@ruvector/cli

Manage RuVector vector databases via npx command-line operations.

1|Updated Feb 8, 2026
One-click install
npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-cli
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: @ruvector/cli
Source: https://github.com/ricable/cli-skills-builder/tree/main/.claude/skills/ruvector-cli
Command: npx skills add https://github.com/ricable/cli-skills-builder --skill ruvector-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a command-line interface for managing the RuVector vector database, enabling efficient vector operations, index management, and AI-driven task routing.

Core Features & Use Cases

  • Vector Database Management: Initialize, insert, search, delete, and manage vector data.
  • HNSW Indexing: Build, optimize, and manage HNSW indexes for fast search.
  • Self-Learning Hooks: Integrate AI-driven learning for task routing and performance improvement.
  • Agent Routing: Intelligently route tasks to appropriate agents.
  • Benchmarking: Measure performance of insert, search, and HNSW operations.

Quick Start

Use the @ruvector/cli skill to initialize a new vector database with 384 dimensions.

Frequently Asked Questions about @ruvector/cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I manage a vector database from the command line?

You can manage a vector database directly from the command line using npx commands to initialize storage, insert vectors, and perform searches without needing a separate server application.

How do I build and optimize an HNSW index for vector search?

Building an HNSW index involves using specific terminal commands to construct and tune the graph parameters, ensuring fast approximate nearest neighbor search for your vector dataset.

Can I use AI agent routing to optimize task performance?

Yes, you can use AI agent routing to intelligently direct tasks to appropriate agents, leveraging self-learning hooks to continuously optimize task routing and overall performance.

What is the best way to benchmark vector insertion and search operations?

Benchmarking vector operations involves running built-in terminal commands that measure and report the performance metrics of insert, search, and HNSW index building processes.

Do I need any external dependencies to use the RuVector CLI?

No external dependencies are required to use the RuVector CLI, as it operates directly via npx commands in your terminal for immediate vector database management and interaction.