agent-builder

Name: agent-builder
Availability: InStock
Author: mindmorass

Build specialized sub-agents for modular AI workflows with a shared RAG server.

2|Updated Jan 2, 2026

Search Tags:#routing #build #agents #registry #prompts #orchestrator

Ready to run

npx skills add https://github.com/mindmorass/reflex --skill agent-builder-mindmorass

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-builder
Source: https://github.com/mindmorass/reflex/tree/main/plugins/reflex/skills/agent-builder
Command: npx skills add https://github.com/mindmorass/reflex --skill agent-builder-mindmorass

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Builds specialized sub-agents for a modular AI workflow to enable scalable, domain-specific task execution across a coordinated team of AI assistants.

Core Features & Use Cases

Modular Agent Architecture: An Orchestrator routes tasks to Researcher, Coder, Writer, and Analyst with a shared RAG-backed knowledge base.
Configurable Prompts & Tools: Sub-agents are defined in a central registry and can be customized with per-agent prompts.
End-to-End Task Routing: Automates delegation and synthesis of results across agents for multi-domain projects.
Use Case: Orchestrate a complex data-to-code-to-report workflow where information gathering, code generation, documentation, and analysis are coordinated automatically.

Quick Start

Use the agent-builder to configure and deploy sub-agents and start the orchestrator for a multi-domain task.

Frequently Asked Questions about agent-builder

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

FAQPage Schema

How do I build a multi-agent workflow that routes tasks to specialized AI assistants?▼

Agent-builder orchestrates specialized sub-agents—Researcher, Coder, Writer, Analyst—that handle domain-specific tasks in a coordinated workflow. It uses an Agent Registry to define each agent's role, custom prompts, and shared RAG-backed knowledge base, routing tasks automatically across the team.

What's the best way to set up modular AI agents with custom prompts and tool configurations?▼

Agent-builder centralizes agent definitions in a registry.yaml file where you configure each sub-agent with custom prompts and tools. The Orchestrator instantiates agents from this registry and delegates tasks based on their domain expertise, enabling easy reconfiguration without code changes.

Can I automate task delegation across research, coding, writing, and analysis phases?▼

Yes. Agent-builder's end-to-end routing automates delegation and result synthesis across four specialized agent types. It orchestrates the full workflow—information gathering, code generation, documentation, and analysis—with a shared knowledge base backing each phase.

Do I need a shared knowledge base to coordinate multiple AI agents?▼

Agent-builder uses a shared RAG server as its knowledge backbone, enabling all sub-agents to access consistent context. This unified knowledge base improves coherence across agents and reduces redundant retrieval, though you configure it once during setup.

What preparation is required before deploying the orchestrator?▼

You need an Agent Registry (registry.yaml) defining each sub-agent, per-agent prompt files tailored to their roles, and a loader script to instantiate agents and start the orchestrator. The RAG server and agent configurations must be in place before routing tasks.

How does agent-builder differ from running single standalone AI assistants?▼

Agent-builder coordinates multiple specialized agents with role-specific prompts and shared knowledge, enabling complex multi-domain workflows. Standalone assistants lack this orchestration layer, requiring manual task distribution and context passing between separate systems.