openclaw-genpark-recursive-strategic-optimizer

Production-hardened OpenClaw GenPark Agent skill engineered strictly with Python standard library. Provides high-throughput deterministic execution, cryptographic security, and game-theoretic optimization via the Model Context Protocol (MCP).

Architecture & Data Flow

flowchart TD
    Input[Incoming Agent Telemetry / Task Input] --> Core["OpenClawGenParkRecursiveStrategicOptimizer"]
    Core --> Model[Mathematical Logic Engine]
    Model --> MCPResponse[Deterministic JSON Output / MCP Tool Result]

Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Standalone MCP Server Launch

Run the native STDIO MCP server:

python mcp_server.py

License

This project is licensed under the MIT License - see the LICENSE file for details.