Manage RuVector graph databases with Cypher queries and HNSW vector search.
npx skills add https://github.com/ricable/cli-skills-builder --skill agentdb-ricable
Please help me install this Agent Skill. Skill: agentdb Source: https://github.com/ricable/cli-skills-builder/tree/main/.claude/skills/agentdb Command: npx skills add https://github.com/ricable/cli-skills-builder --skill agentdb-ricable
This Skill provides a powerful command-line interface for managing a RuVector-powered graph database, enabling efficient data storage, querying, and analysis.
Initialize a new AgentDB database in the current directory.
High-intent search queries and answers about installing and using this skill.
You can execute Cypher queries directly via a graph database CLI, which supports complex graph operations, hyperedges, and ACID persistence without needing a separate server GUI. This CLI handles initialization, querying, and data management directly from your terminal.
Yes, vector similarity search is supported using HNSW indexing within the graph database. It allows you to perform fast vector searches on embedded data, enabling AI-driven insights and efficient knowledge graph management for your agents.
The best way to manage a local knowledge graph is using a CLI tool that handles database initialization, server startup, and data import/export. It provides a programmatic API and command-line interface for storing entities and relationships efficiently.
Yes, the graph database CLI supports both ACID persistence for reliable data transactions and hyperedges for modeling complex relationships. This ensures data integrity while allowing advanced graph structures in your knowledge graph.
Data import and export are handled directly through the graph database CLI. You can use the built-in commands to move data in and out of the RuVector-powered database, facilitating backups and data migration for your knowledge graph.
Use the CLI for quick database initialization, server startup, and direct Cypher queries, while the programmatic API is better for integrating graph operations, vector indexing, and knowledge graph management into automated applications.
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