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oma-orchestrator

Coordinate multiple AI agents to execute complex multi-step workflows.

5|3|Updated Mar 11, 2026
Search Tags:#automation#parallel execution#multi-agent#orchestration#workflow management#task scheduling
One-click install
npx skills add https://github.com/ddarkr/antigravity-token-monitor --skill oma-orchestrator-ddarkr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oma-orchestrator
Source: https://github.com/ddarkr/antigravity-token-monitor/tree/main/.agents/skills/oma-orchestrator
Command: npx skills add https://github.com/ddarkr/antigravity-token-monitor --skill oma-orchestrator-ddarkr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides an automated system to coordinate multiple specialized agents, enabling efficient parallel execution and comprehensive workflow management.

Core Features & Use Cases

  • Task Decomposition and Scheduling: Breaks down complex projects into manageable sub-tasks assigned to specific agents.
  • Parallel Agent Execution: Spawns multiple agents concurrently respecting parallelism limits to accelerate delivery.
  • Progress Monitoring and Verification: Tracks agent progress, runs automated verification, and facilitates QA reviews to ensure quality.
  • Use Case: Automate a full-stack project delivery pipeline by orchestrating backend, frontend, and QA agents executing in parallel, with iterative feedback loops for quality assurance.

Quick Start

Define your project tasks in a YAML file and execute using the parallel-run script to orchestrate multi-agent workflows seamlessly.

Frequently Asked Questions about oma-orchestrator

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

FAQPage Schema
How do I orchestrate multiple AI agents for complex multi-step workflow automation?▼

Multi-agent orchestration coordinates multiple specialized AI agents to execute complex workflows, utilizing task decomposition, parallel execution, and iterative verification to automate end-to-end processes across various domains.

What is the best way to manage parallel execution and task scheduling for multi-agent workflows?▼

Managing parallel execution involves breaking down complex projects into sub-tasks assigned to specific agents, spawning multiple agents concurrently while respecting parallelism limits to accelerate delivery through structured task scheduling.

How do I set up and run multi-agent workflows using a YAML configuration?▼

To run multi-agent workflows, define your project tasks in a YAML file and execute using the parallel-run script to seamlessly orchestrate and schedule agents.

Can I track progress and run automated verification for parallel agent execution?▼

Yes, progress monitoring tracks agent execution status, runs automated verification checks, and facilitates QA reviews to ensure quality through iterative feedback loops during task scheduling.

Does multi-agent orchestration require external dependencies to manage complex workflows?▼

No, this multi-agent orchestration system operates with zero external dependencies, relying solely on its internal references and assets to coordinate task decomposition and parallel execution.

When should I use multi-agent orchestration instead of sequential task processing?▼

Use multi-agent orchestration when automating complex, multi-step projects like full-stack delivery pipelines that require backend, frontend, and QA agents executing in parallel with iterative verification for quality assurance.

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