rem-sleep

What problem does it solve?

This Skill addresses the challenge of accumulating session logs that are expensive to re-read, leading to important insights being buried and memory loss after context compaction or restarts.

Core Features & Use Cases

• Memory Consolidation: Processes raw session logs to extract significant patterns and consolidate them into durable memory files.
• Memory Defragmentation: Reviews and cleans up long-term memory files by removing stale entries, duplicates, and compressing verbose information.
• Use Case: An AI agent can use this skill periodically to ensure that crucial decisions, learned facts, and important preferences are preserved in its long-term memory, preventing the loss of valuable knowledge.

Quick Start

Run the REM sleep skill to consolidate recent session logs into durable memory.