memory-manager

What problem does it solve?

This Skill addresses the challenges of managing ElizaOS agent memory, context windows, and conversation history. It provides strategies for memory pruning, optimization, and consolidation, ensuring agents maintain relevant context without exceeding token limits or becoming overwhelmed by irrelevant information, leading to more efficient and accurate responses.

Core Features & Use Cases

• Memory Pruning Strategies: Implements time-based and size-based pruning to automatically remove old or less important memories.
• Context Window Management: Helps optimize the agent's working memory to keep the most relevant information within the LLM's context.
• Use Case: If your ElizaOS agent is struggling with long conversations or exceeding token limits, use this Skill to "optimize agent memory." It will help you implement pruning strategies based on time and importance, ensuring the agent's context remains focused and efficient.

Quick Start

Optimize my ElizaOS agent's memory by implementing time-based pruning for low-importance memories older than 30 days.