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yangkun19921001
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memory

Maintain persistent context with MEMORY.md for long-term facts and HISTORY.md for event logs.

37|9|Updated Mar 4, 2026
Search Tags:#memory#persistence#context-management#agent-memory#long-term-memory#memory-system#event-logging
One-click install
npx skills add https://github.com/yangkun19921001/PP-Claw --skill memory-yangkun19921001
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory
Source: https://github.com/yangkun19921001/PP-Claw/tree/main/skills/memory
Command: npx skills add https://github.com/yangkun19921001/PP-Claw --skill memory-yangkun19921001

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Two-layer memory system helps the AI retain long-term facts and track events without cluttering the current working context.

Core Features & Use Cases

  • Long-term facts are stored in MEMORY.md and loaded into context across sessions, enabling persistent personalization.
  • Event logging via HISTORY.md records interactions without inflating active memory, supporting traceability and analysis.
  • Use cases include maintaining project context, user preferences, and important relationships for more coherent agent behavior.

Quick Start

Remember user preferences and project context by ensuring MEMORY.md and HISTORY.md are in the memory directory, then interact with the agent.

Frequently Asked Questions about memory

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

FAQPage Schema
How do I persist context for an AI agent across multiple sessions?▼

To persist agent context across sessions, maintain a MEMORY.md file for long-term facts like user preferences and project details. This file is automatically loaded into the active context, ensuring continuity without manual input.

What is the best way to log agent events without cluttering the working context?▼

Logging agent events without context clutter is achieved by using an append-only HISTORY.md file. This records interactions and traceable history separately from active memory, preventing context inflation while supporting analysis.

How does two-tier agent memory work for personalization?▼

Two-tier agent memory works by separating long-term facts from event logs. MEMORY.md stores persistent user preferences and project context for immediate recall, while HISTORY.md tracks chronological interactions for traceability.

Do I need any dependencies to set up long-term memory for my AI agent?▼

No dependencies are required to set up long-term memory for your AI agent. You only need to ensure MEMORY.md and HISTORY.md are present in the memory directory before interacting with the agent.

Can I track project context and user relationships using a two-file memory system?▼

Yes, you can track project context and user relationships using a two-file memory system. MEMORY.md retains important relationship facts and project details, while HISTORY.md logs event sequences for coherent agent behavior.

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