memoria

Maintain persistent OpenClaw session memory in a local Markdown file.

5|1|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/contrario/aetherlang --skill memoria
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: memoria
Source: https://github.com/contrario/aetherlang/tree/main/skills/memoria
Command: npx skills add https://github.com/contrario/aetherlang --skill memoria

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

MEMORIA addresses the issue of context loss between OpenClaw sessions by providing a persistent, local memory layer that the agent reads at startup and updates as learning occurs.

Core Features & Use Cases

  • Persistent memory file at ~/.memoria/memory.md for each user.
  • Structured memory sections (Who I am, What I'm building, Decisions, Lessons, Blockers, Current Focus, etc.).
  • Memory lifecycle commands and pattern detection to improve response quality and consistency.

Quick Start

Install MEMORIA and start a session to initialize your memory.

Frequently Asked Questions about memoria

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

FAQPage Schema
How do I keep AI session context across conversations?

To keep AI session context across conversations, a persistent local memory file is maintained at ~/.memoria/memory.md. Your agent loads this structured context at startup and tracks decisions, lessons, and blockers continuously across sessions.

Can I use persistent memory management for multi-project workflows?

Yes, persistent memory management supports multi-project workflows and solo founders. It structures session context into specific sections like What I'm building, Current Focus, and Blockers to track progress across different initiatives seamlessly.

What is the best way to maintain local storage for AI agent memory?

The best way to maintain local storage for AI agent memory is using a structured local markdown file. The agent reads this file at startup and applies real-time updates during the session, ensuring privacy without external database dependencies.

How does a memory lifecycle work for an OpenClaw agent?

A memory lifecycle for an OpenClaw agent works by loading a local memory file at startup and executing real-time updates as learning occurs. It utilizes pattern detection to improve response quality and consistency throughout the active session.

Does persistent AI memory work without external dependencies?

Yes, persistent AI memory works without external dependencies. It relies entirely on local file storage to preserve session context, ensuring your data remains private and accessible without requiring external database connections.