POMASA

Pattern-Oriented Multi-Agent System Architecture

Purpose

POMASA is a pattern language and generation toolkit for building Declarative Multi-Agent Systems.

Its core value proposition: Enable AI to rapidly construct new MAS systems guided by patterns.

Overall Approach

Problem

When building multi-agent systems, every team uses their own approach to construct systems and their own terminology to describe architecture. The lack of a common pattern language makes it difficult to:

• Disseminate knowledge
• Reuse experience
• Discuss problems clearly

Solution

POMASA adopts a "pattern language + generator" approach:

1. Pattern Catalog (pattern-catalog/): Reusable architectural patterns extracted from real systems, each describing a specific problem and its solution
2. Generator (generator.md): A prompt that guides AI to build new systems based on patterns

Core Principles

• Patterns are knowledge carriers: Transform tacit architectural experience into explicit, shareable patterns
• Patterns have necessity levels: Required, Recommended, Optional—systems can be flexibly composed
• AI is the executor: AI reads pattern documents, understands design principles, and generates pattern-conforming systems
• Continuous evolution: New patterns are added as practice accumulates

Directory Structure

pomasa/
├── README.md                # This file
├── generator.md             # MAS generator prompt
├── user_input_template.md   # User input template
├── pattern-catalog/         # Pattern catalog
│   ├── README.md            # Pattern overview and usage guide
│   ├── COR-01-prompt-defined-agent.md
│   ├── COR-02-intelligent-runtime.md
│   ├── STR-01-...
│   ├── BHV-01-...
│   ├── QUA-01-...
│   └── ...
└── references/              # Reference materials
    ├── declarative-multi-agent-architecture-part1-en.md
    └── declarative-multi-agent-architecture-part2-en.md

How to Use the Generator

Scenario 1: Building a New Research-Oriented MAS

Step 1: Copy user_input_template.md to your working directory and fill in your research project information

Step 2: Issue a command to Claude Code:

Please read pomasa/generator.md, then generate a multi-agent research system based on [your user_input file path].

The Generator will guide the AI to:

1. Read your completed user_input
2. Read the relevant patterns in pattern-catalog
3. Select the appropriate pattern combination based on your needs
4. Generate the complete system files

Scenario 2: Understanding or Improving an Existing System

Please read pomasa/pattern-catalog/README.md, then analyze which patterns [a system directory] uses and what improvements could be made.

Scenario 3: Learning MAS Architecture

Read the pattern documents under pattern-catalog/ directly to learn about declarative MAS design principles and best practices.

Pattern Overview

See pattern-catalog/README.md

Evolution Plan

POMASA is a continuously evolving project:

• Extract new patterns as more systems are built and operated
• Refine existing pattern descriptions based on practical feedback
• Explore pattern variants and adaptations across different domains