agentdb-performance-optimization

bjpl/open_learn_co

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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Installation

Option 1: Use slash command in Claude Code

/install-skill https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization

Option 2: Clone to skills directory

# Global (all projects)

git clone https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization ~/.claude/skills/open_learn_co

# Project-specific

git clone https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization .claude/skills/open_learn_co

Add MCP server to .cursor/mcp.json:

{
  "mcpServers": {
    "skillz": {
      "command": "npx",
      "args": ["-y", "skillz-mcp", "https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization"]
    }
  }
}

Restart Cursor after adding the configuration.

Option 1: Use Gemini CLI command

gemini extensions install https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization

Option 2: Clone to extensions directory

git clone https://github.com/bjpl/open_learn_co/tree/main/.claude/skills/agentdb-optimization ~/.gemini/extensions/open_learn_co

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