ontology

A knowledge graph structures agent memory by providing typed entities and relationships for data management. You can create, query, and manage entities like Person or Project to maintain structured state across complex workflows.

A typed knowledge graph for composable skills is a structured data model that enforces constraints on entities and relationships. It supports CRUD operations and graph traversal to enable state sharing between different skills.

To enforce data constraints in an ontology knowledge graph, you define typed relationships and rules during entity creation. The graph structure ensures data integrity by validating operations against these defined constraints.

Yes, you can use Python to manage knowledge graph entities and relationships. The ontology requires Python scripts to execute CRUD operations, perform graph traversal, and enforce constraints on entities like Person, Project, and Task.

You plan multi-step actions as graph transformations by modeling workflow steps as sequential changes to the knowledge graph. This approach maps state transitions to graph modifications, enabling robust management of complex workflows.

You need a structured knowledge graph for agent state sharing when multiple composable skills require access to a shared, typed memory. It facilitates reliable data exchange by maintaining a consistent entity and relationship model across skills.