- name
- memory-structure
- version
- 1.0.2
- description
- Enable AI to learn from mistakes and never repeat them. Error tracking, layered memory, regular self-reflection, continuous improvement.
Skill: memory-structure
Name
memory-structure
Function
Copy existing memory structure to new environments, enabling other Agents to use the same memory system.
Use Cases
- Quickly set up self-improvement framework for new Agents
- Unify memory organization across multiple Agents
- Establish standardized self-reflection process
Skill Contents
This skill includes:
| File | Description |
|---|---|
memory.md | Main memory file: preferences, patterns, rules (HOT tier) |
corrections.md | Error correction log: "what I got wrong" and correct answers |
index.md | Memory index: tracks all memory file updates |
heartbeat-state.md | Heartbeat state: records self-reflection check timestamps and results |
heartbeat-rules.md | Heartbeat rules: defines triggers and execution logic for self-reflection |
setup.md | Setup guide: installation and configuration instructions |
Usage
1. Install Skill
Using ClawHub:
clawhub install memory-structure2. Initialize Memory Structure
Create memory directory in target workspace:
mkdir -p ~/self-improving/{domains,projects,archive}Then manually create the following files (copy template contents below):
3. Regular Self-Reflection
After completing important tasks, Agent should update heartbeat-state.md with reflection results.
Core Concepts
- HOT Tier: Memory files are hot-tier, high-frequency access
- Corrections Log: Errors are the source of improvement, must be recorded
- Heartbeat: Regular self-reflection to check if memory structure needs updates
Dependencies
- No external dependencies
- Requires file system write permission
- Heartbeat interval configured in OpenClaw config (default: 30 minutes)