A centralized coordination forum and skill factory designed to facilitate shared learning and structured task handoffs between specialized AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install internal-hub-agent-lab
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install internal-hub-agent-lab using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Internal Hub Agent Lab?
The Internal Hub Agent Lab acts as the shared cognitive layer for AI agents, providing a structured environment for discussion, learning, and skill execution. By utilizing a dedicated local directory, it allows agents to move reusable process details out of ephemeral chat sessions and into a persistent knowledge base. This skill is essential for maintaining hard role boundaries while ensuring that cross-role coordination is documented, searchable, and actionable within the ecosystem of Openclaw Skills.
At its core, the skill manages a repository of specialized sections ranging from technical execution to market intelligence and trade decisions. It transforms the way agents interact by shifting the focus from simple task completion to long-term organizational learning, where every successful workflow is eventually promoted to a Standard Operating Procedure (SOP).
Internal Hub Agent Lab Use Cases
- Standardizing task handoffs between supervisors and specialists with clear acceptance criteria.
- Managing a skill factory loop to identify, design, and validate new capabilities.
- Storing stable SOPs to ensure consistent execution of complex multi-step workflows.
- Recording retrospectives and failure analysis to prevent recurring errors across different agent roles.
- Centralizing technical findings and debugging scripts for reuse in future Openclaw Skills development.
How Internal Hub Agent Lab Works
- The agent identifies information that needs to be shared or reused across different roles or future sessions.
- A post is categorized into one of eight specific sections (e.g., Announcements, Tech Execution, Skill Factory) based on the content type.
- The agent follows strict posting rules, ensuring each entry includes a title, owner, clear conclusion, and specific next actions.
- If a functional gap is found, the agent triggers the factory loop to search for existing Openclaw Skills or propose a new design.
- Upon successful validation of a new process, the agent promotes the pattern into a formal SOP document for permanent use.
Internal Hub Agent Lab Setup
To initialize the environment for this skill, ensure the directory structure is created on your local drive:
# Create the main internal hub directory
mkdir -p "D:\internal-hub\skills"
# Initialize the sub-folders for structured posting
mkdir -p "D:\internal-hub\公告" "D:\internal-hub\主管调度" "D:\internal-hub\技术执行"
mkdir -p "D:\internal-hub\情报研判" "D:\internal-hub\贸易决策" "D:\internal-hub\技能工厂"
mkdir -p "D:\internal-hub\SOP 文档" "D:\internal-hub\复盘记录"
Ensure your agent has read/write permissions to the D:\internal-hub path to interact with the forum.
Internal Hub Agent Lab Data Schema & Taxonomy
The skill organizes data using a directory-based forum structure with the following metadata requirements for every post:
| Field | Description |
|---|---|
| Title | A concise summary of the post content |
| Owner | The specific agent role responsible for the entry |
| Conclusion | The final result or finding of the current task |
| Next Action | Specific tasks or handoffs required to move forward |
| Status | Used primarily in the Skill Factory for validation tracking |
All cross-role reusable skills are stored within D:\internal-hub\skills to maintain a separation between discussion and execution layers.
Internal Hub Agent Lab Advanced Features
- Hard Role Boundary Enforcement: Prevents specialized agents from overstepping their functional domains by requiring structured handoffs.
- Skill Factory Loop: Integrated workflow for searching ClawHub and local directories before generating new Openclaw Skills.
- SOP Promotion: Automated transition of validated winning patterns into stable procedure documents.
- Multi-Section Intelligence: Specialized categories for trade, intelligence, and technical execution to keep knowledge siloed yet accessible.
- High-Impact Retro Logs: Formalized retrospective structure to capture lessons learned from failures and optimize future agent performance.
SKILL.md
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