openclaw-memory

What problem does it solve?

This Skill addresses the critical challenge of managing and preserving information within AI agent systems, preventing data loss and ensuring consistent knowledge recall.

Core Features & Use Cases

• Memory Architecture: Understands and implements a four-layer memory model (Bootstrap, Daily Logs, Session Transcript, Retrieval Index).
• Data Persistence: Guides users on setting up persistent storage for agent knowledge, including MEMORY.md and daily logs.
• Failure Mode Mitigation: Provides strategies to prevent data loss due to agents not storing information, compaction errors, or pruning.
• Shared Memory: Details patterns for enabling cross-agent knowledge sharing through team-memory/ directories and SHARED_KNOWLEDGE.json.
• Use Case: An AI agent needs to remember customer preferences and past interactions across multiple sessions. This Skill helps configure the agent's memory layers to store this information reliably, even when dealing with large amounts of data or system updates.

Quick Start

Use the openclaw-memory skill to set up memory for a new agent, including bootstrap files and daily logs.