🧠 AgentDB & Memory Skills
/development-tools/agentdb--memory-skills
Skills are reusable workflows that combine agents, hooks, and patterns into ready-to-use solutions. Think of them as "recipes" for common development tasks.
How Skills Work
┌──────────────────────────────────────────────────────────────────┐
│ SKILL EXECUTION │
├──────────────────────────────────────────────────────────────────┤
│ You: "Run /github-code-review" │
│ ↓ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Load Skill │──▶│ Spawn Agents│──▶│ Execute │ │
│ │ Definition │ │ (5 agents) │ │ Workflow │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
│ │ │ │
│ └──── Learns from outcome ─────────┘ │
└──────────────────────────────────────────────────────────────────┘All 42 Skills by Category
Details
| Skill | What It Does | When To Use |
|---|---|---|
agentdb-vector-search | Semantic search with 150x faster retrieval | Building RAG systems, knowledge bases |
agentdb-memory-patterns | Session memory, persistent storage, context management | Stateful agents, chat systems |
agentdb-learning | 9 RL algorithms (PPO, DQN, SARSA, etc.) | Self-learning agents, behavior optimization |
agentdb-optimization | Quantization (4-32x memory reduction), HNSW indexing | Scaling to millions of vectors |
agentdb-advanced | QUIC sync, multi-database, custom distance metrics | Distributed AI systems |
bash
/agentdb-vector-search