Agent Os Three Layer

What This Skill Does

Agent Os Three Layer is a robust, modular framework designed to structure the operational logic of AI agents. By decoupling the architecture into three distinct layers—Identity, Operations, and Knowledge—it allows developers to create more predictable, consistent, and maintainable AI entities. The 'Identity' layer serves as the foundation, anchoring the agent's core values, persona, and user-specific context. The 'Operations' layer acts as the executive engine, housing the protocols, team management, and standard operating procedures (SOPs) that guide the agent's daily functions. Finally, the 'Knowledge' layer provides the long-term memory and context retention, ensuring that the agent learns and adapts based on past interactions. This separation prevents prompt drift and allows for modular upgrades to specific parts of an agent's brain without risking the entire system's stability.

Installation

To integrate this framework into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/huamu668/agent-os-three-layer Once the installation completes, navigate to the directory located at ~/agent-os and initialize the system using the provided scripts: ./scripts/startup.sh to launch the runtime and ./scripts/verify.sh to ensure the directory structure and permissions are correctly configured.

Use Cases

This skill is ideal for building autonomous corporate assistants, specialized research agents, or persona-based chatbots that require long-term context retention. It is particularly effective for teams building complex agents that need to evolve over time without losing their core identity. By organizing memory and logic into specific subdirectories, developers can easily plug in new tools or data sources without reconfiguring the agent's persona.

Example Prompts

1. "Initialize the Agent OS system and read the contents of the SOUL.md file to confirm my current persona settings."
2. "Review the current state of MEMORY.md and summarize the last three key decisions made by the agent."
3. "Update the ROLE-CEO.md configuration to prioritize task automation over manual file sorting for the next operational cycle."

Tips & Limitations

To maximize the efficacy of this skill, ensure that the IDENTITY.md file is kept concise and prioritized for the model's system prompt. Because the system relies on file-based storage for memory, perform regular backups of the knowledge/ directory to prevent data loss during system updates. Note that this architecture is a structural framework; while it provides the organization, the agent's intelligence level will still be limited by the underlying LLM's capabilities. Always test new configurations in a sandbox environment before applying them to a live, multi-session workflow.