A persistent memory management skill that gives AI agents structured long-term recall, enabling them to remember preferences, decisions, project context, and learned patterns across sessions.

Key Features

Structured Storage — Organise memories by type: facts, preferences, decisions, learnings, and context
Semantic Retrieval — Find relevant memories by meaning, not just keywords, using contextual matching
Auto-Capture — Automatically detect and store important information from conversations
Memory Decay — Configurable relevance scoring that deprioritises stale information over time
Export/Import — Portable memory format for backup, sharing, and migration between agents

Use Cases

Project continuity — Remember codebase conventions, team decisions, and architectural choices across sessions
Personal preferences — Retain communication style, formatting preferences, and workflow habits
Knowledge building — Accumulate domain expertise that compounds over time
Client context — Maintain client-specific preferences, history, and relationship notes

How It Works

The skill stores memories as structured markdown files with metadata (type, timestamp, relevance score). On each session start, it loads contextually relevant memories based on the current task, project, and conversation topic.

Getting Started

Install from ClawHub. The skill creates its storage directory automatically and begins capturing memories from the first session.

View on ClawHub

Memory Manager

AI Skill Market Insights

Quick Start

Manual Installation

TEAR & SHARE

Be Part of the 0+ Developer Community

Key Features

Use Cases

How It Works

Getting Started

Channels

Learn

Compare

Company