Progressive Memory

What problem does it solve?

This Skill addresses the issue of limited context windows in AI agents by providing a token-efficient memory system that prioritizes relevant information and reduces wasted attention.

Core Features & Use Cases

• Token Efficiency: Significantly reduces token usage by scanning an index first and fetching details on demand, rather than loading entire memory dumps.
• Structured Memory: Organizes memory into daily files and a long-term memory file, each with a scannable index and detailed entries.
• Observation Types: Utilizes icons to categorize memory entries (e.g., rules, pitfalls, fixes, discoveries), enabling faster visual recognition.
• Use Case: An AI agent can quickly review its past decisions and learnings by scanning a concise index, only retrieving full details for entries directly relevant to its current task, thus saving processing time and cost.

Quick Start

Use the progressive memory skill to add a new rule to the long-term memory.