surrealdb-expert

Name: surrealdb-expert
Availability: InStock
Author: RepairYourTech

Guide SurrealDB 3.0 multi-model database design and SurrealQL 3.0 syntax.

6|1|Updated Feb 27, 2026

Search Tags:#authentication #database #vector database #multi-model #surrealdb #graph database #surrealql

Ready to run

npx skills add https://github.com/RepairYourTech/cfsa-antigravity --skill surrealdb-expert-repairyourtech

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: surrealdb-expert
Source: https://github.com/RepairYourTech/cfsa-antigravity/tree/main/.agent/skill-library/stack/databases/surrealdb-expert
Command: npx skills add https://github.com/RepairYourTech/cfsa-antigravity --skill surrealdb-expert-repairyourtech

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides comprehensive guidance for designing, querying, and securing applications using SurrealDB 3.0, enabling efficient multi-model data management.

Core Features & Use Cases

Multi-Model Design: Covers document, graph, vector, and KV data models within a single database.
SurrealQL 3.0: Detailed syntax for queries, schema definitions, authentication, and API endpoints.
Security Hardening: Best practices for authentication, permissions, and network security.
Use Case: You are building a new application that requires both a traditional document store for user profiles and a graph database to represent social connections. This Skill will guide you through defining the schema, setting up authentication, and writing efficient queries for both models.

Quick Start

Use the surrealdb-expert skill to define a new user table with email and password fields.

Frequently Asked Questions about surrealdb-expert

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

FAQPage Schema

How do I manage document and graph data in a single multi-model database?▼

To manage document and graph data in a multi-model database, use SurrealDB 3.0 to define schemas and coordinate cross-store queries. It natively supports document, graph, vector, and key-value models within a single database engine using SurrealQL.

Can I set up authentication and custom API endpoints directly in SurrealDB 3.0?▼

Yes, SurrealDB 3.0 supports setting up authentication and custom API endpoints natively. You use SurrealQL syntax with DEFINE ACCESS for authentication and DEFINE API to create custom endpoints for your applications.

What is the syntax for implementing vector indexing in a multi-model database?▼

Implementing vector indexing in SurrealDB 3.0 involves using HNSW vector indexing. You define vector indexes through SurrealQL syntax to efficiently store and query vector embeddings alongside document and graph data.

How do I define schemas and computed fields in SurrealQL 3.0?▼

Defining schemas and computed fields in SurrealQL 3.0 involves using specific syntax to establish table structures and record references. You can create dynamic computed fields to automatically calculate values based on other record data.

Does SurrealDB 3.0 work for polyglot persistence architectures?▼

Yes, SurrealDB 3.0 works for polyglot persistence architectures by consolidating multiple data models into a single engine. It eliminates the need for separate databases by handling document, graph, vector, and key-value stores simultaneously.

What are the best practices for security hardening in a multi-model database?▼

Security hardening in SurrealDB 3.0 involves configuring proper authentication and permissions using DEFINE ACCESS. You should apply strict access controls and network security best practices to protect cross-store data.