add-memory

Name: add-memory
Availability: InStock
Author: AllBeingsFuture

Store user preferences and interaction patterns into long-term memory with type tags.

9|2|Updated Mar 18, 2026

Search Tags:#patterns #memory #long-term-memory #user-preferences #error-lessons

Ready to run

npx skills add https://github.com/AllBeingsFuture/AllBeingsFuture --skill add-memory-allbeingsfuture

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: add-memory
Source: https://github.com/AllBeingsFuture/AllBeingsFuture/tree/main/electron/embedded-assets/skills/system/add-memory
Command: npx skills add https://github.com/AllBeingsFuture/AllBeingsFuture --skill add-memory-allbeingsfuture

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Record and organize critical information into long-term memory to improve learning, personalization, and error analysis.

Core Features & Use Cases

Persist user preferences and successful interaction patterns for future sessions.
Tag and categorize memories by type (fact, preference, skill, error, rule) with optional importance levels.
Retrieve and apply remembered data to adapt AI behavior and responses across tasks.

Quick Start

Tell me to save a memory by providing content, type, and optional importance.

Frequently Asked Questions about add-memory

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

FAQPage Schema

How do I save user preferences and patterns into long-term memory for AI personalization?▼

Store user preferences and successful interaction patterns into long-term memory by providing the content, type, and optional importance. This persists data across sessions to adapt AI behavior and improve personalization.

What is the best way to record error lessons so AI learns from past mistakes?▼

Record error lessons by tagging memories with the 'error' type and assigning an importance level. This allows the system to retrieve past mistakes and apply lessons to prevent similar errors across future tasks.

Can I categorize long-term memories by type and importance level?▼

Yes, you can tag and categorize memories by specific types including fact, preference, skill, error, and rule. You can also assign optional importance levels to prioritize which memories are retrieved for personalization.

How do I store user information across sessions to adapt AI behavior?▼

Store critical user information using localized, secure memory storage to persist data across sessions. The system retrieves and applies this remembered data to adapt AI responses and behavior for future interactions.

Does storing long-term memories require any specific dependencies or environment setup?▼

No dependencies are required to store long-term memories. The skill operates independently to satisfy explicit memory typing and localized, secure storage requirements without needing external frameworks or modules.

What are the limitations of using long-term memory storage for personalization?▼

The system relies on explicit user inputs to save memories and does not automatically infer preferences. Memory storage is localized and secure, meaning data retrieval is constrained to the specific environment where it was saved.