Extropy Operator is an execution-first skill designed to run complex simulation pipelines, diagnose failures, and deliver evidence-backed analysis using strict quality gates.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install extropy
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 extropy 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 Extropy Operator?
Extropy Operator serves as a robust framework for managing simulation life cycles within Openclaw Skills. It prioritizes direct execution over description, ensuring that every stage of a pipeline—from initial population specification to final result extraction—is handled with precision and validated against strict technical benchmarks.
By leveraging this skill, developers can orchestrate large-scale simulations involving thousands of agents, complex social networks, and dynamic scenarios. The operator emphasizes transparency and reliability, mandating that every conclusion drawn from a simulation is supported by explicit evidence such as SQL metrics, file paths, and validated artifacts.
Extropy Operator Use Cases
- Orchestrating large-scale population simulations for socio-economic forecasting.
- Running high-fidelity persona and agent interaction experiments with strict quality control.
- Diagnosing and escalating pipeline failures in complex AI modeling workflows.
- Generating evidence-based reports and timelines from raw simulation data using Openclaw Skills.
How Extropy Operator Works
- Define the population and experiment parameters using the spec command.
- Generate scenarios and personas to establish the simulation environment.
- Sample the population and build the network topology while enforcing strict quality gates.
- Execute high-fidelity simulations with configurable rate limits and concurrency settings.
- Extract results and query states to produce summaries, timelines, and raw data files.
Extropy Operator Setup
To utilize this skill, ensure the extropy binary is installed on your system. Configure your environment with the necessary API keys and settings:
# Install the extropy binary and verify PATH
# Set required environment variables
export OPENAI_API_KEY="your_key"
export ANTHROPIC_API_KEY="your_key"
export MODELS_STRONG="gpt-4"
# Initialize the configuration
mkdir -p ~/.config/extropy
# Ensure ~/.config/extropy/config.json is populated
Extropy Operator Data Schema & Taxonomy
Extropy Operator organizes simulation data into a structured directory hierarchy with the following primary artifacts:
| File Type | Description | Validation Method |
|---|---|---|
| population.vN.yaml | Defines the base demographic and agent specs | extropy validate |
| scenario.vN.yaml | Contains the simulation narrative and parameters | extropy validate |
| states.jsonl | Raw execution logs and agent state transitions | extropy query |
| network.yaml | Defines the topology and edges between agents | Topology metrics |
Extropy Operator Advanced Features
- Multi-provider support including OpenAI, Anthropic, Azure, and DeepSeek via Openclaw Skills.
- Automated quality gates that prevent expensive downstream stages if upstream artifacts fail validation.
- Checkpoint and recovery system for long-running simulations.
- Deep inspection capabilities via SQL queries and network status checks.
- High-concurrency execution with fine-grained RPM and TPM overrides.
SKILL.md
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