memory-schema

To validate notes in a knowledge graph, you define a schema for a specific entity type and then check existing notes against it to identify missing fields or type mismatches. This ensures data integrity and consistency.

Schema inference automatically suggests formal schema structures by analyzing existing notes. It identifies common fields across notes of the same type, like Meetings or Tasks, to help you standardize your structured note-taking format.

You create a schema for meeting notes by defining required fields such as topic, date, and attendees using Picoschema syntax. This formalizes the structure so all meeting notes maintain uniform fields and formats.

Yes, schema drift detection identifies existing notes that no longer conform to their defined schemas. It flags missing fields or type mismatches, ensuring your structured notes maintain data integrity over time.

You need Picoschema syntax when you want to define, update, or enforce the structure of entity types like People and Meetings. It provides the validation tools required to maintain consistency across your knowledge graph.

You update schemas by editing the existing structure for a note type, then validating all related notes against the new definition. This facilitates schema evolution while ensuring existing notes conform to the updated format.