Progressive Memory

What problem does it solve?

This Skill addresses the issue of AI context windows being overwhelmed by irrelevant information, leading to wasted attention and decreased performance by implementing a token-efficient memory system.

Core Features & Use Cases

• Token Efficiency: Significantly reduces token usage by only loading necessary information.
• Progressive Disclosure: Presents an index first, allowing the AI to fetch detailed information on demand.
• Structured Memory: Organizes memory into daily files and a long-term memory index with clear categorization and token estimations.
• Use Case: An AI agent can quickly scan a concise index of past interactions and decisions, then retrieve only the specific details relevant to its current task, such as a past "gotcha" or a critical "rule."

Quick Start

Scan the memory index to find relevant information for the current task.