cva-patterns-workflows

What problem does it solve?

Orchestrating multiple AI agents into reliable, performant, and observable production systems can be complex. This Skill provides robust patterns to tackle topology design (sequential, parallel, DAG), state management (stateless, stateful, hybrid), and reliability (retries, fallbacks, monitoring), ensuring your multi-agent systems deliver consistent results.

Core Features & Use Cases

• Topology Design: Implement sequential, parallel, or Directed Acyclic Graph (DAG) workflows for optimal agent connection and dependency management.
• State Management: Handle intermediate results and failures with stateless, stateful, or hybrid approaches, enabling pipeline recovery and data consistency.
• Reliability & Performance: Incorporate advanced error handling (retries, circuit breakers) and comprehensive monitoring to ensure robustness and optimize latency (e.g., 32% reduction with parallelization).
• Use Case: Design a healthcare pipeline that processes patient data through multiple AI agents, ensuring LGPD compliance, scientific validation, and SEO optimization, achieving 99.4% latency reduction and 92.4% cost reduction.

Quick Start

Design a multi-agent system for content generation. Start with a sequential flow, then identify independent steps for parallelization. Implement state management for expensive agents and add error handling.