A powerful meta-generator that creates professional cognitive frameworks for AI agents based on any occupation name.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install universal-occupation-adapter
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 universal-occupation-adapter 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 Universal Occupation Adapter?
The Universal Occupation Adapter acts as a foundational meta-skill that allows AI agents to inhabit any professional role by mapping industry-specific knowledge to the SOUL five-law cognitive framework. It bridges the gap between generic LLM responses and deep professional expertise by defining exactly how an agent should handle known data, investigate unknowns, verify its work, and respect industry redlines. This ensures that every generated skill in the ecosystem maintains high reliability and professional integrity within the wider Openclaw Skills library.
By synthesizing information through a four-way collision engine—analyzing core knowledge, failure patterns, similar role templates, and future trends—the adapter creates a robust operational model for agents. Whether you are building an AI lawyer, an architect, or a specialized software engineer, this adapter provides the structural blueprints necessary for high-confidence autonomous operations.
Universal Occupation Adapter Use Cases
- Automating the creation of domain-specific AI personas for enterprise workflows.
- Standardizing professional redlines and safety constraints for autonomous agents.
- Rapidly prototyping new Openclaw Skills for niche industries without manual configuration.
- Enhancing multi-agent collaboration by giving each agent a distinct, professionally grounded cognitive model.
How Universal Occupation Adapter Works
- The user provides an occupation name (e.g., 'Architect') to the adapter via CLI or internal API call.
- The adapter searches its internal library for pre-validated occupational templates like Programmer or Researcher.
- If a template is missing, the four-way collision engine initiates a search for core knowledge, failure modes, and industry trends to build a new profile.
- Extracted data is mapped onto five professional dimensions: known sources, unknown types, verification methods, memory types, and redlines.
- The engine formats these dimensions into the SOUL framework and generates the required markdown and configuration files.
- An automated self-verification step runs to ensure the generated skill meets the 95% confidence threshold before final output.
Universal Occupation Adapter Setup
Install the adapter using the following command to begin building your own Openclaw Skills:
clawhub install universal-occupation-adapter
Alternatively, for a manual installation, copy the skill directory to your local configuration:
cp -r skills/universal-occupation-adapter ~/.openclaw/skills/
Universal Occupation Adapter Data Schema & Taxonomy
The adapter generates a structured directory for each new occupation containing the following core files:
| File | Description |
|---|---|
| SKILL.md | The primary cognitive definition and SOUL mapping. |
| VERIFICATION_PROTOCOL | Step-by-step instructions for validating the agent's professional output. |
| HEARTBEAT | Operational health checks for the specific professional role. |
| README | Usage documentation and metadata for the generated skill. |
It also defines specific memory taxonomies such as decision_log/, case_log/, or iteration_history/ depending on the professional requirements of the target occupation.
Universal Occupation Adapter Advanced Features
- Batch Generation: Automatically create and publish multiple Openclaw Skills simultaneously for entire professional departments.
- Four-Way Collision Engine: Synthesizes positive, negative, lateral, and holistic insights to ensure high-fidelity role modeling.
- Custom Dimension Injection: Manually override redlines or verification methods to suit specific project constraints or corporate ethics.
- Confidence Scoring: Integrated auto-verification system that ensures every generated skill is production-ready with a confidence rating of 95% or higher.
SKILL.md
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