A professional framework for AI agents to maintain long-term context and daily logs using structured Markdown storage.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install atomic-memory-manager
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install atomic-memory-manager 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 Memory Management?
The Memory Management skill provides a robust mechanism for AI coding agents to overcome context window limitations by persisting data across sessions. By utilizing this component of Openclaw Skills, agents can store durable facts, project decisions, and user preferences in a structured Markdown format. This ensures that every interaction builds upon a foundation of established knowledge rather than starting from scratch.
This skill divides memory into two distinct layers: a curated long-term storage file for standing facts and a daily log system for chronological context. This dual-layered approach within Openclaw Skills allows for both high-level recall and granular tracking of day-to-day progress, making it an essential tool for complex, long-running development projects.
Memory Management Use Cases
- Retrieving technical decisions or architectural choices made in previous coding sessions.
- Recalling user preferences, such as specific API keys, page IDs, or coding style requirements.
- Tracking the status of todos and milestones through daily activity logs.
- Maintaining a record of people, dates, and recurring workflows relevant to the workspace.
- Identifying and citing specific historical context to avoid repeating past mistakes.
How Memory Management Works
- The agent identifies a trigger, such as a user asking about prior work or providing a fact that needs to be remembered.
- For retrieval, the agent invokes memory_search with a specific query to locate relevant snippets within the workspace.
- The agent uses memory_get to extract exact lines of text for high-precision answering.
- For storage, the agent determines the durability of the information: long-term facts go to MEMORY.md, while daily context goes to a date-stamped file in the memory directory.
- The agent writes the smallest useful note possible to maintain a clean and searchable knowledge base.
Memory Management Setup
To enable persistent context in your Openclaw Skills environment, ensure your workspace is initialized with the required directory structure.
# Initialize the memory directory and long-term storage file
mkdir -p memory
touch MEMORY.md
Once the files are present, the agent will automatically utilize the memory_search and memory_get tools to interface with these documents.
Memory Management Data Schema & Taxonomy
The skill organizes workspace intelligence using a simple yet effective file-based taxonomy:
| Data Component | File Path | Scope |
|---|---|---|
| Long-term Memory | MEMORY.md |
Durable facts, standing preferences, and core workflows. |
| Daily Memory | memory/YYYY-MM-DD.md |
Session context, daily progress, and ephemeral notes. |
| Retrieval Tools | memory_search / memory_get |
Functional interfaces for querying and reading stored data. |
Memory Management Advanced Features
- Targeted retrieval logic that prioritizes specific line-item fetching over bulky file reads.
- Automated context tiering between daily logs and curated long-term knowledge.
- Minimalist storage philosophy to prevent context bloat and ensure fast search performance.
- Seamless cross-session continuity for multi-turn tasks within the Openclaw Skills ecosystem.
SKILL.md
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