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memory

Store persistent user data with semantic search and PARA organization.

17|Updated Mar 14, 2023
Search Tags:#memory#persistence#ai-agent#semantic-search#data-management#para#multi-user
One-click install
npx skills add https://github.com/hybrid-npm/hybrid --skill memory-hybrid-npm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory
Source: https://github.com/hybrid-npm/hybrid/tree/main/packages/agent/skills/memory
Command: npx skills add https://github.com/hybrid-npm/hybrid --skill memory-hybrid-npm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Memory persists across sessions with semantic search, enabling AI agents to recall context, preferences, and decisions while maintaining multi-user isolation through PARA organization.

Core Features & Use Cases

  • Persistent memory with semantic search across memory sources
  • PARA-based organization (projects, areas, resources, archives) for structured memory
  • Per-user isolation to protect privacy and context switching
  • Daily logs and fact storage enabling better recall and retroactive reasoning
  • Use Case: An AI agent remembers user preferences and past decisions to personalize recommendations over long-running conversations.

Quick Start

Initialize the memory system with PARA organization and semantic search across multi-user data.

Frequently Asked Questions about memory

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

FAQPage Schema
How do I add persistent memory with semantic search to my AI agent?▼

You add persistent memory with semantic search by integrating a modular storage system that enables AI agents to recall past context, preferences, and decisions across multiple sessions. This allows agents to retrieve remembered information using fast semantic queries.

How does PARA organization work for AI agent memory management?▼

PARA organization structures AI agent memory into projects, areas, resources, and archives. This framework categorizes persistent data logically, enabling structured memory storage and more efficient retrieval of remembered context.

Can I use per-user isolation to protect memory context in multi-user applications?▼

Per-user isolation protects memory context in multi-user applications by separating stored data, preferences, and daily logs for each individual user. This ensures privacy and accurate context switching when AI agents access remembered information.

What is the best way to store daily logs and facts for retroactive reasoning in AI?▼

The best way to store daily logs and facts for retroactive reasoning is using a persistent memory system with semantic search capabilities. This enables AI agents to recall past decisions and stored facts to personalize future recommendations.

Does persistent memory work across different AI agents and applications?▼

Persistent memory works across different AI agents and applications through a modular and extensible design. This architecture allows multiple agents to access the same semantic search and PARA-organized memory sources for consistent context retrieval.

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