OpenClaw Memory and Skills System

Modern AI assistants become far more useful when they can remember information and perform repeatable tasks. That’s exactly what the OpenClaw Memory and Skills system is designed to do. Instead of treating every conversation as temporary, OpenClaw allows agents to store knowledge in files and execute reusable “skills” for automation. This design keeps the system efficient while still giving your AI long-term awareness.

Below are three core parts of the OpenClaw Memory and Skills system.

1. OpenClaw Markdown Memory System

The default memory system in OpenClaw uses simple Markdown files, making it easy to inspect, edit, and back up your AI’s knowledge.

The structure has two main layers: daily logs and long-term memory. Daily logs are stored in files like memory/YYYY-MM-DD.md. These files act as an append-only timeline of events, notes, and context. When a session begins, OpenClaw automatically reads the logs from today and yesterday to maintain continuity.

For more permanent information, the system uses a file called MEMORY.md. This file stores durable facts such as preferences, decisions, or recurring instructions. To protect privacy, MEMORY.md is only loaded in your private session and never in public chats or shared channels.

Instead of loading all files directly into the AI’s context window, OpenClaw retrieves information using built-in tools like memory_search and memory_get. The system maintains a local vector index that combines semantic search with traditional keyword matching. This means the AI can find information even if the wording changes.

Additional ranking methods—such as temporal decay and MMR (Maximal Marginal Relevance)—help prioritize recent and diverse information. OpenClaw also performs automatic “memory flush” events before conversations are summarized, ensuring important details are safely written to disk.

2. Build Your First OpenClaw Skill

Skills allow OpenClaw to perform repeatable tasks using instructions stored in Markdown files. These skills help automate common actions while keeping the system flexible and easy to customize.

To create a skill, start by making a new folder inside the workspace skills directory, for example:

~/.openclaw/workspace/skills/hello-world

Inside this folder, create a file named SKILL.md. Each skill begins with a short YAML frontmatter section that defines the skill’s name and description. Below that, you write clear instructions explaining how the AI should perform the task.

For instance, a simple greeting skill might instruct the agent to use an echo command whenever a user asks for a greeting.

In case you are interested, the articles OpenClaw Installation Guide and OpenClaw AI Model Integration go perfectly with what you're reading right now.

Skills can also use built-in tools such as bash, browser, or read, allowing the agent to interact with files, websites, or the operating system. Advanced users may define additional tools using JSON schema if the skill requires structured inputs.

After saving the file, OpenClaw must discover it. You can either ask the agent to refresh skills or restart the gateway service. Once loaded, the skill becomes available to the AI.

To test it quickly, run:

openclaw agent –message “use my new skill”

For best results, keep instructions concise and avoid allowing unsafe command execution from untrusted inputs.

3. MEMORY.md vs Daily Logs Structure

Understanding the difference between daily logs and MEMORY.md helps you design a reliable long-term memory system for OpenClaw.

Daily logs are stored in files such as memory/YYYY-MM-DD.md. These files act as a running narrative of events, notes, and temporary observations. OpenClaw reads today’s and yesterday’s logs at the start of a session to maintain short-term continuity.

However, daily logs are not inserted into the AI context on every message. Instead, the agent retrieves information from them only when necessary using memory tools. Older entries also receive a temporal decay ranking, meaning recent notes are prioritized during searches.

In contrast, MEMORY.md represents the system’s curated long-term knowledge. This file stores durable facts such as user preferences, rules, or major decisions. Because the information is considered essential, it is injected directly into the AI’s context window during each interaction.

MEMORY.md is also treated as an evergreen source, meaning it is not affected by temporal decay during searches. To protect personal information, OpenClaw restricts this file to private sessions and prevents it from loading in public channels.

In practice, daily logs function as a working scratchpad, while MEMORY.md holds the distilled insights that the AI should remember permanently.

The OpenClaw Memory and Skills system helps AI assistants become more useful by combining persistent memory with custom automation skills. With simple Markdown files and reusable instructions, OpenClaw can remember important information and perform tasks more efficiently.