Memory Management Skill
Purpose
AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management.
When to Trigger
- need to store successful patterns
- searching for similar solutions
- semantic lookup of past work
- learning from previous tasks
- sharing knowledge between agents
- building knowledge base
When to Skip
- no learning needed
- ephemeral one-off tasks
- external data sources available
- read-only exploration
Commands
Store Pattern
Store a pattern or knowledge item in memory
Example:
Semantic Search
Search memory using semantic similarity
Example:
Retrieve Entry
Retrieve a specific memory entry by key
Example:
List Entries
List all entries in a namespace
Example:
Delete Entry
Delete a memory entry
Initialize HNSW Index
Initialize HNSW vector search index
Memory Stats
Show memory usage statistics
Export Memory
Export memory to JSON
Scripts
References
Best Practices
- Check memory for existing patterns before starting
- Use hierarchical topology for coordination
- Store successful patterns after completion
- Document any new learnings
