agents

Name: agents
Availability: InStock
Author: ormastes

Orchestrate iterative agent loops and team coordination across MCP tools.

1|Updated Mar 8, 2026

Search Tags:#workflow #MCP #agent #multi-agent #orchestration #coordination #loop

Ready to run

npx skills add https://github.com/ormastes/simple --skill agents-ormastes

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agents
Source: https://github.com/ormastes/simple/tree/main/doc/00_llm_process/skill_command/skills/claude/lib/agents
Command: npx skills add https://github.com/ormastes/simple --skill agents-ormastes

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates iterative agent loops and team coordination across MCP tools to streamline multi-agent tasks.

Core Features & Use Cases

Iterative agent loops with task handoff between agents
Flexible coordination strategies (sequential, parallel, round-robin)
Lightweight integration hooks for monitoring and persistence

Quick Start

Start an agent loop with agent_loop_start(prompt, max_iterations, completion_condition, agent) and drive steps with agent_loop_step until completion.

Frequently Asked Questions about agents

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I coordinate multi-agent workflows with sequential or parallel task delegation?▼

Multi-agent workflows are coordinated by creating an agent team and driving iterative agent loops with MCP tooling to enable sequential, parallel, or round-robin task delegation and cross-agent decision making.

What is an agent loop and how does it handle iterative task handoff?▼

An agent loop is an iterative process started with agent_loop_start that drives steps via agent_loop_step, enabling task handoff between agents until a specified completion condition is met.

Can I use MCP tools to orchestrate dynamic task delegation across multiple agents?▼

Yes, MCP tools orchestrate dynamic task delegation across multiple agents by implementing team coordination strategies and agent loops with state persistence for cross-agent decision making.

Does multi-agent orchestration support state persistence and monitoring hooks?▼

Multi-agent orchestration supports state persistence and provides lightweight integration hooks for monitoring agent loop steps and team coordination during sequential or parallel execution.

What is the best way to start an agent loop for team collaboration?▼

The best way to start an agent loop is by calling agent_loop_start with a prompt, max_iterations, completion_condition, and agent, then driving the process with agent_loop_step until completion.

When should I use multi-agent coordination strategies for MCP tooling?▼

Use multi-agent coordination strategies for MCP tooling in scenarios requiring iterative agent loops, dynamic task delegation, sequential or parallel collaboration, and cross-agent decision making.