A powerful domain-specific language for orchestrating multi-model AI workflows with specialized engines for strategy, science, and culinary arts.
Install & Download
1. ClawHub CLI
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npx clawhub@latest install skills-2
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 skills-2 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 AetherLang AI Workflow Orchestration?
AetherLang is a sophisticated AI orchestration platform that utilizes a unique Domain-Specific Language (DSL) to manage complex, multi-step AI pipelines. By leveraging Openclaw Skills, developers can access nine specialized V3 engines ranging from Nobel-level business analysis to Michelin-grade recipe generation. The platform stands out by providing mandatory structured outputs and a robust security architecture, ensuring that every AI interaction is validated and sanitized server-side.
The system is designed for high-stakes environments where precision is paramount. Whether you are performing molecular gastronomy calculations or running Monte Carlo simulations for a business strategy, AetherLang provides the framework to connect research, analysis, and execution into a single, cohesive flow.
AetherLang AI Workflow Orchestration Use Cases
- Orchestrating multi-agent intelligence for complex decision-making scenarios using Openclaw Skills.
- Generating professional restaurant consulting reports including HACCP compliance, food costing, and kitchen timelines.
- Conducting advanced business strategy analysis using game theory, Nash equilibrium, and unit economics.
- Building research pipelines that grade evidence levels and identify knowledge gaps in scientific domains.
- Performing automated data analysis with anomaly detection, statistical testing, and predictive modeling.
How AetherLang AI Workflow Orchestration Works
- The developer defines a workflow using the AetherLang DSL syntax, specifying the required nodes, engine types, and parameters.
- The Openclaw Skills agent sends the DSL code and the natural language user query to the secure AetherLang execution API.
- Server-side middleware validates the input against a whitelist of fields and enforces length restrictions to prevent injection attacks.
- The orchestrator processes the flow through the selected engines (e.g., APEX Strategy, GAIA Brain, or Chef Omega) using optimized system prompts.
- The system returns a structured JSON response containing the synthesized final output, individual node results, and execution duration.
AetherLang AI Workflow Orchestration Setup
To get started with this skill, no API keys are required for the free tier, which supports up to 100 requests per hour. Ensure your environment can make outbound HTTPS requests to the API endpoint.
# You can test the connection to the AetherLang API using curl
curl -X POST https://api.neurodoc.app/aetherlang/execute \
-H "Content-Type: application/json" \
-d '{"code": "flow Test { input text query; node L: analyst; output text result from L; }", "query": "Analyze this data"}'
AetherLang AI Workflow Orchestration Data Schema & Taxonomy
The skill utilizes a strict schema for both inputs and outputs to ensure data integrity and security within Openclaw Skills.
| Field | Type | Description |
|---|---|---|
code |
String | The AetherLang DSL flow definition (Max 10,000 characters). |
query |
String | The natural language user input or data to process (Max 5,000 characters). |
status |
String | Indicates 'success' or 'error'. |
result |
Object | Contains the final_output string and execution metadata. |
duration_seconds |
Float | The total time taken to orchestrate and execute the flow. |
AetherLang AI Workflow Orchestration Advanced Features
- Multi-Engine Pipelining: Connect multiple specialized nodes (e.g., Research -> Market -> Strategy) to create comprehensive intelligence reports.
- GAIA Brain Voting: A 12-neuron voting system with a disagreement protocol and 'Gandalf Veto' for high-confidence AI outputs.
- Bayesian Forecasting: Utilize the Oracle engine for signal vs. noise scoring and Kelly criterion bet sizing.
- Internationalization: Native support for high-fidelity Greek language outputs with proper markdown formatting.
- Built-in Security Guards: Implement GUARD nodes with STRICT, MODERATE, or PERMISSIVE settings to filter content dynamically.
SKILL.md
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