memory

Load MEMORY.md and log events to HISTORY.md for persistent AI context.

29|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/whanyu1212/Krill.jl --skill memory-whanyu1212
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory
Source: https://github.com/whanyu1212/Krill.jl/tree/main/context/skills/memory
Command: npx skills add https://github.com/whanyu1212/Krill.jl --skill memory-whanyu1212

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Two-layer memory system provides persistent long-term context and an append-only history, ensuring consistent AI behavior across sessions.

Core Features & Use Cases

  • Two-layer memory: Long-term memory stored in MEMORY.md and a separate HISTORY.md log for events.
  • Auto-consolidation: Periodically distills durable facts to MEMORY.md and logs events with timestamps.
  • Guided recall: Searches history when needed; loads long-term facts at session start for immediate context.
  • Use Case: An agent working on a multi-turn project can remember preferences and key relationships across days.

Quick Start

Load MEMORY.md into memory at session start and log events to HISTORY.md.

Frequently Asked Questions about memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I maintain persistent AI context across multiple sessions?▼

Long-term AI memory works by loading durable facts from MEMORY.md into the session at start, while appending ongoing events to HISTORY.md, allowing periodic auto-consolidation of context over extended conversations.

How does auto-consolidation manage long-term memory for AI agents?▼

Auto-consolidation manages long-term memory by periodically distilling durable facts from the history log into MEMORY.md, ensuring the AI agent retains key relationships and preferences without manual summarization.

Can I use a two-layer memory system for multi-turn AI projects?▼

Yes, a two-layer memory system is designed for multi-turn AI projects, allowing an agent to remember preferences and key relationships across days by separating long-term facts from an append-only event history.

What is the best way to log AI agent history with timestamps?▼

Logging AI agent history with timestamps is achieved by appending events to a HISTORY.md file, separating the append-only event log from the distilled facts in MEMORY.md to preserve context.

Does guided recall search the history log when AI context is missing?▼

Yes, guided recall searches the history log when needed, retrieving specific past events from HISTORY.md while loading long-term facts into MEMORY.md for immediate AI context at session start.