How do I install the Openmemory skill?

Run npx skillmds add majiayu000/openmemory in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Openmemory skill do?

Persistent long-term agent memory for storing and querying past work, patterns, and learnings. It is listed under AI & ML on SkillMD.

Is Openmemory safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Openmemory?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Openmemory free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Openmemory?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Openmemory by majiayu000 — Agent Skill

Name: Openmemory
Rating: 4.2 (5 reviews)
Author: majiayu000

File contents

OpenMemory (Persistent Agent Memory)

You have access to OpenMemory for persistent long-term memory across sessions.

Memory Tools

Tool	Purpose
`openmemory_query`	Semantic search across memories by similarity
`openmemory_store`	Store new memories with sector classification
`openmemory_list`	List recent memories for a user/agent
`openmemory_get`	Retrieve specific memory by ID
`openmemory_reinforce`	Boost salience of important memories

Memory Sectors

Memories are classified into sectors:

Sector	Use Case	Example
episodic	Events, task history	"Implemented auth flow for project X"
semantic	Facts, learned patterns	"Always add Context7 lookup before Rust implementation"
procedural	How-to knowledge	"Steps to deploy with ArgoCD"

Usage Patterns

Before starting a task:

openmemory_query({ query: "similar implementations", sector: "episodic" })

After completing a task:

openmemory_store({ 
  content: "Implemented OAuth2 with PKCE for React app using Effect",
  sector: "episodic",
  tags: ["auth", "react", "effect"]
})

For important learnings:

openmemory_reinforce({ memory_id: "mem_xyz", boost: 1.5 })

Best Practices

Query before implementing - Check for similar past work
Store after completing - Save successful patterns and solutions
Reinforce important memories - Boost salience of critical learnings
Tag memories well - Include relevant technologies and patterns

Frequently asked questions