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Created by Shaunak Ghosh
Build an under-the-hood mental model of OpenClaw’s control plane, prompt/tool execution loop, and extension surfaces so you can add capabilities without collapsing trust boundaries. You’ll learn when to use SKILL.md vs plugins/hooks vs MCP-style bridges, and how to enforce sandboxing, tool policy, approvals, and observability in real deployments.
7 modules • Each builds on the previous one
Build a precise mental model of the Gateway as the long-lived control plane that owns channel sessions, and nodes as capability-advertising devices that execute privileged actions under pairing and policy boundaries.
Understand how OpenClaw assembles a compact system prompt (tools, safety, workspace, skills list) and why tool availability is determined by both prompt text and structured tool schemas sent to the model.
Learn the reliable “status → snapshot/describe → act → verify” patterns for browser, canvas, cron, and node-targeted tools, with emphasis on minimizing irreversible actions and improving determinism.
Master how SKILL.md metadata and instructions shape agent behavior, including how to write concise, tool-oriented procedures that avoid ambiguity and reduce prompt-injection surface area.
Understand plugins as in-process Gateway extensions that can register tools, RPC, commands, and bundled skills, and learn the decision framework for when a capability belongs in a skill, plugin, or external tool bridge.
Learn how sandboxing, tool allow/deny policy, and exec approvals combine into hard enforcement layers that bound blast radius even when the model is confused, tricked, or maliciously prompted.
Develop a production-grade debugging loop using diagnostics (doctor), logging levels, and targeted status probes to isolate failures in gateway runtime, channels, skills eligibility, nodes, and sandbox policy.
Begin your learning journey
In-video quizzes and scaffolded content to maximize retention.