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mem0-patterns

Organize AI memory into semantic, episodic, procedural, and preference types.

Updated Aug 27, 2026
Search Tags:#semantic-memory#memory-management#mem0#memory-patterns#episodic-memory#procedural-memory#ai-memory
One-click install
npx skills add https://github.com/alexaundre/mycc --skill mem0-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mem0-patterns
Source: https://github.com/alexaundre/mycc/tree/main/.claude/skills/mem0-patterns
Command: npx skills add https://github.com/alexaundre/mycc --skill mem0-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

mem0-patterns provide a structured approach to organizing AI memory into four distinct types to enhance recall, context retention, and decision-making efficiency.

Core Features & Use Cases

  • Four memory types: Semantic, Episodic, Procedural, Preferences, plus practical guidelines for integration with memory system files.
  • Clear patterns for write/read cycles, prioritization, and aging to maintain memory quality across sessions.
  • Use Case: Build a robust memory layer for an AI agent that remembers user preferences and past interactions to personalize responses.

Quick Start

Explain and implement the four mem0 memory types in your agent’s memory layer to begin structured memory management.

Frequently Asked Questions about mem0-patterns

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

FAQPage Schema
What are the four AI memory types for organizing persistent agent context?▼

Organize AI memory into semantic, episodic, procedural, and preferences types. This pattern-driven approach provides clear write/read cycles and aging policies to maintain memory quality across persistent agent sessions.

How do I structure AI agent memory to remember user preferences across sessions?▼

Build a memory layer using semantic, episodic, procedural, and preferences categories. Apply frontmatter-based configuration with defined write/read rules and aging policies to retain user preferences and past interactions across sessions.

Does mem0-patterns require specific configuration rules for memory management?▼

Yes, this approach requires frontmatter-based configuration to define write/read rules and aging policies. These configuration patterns govern memory prioritization and maintain quality for persistent agents across sessions.

What is the best way to manage AI memory aging and prioritization for long-running tasks?▼

Apply pattern-driven write/read cycles with clear prioritization and aging policies. This approach maintains memory quality and context retention for long-running tasks and persistent agents across multiple sessions.

When do I need structured memory patterns for my AI agent?▼

You need structured memory patterns when building persistent agents that must retain context across sessions, remember user preferences, or support long-running tasks. Organizing memory into four types improves recall and decision-making efficiency.

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