing components within layers (Data, Intelligence, Output) or composing entire layers for system-level orchestration.
- Conditional Logic & Routing: Implement decision-making within workflows using
Conditional for binary branches and Router for multi-way routing.
- State Management: Utilize
Workflow objects with checkpointing for long-running or complex pipelines.
- Framework Integration: Seamlessly integrate external agents from frameworks like LangChain, AutoGen, and CrewAI via adapters.
- Use Case: Build a content generation pipeline where an initial data layer fetches market research, an intelligence layer uses multiple agents to analyze the data and draft an article, and an output layer generates both a PDF report and a social media post.
Quick Start
Define a sequential workflow that first processes a PDF document and then sends the output to a research agent.
