# NeoSmith Just Do It: Autonomous Task Execution System with Multi-Agent Collaboration

> A general-purpose autonomous agent system that adopts a multi-agent review pipeline architecture, supports 6 workflow modes, and provides a flexible framework for the automated execution of complex tasks.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-12T05:46:34.000Z
- 最近活动: 2026-04-12T05:52:24.403Z
- 热度: 157.9
- 关键词: AI Agent, 多智能体系统, 自主智能体, 任务自动化, 工作流引擎, 智能体协作, 开源AI
- 页面链接: https://www.zingnex.cn/en/forum/thread/neosmith-just-do-it
- Canonical: https://www.zingnex.cn/forum/thread/neosmith-just-do-it
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: NeoSmith Just Do It: Autonomous Task Execution System with Multi-Agent Collaboration

A general-purpose autonomous agent system that adopts a multi-agent review pipeline architecture, supports 6 workflow modes, and provides a flexible framework for the automated execution of complex tasks.

## Project Overview

NeoSmith Just Do It is an open-source general-purpose autonomous agent system. It achieves automated execution of complex tasks through an innovative multi-agent review pipeline architecture. The system supports 6 distinct workflow modes, capable of adapting to various application scenarios ranging from simple instructions to complex projects. In the current context of booming AI Agent development, this project offers a practical and scalable technical solution.

## Multi-Agent Collaboration Model

Unlike traditional single-agent systems, NeoSmith adopts a multi-agent collaboration design:

- **Task Decomposition Agent**: Responsible for breaking down complex tasks into executable subtasks
- **Execution Agent**: Focuses on the implementation of specific tasks
- **Review Agent**: Conducts quality checks on execution results and provides improvement suggestions
- **Coordination Agent**: Manages communication between agents and task allocation

This division of labor and collaboration model simulates the working style of human teams, enabling the system to handle more complex tasks.

## Review Pipeline Mechanism

The core innovation of the project lies in its review pipeline:

1. **First Draft Generation**: Execution agents complete the initial draft of the task
2. **Multi-Dimensional Review**: Multiple review agents evaluate results from different perspectives
3. **Feedback Integration**: Coordination agents summarize review comments
4. **Iterative Improvement**: Execution agents optimize based on feedback
5. **Quality Gating**: Final results are output only after meeting preset standards

This mechanism ensures the stability and reliability of output quality.

## Mode 1: Direct Execution Mode

The simplest mode, suitable for clear and simple tasks. Agents directly execute instructions and return results without complex collaboration processes.

## Mode 2: Single-Round Review Mode

A quality review is conducted once after execution, suitable for tasks requiring basic quality assurance, such as code review and document proofreading.

## Mode 3: Multi-Round Iteration Mode

The execution-review-improvement cycle can be repeated multiple times until quality standards are met. Suitable for tasks that require fine-tuning, such as creative writing and scheme design.

## Mode 4: Parallel Exploration Mode

Multiple execution agents attempt different solutions simultaneously, and review agents select the optimal result. Suitable for tasks that need to explore multiple possibilities.