memory-management
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.
Profile →npx skills add ruvnet/ruflo --skill memory-management --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ```bash npx @claude-flow/cli memory store --key "[key]" --value "[value]" --namespace patterns ``` **Example:** ```bash 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 ```bash npx @claude-flow/cli memory search --query "[search terms]" --limit 10 ``` **Example:** ```bash npx @claude-flow/cli memory search --query "authentication best practices" --limit 5 ``` ### Retrieve Entry Retrieve a specific memory entry by key ```bash
- Purpose
- When to Trigger
- When to Skip
- Commands
- Store Pattern
- Semantic Search
- Retrieve Entry
- List Entries
- Delete Entry
- Initialize HNSW Index
- Memory Stats
- Export Memory
- Scripts
- References
npx @claude-flow/cli memory store --key "[key]" --value "[value]" --namespace patterns npx @claude-flow/cli memory store --key "auth-jwt-pattern" --value "JWT validation with refresh tokens" --namespace patterns npx @claude-flow/cli memory search --query "[search terms]" --limit 10 npx @claude-flow/cli memory search --query "authentication best practices" --limit 5 npx @claude-flow/cli memory get --key "[key]" --namespace [namespace] npx @claude-flow/cli memory get --key "auth-jwt-pattern" --namespace patterns npx @claude-flow/cli memory list --namespace [namespace] npx @claude-flow/cli memory list --namespace patterns --limit 20 npx @claude-flow/cli memory delete --key "[key]" --namespace [namespace] npx @claude-flow/cli memory init --enable-hnsw
What does the memory-management skill do?
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.
How do I install it?
Run `npx skills add ruvnet/ruflo --skill memory-management --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.