niche

Orchestrate multi-agent workflows using a wave-based OODA loop with persistent scratchpads.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/bert-berkers/UrbanRepML --skill niche
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: niche
Source: https://github.com/bert-berkers/UrbanRepML/tree/main/.claude/skills/niche
Command: npx skills add https://github.com/bert-berkers/UrbanRepML --skill niche

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill acts as a coordinator for a multi-agent system, managing complex workflows by delegating tasks to specialist AI agents and ensuring knowledge is preserved through structured documentation.

Core Features & Use Cases

  • Agent Orchestration: Manages the OODA (Observe, Orient, Decide, Act) cycle for specialist agents.
  • Knowledge Management: Ensures that agent reasoning and outcomes are captured in persistent scratchpads for institutional memory.
  • Use Case: When tasked with a complex software development task, this Skill would break it down into waves, delegate specific coding, testing, or documentation tasks to appropriate agents, and manage their execution and reporting.

Quick Start

Use the niche skill to coordinate agent-based development for the task 'Implement GTFS modality end-to-end'.

Frequently Asked Questions about niche

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

FAQPage Schema
How does multi-agent orchestration handle complex software development workflows?

Multi-agent orchestration manages complex software development workflows by breaking tasks into waves and delegating specific coding, testing, or documentation assignments to specialist AI agents through a structured OODA loop.

What is a wave-based OODA loop for AI agent coordination?

A wave-based OODA loop for AI agent coordination is a cycle where a central system observes, orients, decides, and acts on task delegation, processing multi-stage development in sequential phases to manage specialist agents.

How do I maintain institutional memory in a multi-agent system?

To maintain institutional memory in a multi-agent system, orchestration tools capture agent reasoning and outcomes in persistent scratchpads, ensuring structured documentation of knowledge across task execution.

Can I use agent orchestration for multi-stage research projects?

Yes, you can use agent orchestration for multi-stage research projects. It coordinates AI efforts by delegating specialized research tasks to appropriate agents and managing their execution and knowledge capture.

What is the best way to delegate tasks to specialist AI agents?

The best way to delegate tasks to specialist AI agents is using a workflow management system that applies a wave-based OODA loop, ensuring robust agent communication and structured task execution.

When should I not use a multi-agent system for task delegation?

You should not use a multi-agent system for task delegation when a project lacks complex, multi-stage requirements. It requires robust agent communication and is designed specifically for coordinated AI efforts on advanced workflows.