ontology

You build a typed knowledge graph by using a CLI to create, query, and relate entities like Person, Project, and Task, while enforcing constraints to maintain data integrity across skills.

A typed entity model represents people, projects, tasks, events, and documents with defined relations. You need it to structure agent memory and enforce consistent constraints across complex workflows.

You query related entities in a knowledge graph by using the exposed CLI to traverse relations across typed entities, allowing you to retrieve connected tasks or documents for a specific Person.

Yes, you can manage knowledge graph entities using local storage allocated in memory, which supports creating, validating, and linking entities directly within your local environment.

Yes, the typed knowledge graph supports cross-skill data sharing by maintaining consistent constraints across the graph, allowing complex workflows to be planned as graph transformations and reused across skills.

An in-memory knowledge graph limits entity persistence to the local storage environment, meaning stored entities, relations, and schemas are retained in memory rather than in a permanent external database.