# Agent General Staff: A Multi-Agent Engineering Suite for Codex, Cursor, and Claude Code

> A portable multi-agent engineering toolkit designed for the workflows of AI programming assistants like Codex, Cursor, and Claude Code.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-06-13T19:15:08.000Z
- 最近活动: 2026-06-13T19:25:25.367Z
- 热度: 153.8
- 关键词: multi-agent, codex, cursor, claude-code, development-kit
- 页面链接: https://www.zingnex.cn/en/forum/thread/agent-general-staff-codexcursor-claude-code
- Canonical: https://www.zingnex.cn/forum/thread/agent-general-staff-codexcursor-claude-code
- Markdown 来源: floors_fallback

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## Introduction / Main Floor: Agent General Staff: A Multi-Agent Engineering Suite for Codex, Cursor, and Claude Code

A portable multi-agent engineering toolkit designed for the workflows of AI programming assistants like Codex, Cursor, and Claude Code.

## Original Author and Source

- **Original Author/Maintainer**: FernandeZ-hjm
- **Source Platform**: GitHub
- **Original Title**: Agent-General-Staff
- **Original Link**: https://github.com/FernandeZ-hjm/Agent-General-Staff
- **Release Date**: 2026-06-13

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## Background and Motivation

AI programming assistants are profoundly changing the way software development works. From OpenAI's Codex to Cursor IDE and Anthropic's Claude Code, these tools have greatly improved development efficiency. However, to fully unleash the potential of these AI assistants, developers need to master specific interaction patterns, prompt engineering techniques, and best practices.

The Agent General Staff project was born to provide developers with a unified multi-agent engineering suite, enabling different AI programming assistants to collaborate and leverage their respective strengths.

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## Project Overview

Agent General Staff is a portable multi-agent engineering toolkit that supports mainstream AI programming assistants such as Codex, Cursor, and Claude Code. Through standardized interfaces and preconfigured workflows, this project allows multiple AI agents to collaborate on the same project to accomplish more complex development tasks.

## Core Features

- **Multi-agent Support**: Simultaneously supports multiple AI programming assistants like Codex, Cursor, and Claude Code
- **Portable Design**: Configurations and tools can be migrated between different projects and environments
- **Standardized Interfaces**: Unified agent interaction protocol to reduce switching costs
- **Preconfigured Workflows**: Provides preset workflow templates for common development scenarios
- **Collaboration Mechanism**: Supports task assignment and result transfer between agents

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## Agent Abstraction Layer

Agent General Staff designs a unified agent abstraction layer to shield the underlying differences between different AI programming assistants:

1. **Agent Interface**: Defines standardized input and output formats, including code snippets, context information, instructions, etc.
2. **Capability Registration**: Each agent registers its area of expertise (e.g., code generation, code review, documentation writing, etc.)
3. **Context Management**: Maintains shared context across agents to ensure collaboration coherence.

## Multi-agent Collaboration Modes

The project supports multiple agent collaboration modes:

#### Pipeline Mode

Multiple agents process tasks in sequence, each completing a specific link:

- Requirements Analysis Agent → Architecture Design Agent → Code Generation Agent → Test Generation Agent

#### Panel Mode

Multiple agents analyze the same problem in parallel and synthesize opinions from all parties:

- Security Expert + Performance Expert + Maintainability Expert jointly review code

#### Competition Mode

Multiple agents independently generate solutions and the best one is selected:

- Codex, Cursor, and Claude Code generate implementations respectively, and the best solution is chosen through evaluation.

## Context Synchronization Mechanism

The key to collaboration lies in maintaining context consistency:

- **Project Context**: Codebase structure, dependencies, coding standards, etc.
- **Task Context**: Current task goals, constraints, progress status
- **Historical Context**: Previous interaction records, decision-making basis, modification history