An ultra-lightweight, zero-dependency skill that automatically archives every AI conversation into daily Markdown files to ensure persistent agent memory.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install memory-auto-sync
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install memory-auto-sync using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Minimalist Memory Auto-Sync Skill is a specialized utility designed for the OpenClaw ecosystem to eliminate the friction of manual conversation logging. By leveraging native Node.js APIs, it provides a high-performance, zero-dependency solution for developers who require reliable, real-time synchronization of dialogue history into structured Markdown files. This skill ensures that every interaction with your AI assistant is captured instantly, preventing data loss and significantly increasing the value of your Openclaw Skills by creating a permanent, human-readable record of agent activity.
To install the skill, follow these simple steps to integrate it into your environment:
# 1. Navigate to your OpenClaw skills directory
cd ~/.openclaw/skills/
# 2. Place the memory-auto-sync directory into the skills folder
# Ensure the path is ~/.openclaw/skills/memory-auto-sync/
# 3. Restart your OpenClaw gateway
# The skill will automatically load and begin syncing dialogues.
The skill organizes data into daily Markdown files to maintain a clean and navigable hierarchy. Each record follows a standardized metadata taxonomy:
| Element | Description | Example/Format |
|---|---|---|
| Header | Timestamped record identifier | #### Dialogue Record: YYYY-MM-DD HH:mm |
| User Entry | User's message prefixed by name | - User: [Message Content] |
| Assistant Entry | Agent's response prefixed by name | - Assistant: [Response Content] |
| Divider | Visual separation for readability | --- |
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