The Signal & The Act: Architecture Overview
To master OpenClaw, you must understand how it transforms raw text into multi-step browser actions. It is not just a wrapper around GPT-4; it is a signal processing engine.
OpenClaw uses a Reactive Planning loop. It doesn't plan the whole mission upfront; it observes the environment (DOM/Logs) and decides the next 100ms.
Every tool in OpenClaw is an MCP Server (Model Context Protocol). This allows the agent to treat your File System like its own memory.
The Decision Pipeline
- Ingest: The agent scrapes the current UI state using a specialized DOM-to-Text compressor.
- Synthesize: The compressed signal is combined with the user's "Mission Objective" and previous history.
- Reason: The LLM (Brain) determines if a tool call is needed or if the mission is complete.
- Execute: The chosen Skill (Skill System) performs the action (Click, Type, Fetch) and returns the result.
Data Sovereignty
Unlike cloud-based agents, OpenClaw architecture keeps the Signal Phase local. Only the reasoning prompt is sent to the LLM, while the raw DOM remains encrypted in your local memory.
Advanced: The Tree-of-Thought Guard
OpenClaw v2 introduces a "Validator" layer. If the agent makes a potentially destructive action (like rm -rf), the architecture forces a secondary LLM check to verify intent against safety protocols.
"Architecture is what happens when you stop guessing and start measuring."
Next: Understanding Agent Theory