RuView — AgentDB Vector Search

Name: RuView — AgentDB Vector Search
Availability: InStock
Author: ruvnet

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligen

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skill

AI & Machine Learning

intermediate

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4/5 quality

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Last updated: October 22, 2026

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Quick Start

Install Command

npx skills add ruvnet/RuView --skill agentdb-vector-search

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3-5hrs/WK

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AgentDB Vector Search

What This Skill Does

Implements vector-based semantic search using AgentDB's high-performance vector database with 150x-12,500x faster operations than traditional solutions. Features HNSW indexing, quantization, and sub-millisecond search (<100µs).

Prerequisites

Node.js 18+
AgentDB v1.0.7+ (via agentic-flow or standalone)
OpenAI API key (for embeddings) or custom embedding model

Quick Start with CLI

Initialize Vector Database

# Initialize with default dimensions (1536 for OpenAI ada-002)
npx agentdb@latest init ./vectors.db

#

**Install**

```bash
npx skills add ruvnet/RuView --skill agentdb-vector-search

Or copy the skill folder manually:

git clone https://github.com/ruvnet/RuView.git
cp -r RuView/.claude/skills/agentdb-vector-search/ ~/.claude/skills/agentdb-vector-search

Source: ruvnet/RuView — 99,120 stars, MIT, verified 2026-10-22.

RuView — AgentDB Vector Search

AI Skill Market Insights

Quick Start

Install Command

TEAR & SHARE

Tags

Multi-Agent Patterns

Be Part of the 0+ Developer Community

AgentDB Vector Search

What This Skill Does

Prerequisites

Quick Start with CLI

Initialize Vector Database

License

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Context Degradation Detection

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