Typeql

What it does

This skill, typeql, allows AI agents to interact with and query data using the TypeQL language. It enables structured data retrieval and manipulation based on defined schemas and relationships. The agent can execute complex queries against datasets described by TypeQL models, returning results in a predictable format.

When to use it

• Data Extraction: Extract specific information from documents or databases where a TypeQL schema is already defined.
• Knowledge Graph Queries: Retrieve connections and entities within a knowledge graph represented using TypeQL.
• Structured Data Reporting: Generate reports based on data conforming to a TypeQL model, allowing for consistent formatting and analysis.
• Data Validation: Verify that new or existing data adheres to the constraints defined in a TypeQL schema.

Key capabilities

• TypeQL query execution
• Schema definition and management (implied)
• Structured result retrieval

Example prompts

• "Execute this TypeQL query: ...query string..."
• "Find all entities of type 'Product' with a price greater than 100."
• "Run the following TypeQL statement and return the results in JSON format: ...TypeQL statement..."

Tips & gotchas

Requires familiarity with the TypeQL language and access to a dataset defined by a corresponding TypeQL schema. The agent's performance depends on the complexity of the query and the size of the underlying data source.