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team-builder

Generate complete AI agent team repositories with specialized agents, meta-agents, and auditors.

3|Updated Mar 6, 2026
Search Tags:#scaffolding#multi-agent system#meta-agent#auditor#agent team#team builder
One-click install
npx skills add https://github.com/jbrahy/meta-agent-teams --skill team-builder-jbrahy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: team-builder
Source: https://github.com/jbrahy/meta-agent-teams/tree/main/skill
Command: npx skills add https://github.com/jbrahy/meta-agent-teams --skill team-builder-jbrahy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the creation of complex, production-ready AI agent teams, complete with specialized agents, meta-agents, auditors, and robust documentation, from a simple team description.

Core Features & Use Cases

  • Full System Scaffolding: Generates a complete repository including README, constitution, agent configurations, and feedback mechanisms.
  • Iterative Development Framework: Establishes a structured, git-backed process for evolving AI agents based on human feedback.
  • Use Case: When a user wants to "build a marketing AI team that handles content creation and SEO analysis," this skill will generate all the necessary files and configurations for a multi-agent system designed for that purpose.

Quick Start

Use the team-builder skill to create a new AI agent team for customer support.

Frequently Asked Questions about team-builder

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

FAQPage Schema
How do I scaffold a multi-agent system from a text description?▼

Scaffolding a multi-agent system from a text description is done by generating a complete repository with specialized agents, configuration files, and documentation automatically.

What is a meta-agent and how does it evolve an AI agent team?▼

A meta-agent evolves an AI agent team by establishing a structured, git-backed process for iterative development and applying human feedback to update agent configurations.

How do I set up supervised agent training loops with an auditor?▼

Setting up supervised agent training loops requires generating an auditor agent and structured feedback mechanisms to perform ethical constraint checks and validate agent behavior.

Do I need to configure agent dependencies and ethical constraints manually?▼

Agent dependencies and ethical constraints are generated automatically based on your team description, though understanding them is required for successful team scaffolding and iterative evolution.

Can I build a production-ready AI agent team without writing boilerplate code?▼

Building a production-ready AI agent team without boilerplate is possible by automating the creation of README files, a constitution, agent configurations, and git-backed history.

What are the limitations of automating multi-agent system scaffolding?▼

Automating multi-agent system scaffolding is limited by the need for human oversight in structured feedback loops, as the generated agents require manual review to ensure ethical constraints are properly enforced.

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