Is this skill compatible with Vercel AI SDK versions?

This skill is optimized for Vercel AI SDK 5 and above, focusing on modern agent frameworks and Model Context Protocol (MCP) tool integration.

How does this skill prevent infinite loops in AI agents?

It implements loop control strategies including maximum iteration limits, time-based timeouts, and token cost safeguards to prevent runaway operations and minimize costs.

Can I build multi-agent systems with this skill?

Yes, it provides templates for coordinator agents that route tasks to specialized specialist agents, facilitating parallel execution and domain-specific expertise.

What is a ReAct agent pattern?

ReAct (Reasoning + Acting) is a pattern where the AI thinks step-by-step and performs actions via tools iteratively to solve complex tasks, which is fully supported by this skill's templates.

Agent Workflow Patterns

Name: Agent Workflow Patterns
Author: vanman2024

byvanman2024

Data Science & ML

Implements sophisticated autonomous agent architectures and workflow patterns using the Vercel AI SDK.

About

This skill provides a comprehensive toolkit for building resilient, production-ready AI agents with the Vercel AI SDK. It includes implementation patterns for ReAct agents, multi-agent systems, and complex workflow orchestrators, along with critical loop control strategies such as iteration limits, cost safeguards, and quality gates. Whether you are building a simple RAG agent or a complex multi-domain autonomous system, this skill offers the structural templates and best practices needed to manage agent state, coordinate tool execution, and ensure reliable outputs.

Key Features

Multi-agent system coordination and task routing logic
Standardized agent state management and error recovery
Loop control safeguards for cost and iteration management
ReAct (Reasoning + Acting) iterative pattern templates
Parallel and sequential tool orchestration strategies
0 GitHub stars

Use Cases

Building autonomous research or coding assistants
Creating multi-step reasoning workflows for complex problem-solving
Implementing multi-agent systems with specialized domain expertise

About

Key Features

Multi-agent system coordination and task routing logic
Standardized agent state management and error recovery
Loop control safeguards for cost and iteration management
ReAct (Reasoning + Acting) iterative pattern templates
Parallel and sequential tool orchestration strategies
0 GitHub stars

Use Cases

Building autonomous research or coding assistants
Creating multi-step reasoning workflows for complex problem-solving
Implementing multi-agent systems with specialized domain expertise