openmemory

Store and retrieve persistent memories across sessions using Markdown files with YAML front matter.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OpenMemory provides a filesystem-based persistent memory layer for coding agents, enabling context, decisions, and preferences to survive session boundaries.

Core Features & Use Cases

  • Persistent storage of project decisions, architectural notes, gotchas, and task state in Markdown with YAML front matter.
  • Cross-session and cross-project memory that can be browsed and updated using memory_list, memory_get, memory_search, and memory_store.
  • Guardrails and safety rules to avoid storing secrets and to maintain a clear paper trail when memories conflict.

Quick Start

Store a memory entry at the start of a task and retrieve it later to maintain continuity.

Frequently Asked Questions about openmemory

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

FAQPage Schema
How do I keep agent memory and context persistent across sessions?

You can record architectural decisions and task state by storing memory entries as Markdown files with YAML front matter, then retrieve them later using memory_list, memory_get, and memory_search tools to maintain project continuity.

How do I store architectural decisions and project conventions for coding agents?

You can record architectural decisions and task state by storing memory entries as Markdown files with YAML front matter, then retrieve them later using memory_list, memory_get, and memory_search tools to maintain project continuity.

What is the best way to maintain project memory continuity without a database?

This approach uses Markdown files with YAML front matter as a filesystem-based persistent memory layer, applying to project and global scopes to maintain context and preferences without requiring a database.

Does this persistent memory approach work for cross-project context retrieval?

Yes, it supports cross-session and cross-project memory that can be browsed and updated using memory_list, memory_search, and memory_store, allowing you to retrieve context across different project scopes.

What are the limitations of using Markdown files for agent memory persistence?

Limitations include following guardrails to avoid storing secrets and maintaining a clear paper trail when conflicting memories arise across the filesystem-based Markdown memory layer.