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agent-management

Manage AI agents across lifecycle stages within the superomni framework.

2|Updated Mar 25, 2026
Search Tags:#workflow#scaffolding#cli#installation#ai-agents#team-collaboration#agent-management
One-click install
npx skills add https://github.com/Wilder1222/superomni --skill agent-management-wilder1222
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-management
Source: https://github.com/Wilder1222/superomni/tree/main/skills/agent-management
Command: npx skills add https://github.com/Wilder1222/superomni --skill agent-management-wilder1222

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Agent management across AI projects is complex; this skill provides a structured approach to locate, install, create, and manage AI agents within the superomni framework, ensuring consistent capabilities across teams.

Core Features & Use Cases

  • Gate-driven lifecycle: check built-ins, search the network, install from URL or scaffold from scratch.
  • Lifecycle management: create agents, assign skills, update configurations, and remove agents.
  • Reusability and collaboration: publish and share agent definitions with standardized outputs and role-based access.

Quick Start

List built-ins with bin/agent-manager list and install or scaffold an agent to begin management.

Frequently Asked Questions about agent-management

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

FAQPage Schema
How do I install and manage AI agents within a structured workflow?▼

AI agent management involves discovering built-in agents, searching the network, or scaffolding from scratch. This skill applies a phase-based protocol across THINK, PLAN, REVIEW, BUILD, VERIFY, and RELEASE stages to ensure reliable installation and lifecycle control.

What is the best way to scaffold a custom AI agent from scratch?▼

Scaffolding a custom AI agent requires creating a base definition and assigning specific skills. Using a CLI command like bin/agent-manager, you can scaffold agents from scratch and enforce standardized output formats and safety checks.

Can I use this agent-management skill for team collaboration and sharing agent definitions?▼

Yes, the agent-management skill supports team collaboration by allowing you to publish and share agent definitions. It ensures consistent capabilities across teams through standardized outputs and role-based access during the agent lifecycle.

Does this skill support lifecycle management across explicit workflow gates?▼

Lifecycle management is supported through explicit gates within a phase-based protocol. The skill governs agent creation, configuration updates, and removal across explicit THINK, PLAN, REVIEW, BUILD, VERIFY, and RELEASE workflow phases.

Why do I need a phase-based protocol for AI agent installation?▼

A phase-based protocol ensures reliable AI agent installation by enforcing explicit gates and safety checks. This structured approach prevents misconfiguration and standardizes outputs when locating, installing, or creating agents within the framework.

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