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Virtual Company: Standardized Skill Library and Virtual Organizational Structure for AI Agents

Virtual Company is an open-source collection of Agent Skills that provides standardized domain-specific professional skills and workflows for AI programming assistants like Claude Code, Codex, and Kimi CLI, enabling the construction of virtual enterprise organizational structures.

Virtual CompanyAgent SkillsAI助手Claude CodeKimi CLIGemini CLI虚拟团队Prompt Engineering
Published 2026-03-29 21:46Recent activity 2026-03-29 21:56Estimated read 9 min
Virtual Company: Standardized Skill Library and Virtual Organizational Structure for AI Agents
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Section 01

Virtual Company Project Guide: Standardized Skill Library and Virtual Organizational Structure for AI Agents

Virtual Company is an open-source collection of Agent Skills designed to provide standardized domain-specific professional skills and workflows for AI programming assistants such as Claude Code, Codex, and Kimi CLI, and to build virtual enterprise organizational structures. The core concept of the project is to draw on real enterprise architectures to define clear roles, responsibilities, and workflows for AI agents, addressing the lack of depth and consistency in general large language models when handling domain-specific tasks, and enabling more professional and reliable AI-assisted work.

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Section 02

Project Background: Limitations of General AI Assistants and the Need for Virtual Teams

While large language models possess extensive knowledge, they lack depth and consistency when handling domain-specific professional tasks. The Virtual Company project proposes an innovative solution: transforming general AI assistants into virtual team members with professional division of labor through standardized Agent Skills, drawing on real enterprise organizational structures to define clear roles, responsibilities, and workflows for AI agents, thereby enhancing the professionalism and reliability of AI-assisted work.

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Section 03

Core Methods: Agent Skills Design and Technical Implementation

Agent Skills Design Philosophy

  1. Standardization and Reusability: Each Skill follows a unified format (role definition, capability list, workflow template, input/output specifications, boundary conditions) and supports reuse across AI assistants and projects.
  2. Domain Specialization: Covers multiple domains including technical development (architect, front-end/back-end engineer, etc.), product management (product manager, UX designer, etc.), and operational support (technical documentation engineer, project manager, etc.).
  3. Collaboration Interface Definition: Clarifies input dependencies, output deliverables, and collaboration protocols to support multi-Skill collaboration.

Technical Implementation

  • File Structure: Adopts structured organization (the skills directory contains Skill files for each role, the shared directory stores conventions and tools, and the examples directory showcases cases).
  • AI Assistant Integration: Seamlessly integrates with Claude Code (via CLAUDE.md/SKILL.md), Codex (custom instructions), Kimi CLI/Gemini CLI (system prompts or configuration files).
  • Dynamic Skill Loading: Automatically matches Skill combinations through task analysis, injects context, and collaborates to execute complex tasks.
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Section 04

Practical Application Scenarios: Virtual Company Implementation Cases

  1. Full-Stack Project Development: Coordinates Skills such as product manager (requirements analysis), architect (system design), front-end/back-end engineers (development), QA (testing), and DevOps (deployment) to complete projects.
  2. Code Review and Refactoring: The architect evaluates code structure, Skills for various tech stacks propose refactoring plans, collaboratively develop migration plans, and execute them in phases.
  3. Technical Documentation Maintenance: The technical documentation engineer Skill monitors code changes, automatically identifies documents that need updates, and generates update suggestions for manual review.
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Section 05

Relationship with Prompt Engineering: From One-Time Prompts to Engineering Collaboration

Virtual Company represents the evolutionary direction of Prompt Engineering:

  • From one-time prompts to structured roles: Define complete roles and working methods to replace temporary prompt words.
  • From general to professional: Deeply optimize for domain-specific tasks.
  • From individual skills to team collaboration: Expand into an organizational method for multi-agent collaboration.
  • From experience-driven to engineering: Solidify effective prompt patterns into reusable Skills.
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Section 06

Ecosystem and Community Contributions: Co-construction of Skills in Open-Source Mode

Virtual Company adopts an open-source model and encourages community contributions:

  • Skill Contribution Guidelines: Provide detailed writing specifications to ensure compatibility.
  • Quality Review Process: New Skills need to be reviewed before entering the main repository.
  • Use Case Sharing: Community members share cases where Skill combinations solve practical problems.
  • Best Practice Precipitation: Continuously refine and update best practices from usage experiences.
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Section 07

Future Outlook: Skill Market, AI-Native Collaboration, and Enterprise Customization

The project's future development directions include:

  1. Skill Market: Support developers to publish custom Skills, allow users to rate and comment, recommend based on data, and provide paid professional Skills.
  2. AI-Native Collaboration: Explore AI agents' ability to autonomously identify new Skill needs, combine existing Skills to create new capabilities, and self-optimize execution effects.
  3. Enterprise Customization: Provide private Skill repositories, custom Skills that comply with enterprise specifications, and Skills integrated with internal systems.
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Section 08

Project Conclusion: Evolutionary Direction of AI-Assisted Work

Virtual Company represents an important evolutionary direction of AI-assisted work—from tools to virtual team members. Through standardized Skill definitions and virtual organizational structures, AI assistants become more professional, consistent, and reliable in complex tasks. For teams and individuals looking to improve the efficiency of AI assistance, this project provides a framework and methodology worth exploring.