OpenClaw on Derek's Guides

Getting Started with OpenClaw

Sun, 01 Mar 2026 00:00:00 +0000

OpenClaw is an open-source agent orchestration platform that helps you build AI agents with persistent memory, skill systems, and multi-agent coordination.

Core Concepts

Memory Architecture

OpenClaw uses a three-tier memory model:

Episodic - Daily logs (memory/episodic/YYYY-MM-DD.md)
Semantic - Knowledge base (memory/semantic/topic.md)
Procedural - Workflows (memory/procedural/process.md)

Skills System

Skills are modular capabilities stored in ~/.openclaw/skills/. Each skill has:

SKILL.md - Documentation
Scripts or tools
Configuration

Sub-agents

OpenClaw can spawn specialized sub-agents for tasks:

Lossless Claw: Never Lose Context Again

Sun, 15 Mar 2026 00:00:00 +0000

Every LLM has a context window — a maximum number of tokens it can process. When a conversation exceeds this limit, most agents simply truncate older messages. Lossless Claw replaces truncation with a DAG (Directed Acyclic Graph) summarization system that preserves every message while keeping active context within model token limits.

What You’ll Learn

Why context loss happens and why it matters
How LCM (Lossless Context Management) preserves every message
Step-by-step installation and configuration
Best practices for long-lived agent sessions

The Problem: Context Loss

When context exceeds the token limit:

OpenClaw + Hermes: Multi-Agent Infrastructure

Tue, 14 Apr 2026 00:00:00 +0000

Connect OpenClaw (Clawdia) to Hermes Agent for delegating infrastructure tasks via HTTP API. This lets you manage Docker, Kubernetes, and GitOps operations through conversational commands.

What You’ll Learn

When to use multi-agent architecture for infrastructure tasks
How to connect OpenClaw to Hermes via HTTP API
Configuring the Hermes integration skill
Querying Docker, deploying stacks, and managing GitOps
Security considerations for agent-to-agent communication

Why Multi-Agent?

Running everything in one agent creates a security problem. Infrastructure tasks need terminal and Docker access—capabilities you don’t want tied to your general-purpose assistant.

Building Modular Content Moderation with Guardrails

Wed, 18 Mar 2026 00:00:00 +0000

When building AI agents, content moderation is often an afterthought — if it’s considered at all. This guide walks through building a modular guardrails skill for OpenClaw that can be optionally imported into any skill that needs content filtering.

Why Modular Over Middleware?

Traditional approaches often bake moderation into the core agent loop. This has drawbacks:

All-or-nothing — You either moderate everything or nothing
Hard to test — Global changes affect everything
Inflexible — Different skills may need different rules

A modular approach lets you: