# Memory Management

> AgentDB memory system with HNSW vector search. Use when: need to store patterns, search for solutions, semantic lookup. Skip when: no learning needed, ephemeral tasks.

- Skill: `mahabdalla/memory-management` (Agent Skill)
- Install (CLI): `npx skillmds@latest add mahabdalla/memory-management`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mahabdalla/memory-management/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: mahabdalla (https://skillmd.com/u/mahabdalla)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/mahabdalla/memory-management

---


# Memory Management Skill

## Purpose
AgentDB memory system with HNSW vector search.

## When to Trigger
- need to store patterns
- search for solutions
- semantic lookup

## When to Skip
- no learning needed
- ephemeral tasks

## Commands

### Store Data
Store a pattern in memory

```bash
npx @claude-flow/cli memory store --key "key" --value "value" --namespace patterns
```

### Search Data
Semantic search in memory

```bash
npx @claude-flow/cli memory search --query "search terms" --limit 10
```



## 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

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