Skill Store 33

Memory Management

AgentDB memory system with HNSW vector search.

by ruvnet · MIT

The skill

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. Use when: 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. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.

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

npx @claude-flow/cli memory store --key "[key]" --value "[value]" --namespace patterns

Example:

npx @claude-flow/cli memory store --key "auth-jwt-pattern" --value "JWT validation with refresh tokens" --namespace patterns

Semantic Search

Search memory using semantic similarity

npx @claude-flow/cli memory search --query "[search terms]" --limit 10

Example:

npx @claude-flow/cli memory search --query "authentication best practices" --limit 5

Retrieve Entry

Retrieve a specific memory entry by key

npx @claude-flow/cli memory get --key "[key]" --namespace [namespace]

Example:

npx @claude-flow/cli memory get --key "auth-jwt-pattern" --namespace patterns

List Entries

List all entries in a namespace

npx @claude-flow/cli memory list --namespace [namespace]

Example:

npx @claude-flow/cli memory list --namespace patterns --limit 20

Delete Entry

Delete a memory entry

npx @claude-flow/cli memory delete --key "[key]" --namespace [namespace]

Initialize HNSW Index

Initialize HNSW vector search index

npx @claude-flow/cli memory init --enable-hnsw

Memory Stats

Show memory usage statistics

npx @claude-flow/cli memory stats

Export Memory

Export memory to JSON

npx @claude-flow/cli memory export --output memory-backup.json

Scripts

Script Path Description
memory-backup .agents/scripts/memory-backup.sh Backup memory to external storage
memory-consolidate .agents/scripts/memory-consolidate.sh Consolidate and optimize memory

References

Document Path Description
HNSW Guide docs/hnsw.md HNSW vector search configuration
Memory Schema docs/memory-schema.md Memory namespace and schema reference

Best Practices

  1. Check memory for existing patterns before starting
  2. Use hierarchical topology for coordination
  3. Store successful patterns after completion
  4. Document any new learnings

Use this skill

Connect your agent to the Skill Store MCP server and ask for it by ref: ruvnet/memory-management-31905905500.

Download SKILL.md · Markdown version

Details

Publisher
ruvnet
Category
AI & Agents › Memory & context
License
MIT
Updated
2026-10-18

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