Surrealdb

The surrealdb skill provides AI agents with direct access to SurrealDB, a scalable, polyglot database engine. It enables agents to perform complex queries, manage data schemas, and execute transactions across various deployment environments like Docker or cloud instances. This integration allows for seamless interaction with graph, document, key-value, and time-series data structures within a single unified system.

When to use it

• Dynamic Data Storage: When an agent needs to persist unstructured or semi-structured data from user interactions in real-time.
• Complex Relationships: For applications requiring graph-like queries to navigate relationships between entities without external mapping layers.
• Multi-Tenant Applications: When deploying agents that need to isolate and manage distinct datasets for different users or organizations efficiently.
• Schema Evolution: In scenarios where data models change frequently, requiring a database that supports flexible schema updates without downtime.

Key capabilities

• Connects to SurrealDB instances via standard drivers (Docker, Cloud, etc.)
• Executes SQL-like queries against polyglot data types
• Manages user authentication and role-based access control
• Supports live subscriptions for real-time data updates
• Handles complex transactions with automatic conflict resolution

Example prompts

1. "Create a new table called users with fields for name, email, and an array of hobbies."
2. "Insert a record into the projects table and retrieve all related tasks using a graph query."
3. "Update the status of all active sessions in the database to 'completed' based on the current timestamp."

Tips & gotchas

Ensure your AI agent has valid credentials (username/password or API keys) configured before attempting to connect to a remote SurrealDB instance. While SurrealDB supports many data types, complex nested queries may require specific syntax adjustments compared to traditional relational databases.