# Miniature Guacamole: A Product Development Team System with 19 Collaborative Agents

> A multi-agent product development system built on Claude Code, which implements a complete TDD/BDD development workflow through 19 specialized agents and 16 skills.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-06T17:44:57.000Z
- 最近活动: 2026-04-06T17:52:27.644Z
- 热度: 141.9
- 关键词: 多智能体系统, Claude Code, TDD, BDD, 软件开发, 智能体协作, 自动化开发, 产品团队
- 页面链接: https://www.zingnex.cn/en/forum/thread/miniature-guacamole-19
- Canonical: https://www.zingnex.cn/forum/thread/miniature-guacamole-19
- Markdown 来源: floors_fallback

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## Introduction: Core Overview of the Miniature Guacamole Multi-Agent Product Development System

Miniature Guacamole is a multi-agent product development system built on Claude Code. It simulates the collaborative process of a real product team through 19 specialized agents and 16 skill modules, enabling a fully automated TDD/BDD development workflow from requirements to delivery. This system represents a new paradigm of multi-agent collaboration in AI software engineering.

## Background: Multi-Agent Collaboration Becomes a New Trend in AI Software Engineering

With the improvement of large language model capabilities, a single AI assistant can handle complex programming tasks, but it is difficult to balance multi-dimensional work such as requirement analysis and architecture design. This limitation has given rise to multi-agent collaboration systems—assigning professional tasks to specialized agents to simulate human team collaboration models. Miniature Guacamole is a typical representative of this trend.

## Methodology: Role Division Design of 19 Agents

The system draws on agile team role division with clear agent responsibilities:
- **Product Management**: Product Manager (requirements collection/prioritization), Business Analyst (requirements refinement)
- **Technical Architecture**: System Architect (overall solution), Database Architect (data model), DevOps Engineer (CI/CD/containerization)
- **Development Implementation**: Frontend/Backend/Full-stack Development Agents
- **Quality Assurance**: Test Engineer (test strategy/test cases), QA Analyst (exploratory testing), Security Auditor (code security)
- **Support & Optimization**: Technical Documentation (automatic document generation), Code Review (peer review), Performance Optimization (bottleneck identification)

## Methodology: 16 Core Skill Modules Supporting Collaboration

The system defines 16 reusable skills:
- **Requirements Engineering**: User story writing, acceptance criteria definition, requirement prioritization
- **Design & Architecture**: Domain-driven design, API design, data modeling
- **Development & Implementation**: TDD, BDD, code refactoring
- **Quality Assurance**: Unit test writing, integration test design, performance test execution
- **Engineering Practices**: Version control workflow, continuous integration configuration, containerized deployment, monitoring and observability

## Practice: Automated Execution Process of TDD/BDD Workflow

The core value of the system is to automate the TDD/BDD process, with the following steps:
1. **Requirements Clarification**: Product Manager + Business Analyst convert requirements into user stories and Gherkin-format acceptance criteria
2. **Test-First**: Test Engineer writes failing test cases (Red phase)
3. **Feature Implementation**: Development agents write minimal code to pass the tests (Green phase)
4. **Code Refactoring**: Code Review + Performance Optimization agents guide refactoring while keeping tests passing
5. **Integration Verification**: Multi-agent collaboration for integration testing, with parallel security audit scanning
6. **Documentation Delivery**: Technical Documentation agent automatically generates synchronized documents

## Conclusion & Recommendations: Applicable Scenarios and Limitations

**Applicable Scenarios**:
- Standardized product development (following mature norms to reduce omissions)
- Rapid prototype validation (accelerating market validation)
- Legacy system maintenance (rebuilding knowledge to assist transformation)
- 24/7 continuous delivery (not limited by time)

**Limitations**:
- Highly innovative projects require the intuition of human architects
- Agent coordination overhead and error propagation risks
- Dependence on the Claude Code platform

These factors need to be weighed in practical applications.