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

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