ontology

To model task dependencies as a verifiable graph, this Skill stores typed entities and relations in JSONL format, applying YAML schema constraints to validate required fields, cardinality, and acyclic dependencies before you plan work.

Validating entity relationships in a knowledge graph involves applying YAML schema constraints to check required fields, forbidden properties, relation types, and event date order, catching missing fields or circular blockers using Python-based operations.

Yes, you can use YAML schemas to constrain knowledge graph entities and relations. The Skill requires YAML schema constraints to enforce required fields, enums, relation types, and cardinality against your JSONL graph storage.

The best way to track project ownership and event attendance in structured memory is creating typed entities like Person, Project, and Event, then linking them with graph relationships such as ownership, assignment, and event attendance.

Yes, structured memory supports cross-skill state sharing for task tracking. The Skill stores connected knowledge as a typed graph with entities and relations, enabling consistent project tracking, task dependencies, and document linking across workflows.

To check for circular blockers and acyclic dependencies in project tracking, you validate the graph for constraint violations, ensuring task dependencies remain acyclic and event date order is maintained before planning work.