mnemonic-organization

Organize AI memories into filesystem directory layouts with garbage collection and health checks.

20|4|Updated Jan 24, 2026

Search Tags:#maintenance #memory management #namespace #garbage collection #filesystem organization #git versioning

Ready to run

npx skills add https://github.com/zircote/mnemonic --skill mnemonic-organization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mnemonic-organization
Source: https://github.com/zircote/mnemonic/tree/main/skills/mnemonic-organization
Command: npx skills add https://github.com/zircote/mnemonic --skill mnemonic-organization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a structured approach to organizing, maintaining, and cleaning up AI-generated memories, ensuring efficient storage and retrieval.

Core Features & Use Cases

Directory Structure: Defines a clear, hierarchical layout for storing memories based on organization, project, and memory type (semantic, episodic, procedural).
Namespace Management: Establishes conventions for different types of memories within the directory structure.
Maintenance Operations: Includes commands for garbage collection, conflict detection, and health checks.
Use Case: When managing a large codebase, this skill helps categorize and organize all related design decisions, incident reports, and procedural runbooks, making them easily discoverable.

Quick Start

Organize the current project's memories by running the memory organization skill.

Frequently Asked Questions about mnemonic-organization

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

FAQPage Schema

How do I organize AI memories on a filesystem for a large codebase?▼

Organizing AI memories on a filesystem involves defining a hierarchical directory layout separated by organization, project, and memory type. This structure categorizes semantic, episodic, and procedural memories to ensure efficient storage and retrieval across large codebases.

What is the best way to manage namespaces for different types of AI memories?▼

Managing namespaces for AI memories requires establishing conventions within a directory structure to separate semantic, episodic, and procedural types. This ensures distinct memory categories remain organized and easily discoverable across project and organization scopes.

How do I run garbage collection and detect conflicts in stored AI memories?▼

You can run garbage collection and detect conflicts in stored AI memories by executing maintenance operations and health check routines. These commands clean up unused data and identify overlapping or contradictory memory entries automatically.

Can I use git versioning alongside filesystem organization for AI memories?▼

Git versioning can be applied to filesystem organization for AI memories to track changes to stored entries. Managing memories within a directory structure allows version control systems to monitor semantic, episodic, and procedural memory updates over time.

Does this approach support both project and organization level memory scopes?▼

This approach supports both project and organization level memory scopes by defining a hierarchical directory layout. It categorizes semantic, episodic, and procedural memory types across these distinct scopes for comprehensive memory management.