memory-rule

Store and retrieve stable user facts for AI assistant memory.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/rdb420/voiceBOX --skill memory-rule
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: memory-rule
Source: https://github.com/rdb420/voiceBOX/tree/main/.cursor/skills/memory-rule
Command: npx skills add https://github.com/rdb420/voiceBOX --skill memory-rule

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill addresses the challenge of maintaining consistent and relevant long-term memory for AI assistants, ensuring continuity and improving the quality of interactions across multiple sessions.

Core Features & Use Cases

  • Persistent Memory: Stores and retrieves stable facts about user identity, preferences, technical stack, projects, and workflows.
  • Contextual Relevance: Uses stored memory to inform current conversations and tasks, leading to more personalized and efficient assistance.
  • Privacy-Conscious Storage: Captures only necessary, non-sensitive information and allows for user-controlled redaction.
  • Use Case: An AI assistant remembers your preferred coding language, current project goals, and frequently used tools, allowing it to provide more tailored code suggestions and task assistance without needing constant re-explanation.

Quick Start

Begin the next interaction by stating "Remembering..." and then retrieve relevant prior notes from memory.

Frequently Asked Questions about memory-rule

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

FAQPage Schema
How do I maintain long-term memory for an AI assistant across multiple sessions?

Maintaining long-term memory for an AI assistant involves capturing stable, reusable facts about user preferences and technical stack. This skill normalizes and deduplicates entries using a CRUD strategy to ensure context continuity and consistency across sessions.

What is the best way to personalize AI context without repeating my engineering preferences?

Personalizing AI context requires storing stable facts about your engineering stack, tools, and goals. By applying a CRUD strategy to deduplicate and normalize entries, the assistant retrieves relevant prior notes to inform current tasks without needing constant re-explanation.

Can I control privacy and redact sensitive information from AI long-term memory?

Yes, privacy-conscious long-term memory storage allows for user-controlled redaction. The system captures only necessary, non-sensitive information about your workflows and identity, ensuring you can manage what the AI assistant remembers.

How do I start a conversation using stored AI memory rules?

To start using stored AI memory rules, begin your next interaction by stating "Remembering..." and then retrieve relevant prior notes from memory. This quick start approach immediately applies your saved context to the current task.

Why does my AI assistant forget my project goals and technical stack between chats?

AI assistants forget project goals and technical stack details between chats because they lack persistent long-term memory. Implementing a memory rule that captures, normalizes, and deduplicates stable facts ensures contextual relevance and continuity across sessions.

Does persistent AI memory support CRUD operations for managing stored preferences?

Yes, persistent AI memory supports CRUD operations to manage stored preferences. This strategy focuses on precision and consistency, allowing you to create, read, update, and delete stable facts about your identity, tools, and workflows.