Agent Memory Patterns for Openclaw

A framework for implementing persistent, hierarchical memory in AI agents using structured Markdown and automated Bash workflows.

byron-mckeeby
v1.0.0
Feb 3, 2026
1
2.6k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install agent-memory-patterns

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install agent-memory-patterns using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Agent Memory Patterns?

Agent Memory Patterns provide a robust architecture for managing an AI agent's internal knowledge and historical context. By organizing data into a hierarchy—ranging from transient daily logs to highly curated long-term knowledge bases—this skill ensures that agents remain context-aware and efficient over extended durations. It moves beyond simple context windows by utilizing a file-based system that is easily searchable and maintainable.

As a core methodology for Openclaw Skills, this pattern utilizes standard Markdown files and Bash scripts to automate the entire lifecycle of an agent's memory. It includes mechanisms for importance-based logging, weekly curation into a central memory file, and a dedicated staging area for external information, ensuring the agent's knowledge remains organized and accurate.

Agent Memory Patterns Use Cases

  • Maintaining deep project context across multiple work sessions.
  • Staging and validating information gathered from web searches before permanent storage.
  • Generating automated weekly reports of an agent's activities and learned patterns.
  • Implementing a heartbeat system to monitor memory health and prevent context bloat.

How Agent Memory Patterns Works

  1. The system initializes a new daily memory file every morning to track immediate events and sessions.
  2. Logs are recorded throughout the day with importance levels (high, medium, low) using structured markers.
  3. A weekly curation script extracts high-importance events and learned patterns into the central MEMORY.md file.
  4. External content is queued in a staging file for validation and consistency checks before integration.
  5. Automated maintenance scripts handle monthly archiving and heartbeat checks to optimize storage and retrieval.

Agent Memory Patterns Setup

Installation

  1. Initialize the directory structure within your workspace:
mkdir -p ~/.openclaw/workspace/memory/archive
mkdir -p ~/.openclaw/workspace/skills/memory-tools
  1. Deploy the memory management scripts to the memory-tools directory and ensure they are executable:
chmod +x ~/.openclaw/workspace/skills/memory-tools/*.sh
  1. Configure your crontab to automate the maintenance lifecycle:
# Example: Initialize daily memory at 1 AM
0 1 * * * ~/.openclaw/workspace/skills/memory-tools/daily-memory-init.sh

Agent Memory Patterns Data Schema & Taxonomy

The architecture organizes memory into the following schema for Openclaw Skills:

File / Path Purpose Format
MEMORY.md Long-term memory and manually curated knowledge Markdown
memory/YYYY-MM-DD.md Daily activity logs and session-specific data Markdown
memory/pending-memories.md Staging area for unverified external content Markdown
memory/heartbeat-state.json System health metadata and monitoring alerts JSON
memory/archive/ Monthly archives of historical daily logs Directory

Agent Memory Patterns Advanced Features

  • Smart Memory Search: Grep-based retrieval with support for contextual line display and keyword frequency analysis.
  • Importance-Based Curation: Automatic extraction of high-priority events based on visual importance markers (emojis).
  • External Content Staging: A validation queue that ensures new data is verified for reliability and consistency.
  • Memory Heartbeat: Real-time monitoring of file sizes and queue depths to trigger maintenance alerts.
  • Monthly Archiving: Automated rotation of daily logs into monthly summaries to keep the active workspace lean.

SKILL.md


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