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mnemonic

Store and retrieve semantic, episodic, and procedural memories in filesystem namespaces.

20|4|Updated Jan 24, 2026
Search Tags:#context#ai agent#memory#persistence#filesystem#mif
One-click install
npx skills add https://github.com/zircote/mnemonic --skill mnemonic
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mnemonic
Source: https://github.com/zircote/mnemonic/tree/main/docs/archive/templates/codex-skill
Command: npx skills add https://github.com/zircote/mnemonic --skill mnemonic

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides persistent, version-controlled memory for AI agents by leveraging a filesystem-based approach, enabling context retention across sessions.

Core Features & Use Cases

  • Capture & Recall: Store and retrieve semantic, episodic, and procedural memories.
  • Structured Storage: Organize memories into namespaces like decisions, learnings, and patterns.
  • Use Case: Capture a complex architectural decision made during a coding session, including the reasoning and alternatives considered, so it can be easily recalled and referenced in future sessions.

Quick Start

Capture a new memory about a decision by running the provided capture memory command.

Frequently Asked Questions about mnemonic

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

FAQPage Schema
How do I add persistent memory to an AI agent across sessions?▼

Persistent AI agent memory is managed via a filesystem-based system that stores and retrieves semantic, episodic, and procedural memories. This enables context retention across sessions using structured storage in namespaces.

What is the best way to structure AI agent memory storage in namespaces?▼

AI agent memory storage is organized into namespaces like decisions, learnings, and patterns. This structured filesystem approach allows you to capture architectural reasoning and retrieve specific episodic memories efficiently later.

Can I capture and retrieve episodic memories for an AI agent using standard Unix tools?▼

Yes, capturing and retrieving episodic memories is handled using standard Unix tools. The system provides specific commands for searching, capturing, and listing memories directly from the filesystem.

Does filesystem-based AI agent memory support version control?▼

Filesystem-based AI agent memory provides persistent, version-controlled storage. By leveraging standard filesystem structures, it ensures semantic and procedural memories are retained and tracked over time.

When do I need a filesystem memory system for AI agent context retention?▼

A filesystem memory system is needed when you want to capture complex architectural decisions and retrieve them in future coding sessions. It provides persistent memory for AI agents without requiring external database dependencies.

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