ontology

Create and validate typed knowledge graphs of entities and relations.

Updated Mar 19, 2026

Search Tags:#ontology #validation #schema #CLI #knowledge #graph

Ready to run

npx skills add https://github.com/gaos6e/MyOpenclaw --skill ontology-gaos6e

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ontology
Source: https://github.com/gaos6e/MyOpenclaw/tree/main/workspace/skills/ontology
Command: npx skills add https://github.com/gaos6e/MyOpenclaw --skill ontology-gaos6e

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yaml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

A typed vocabulary + constraint system for representing knowledge as a verifiable graph to support memory, reasoning, and cross-skill data sharing.

Core Features & Use Cases

Create and relate entities such as Person, Project, Task, Event, and Document with typed constraints.
Enforce type schemas, cardinality, and graph constraints to ensure data integrity.
Plan multi-step graph transformations and query traversals to derive insights and drive workflows.

Quick Start

Initialize storage and begin modeling entities with the CLI and schema tooling.

Frequently Asked Questions about ontology

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I build a typed knowledge graph to model entities and enforce schema constraints?▼

Build a typed knowledge graph by defining entity types and relations in a schema.yaml file, then use a CLI workflow to create, relate, and validate entities. This enforces type schemas and cardinality constraints to ensure data integrity across your graph store.

What is a typed knowledge graph used for when orchestrating multiple skills?▼

A typed knowledge graph provides a verifiable vocabulary and constraint system for representing knowledge, enabling memory, reasoning, and cross-skill data sharing. It supports multi-step graph transformations and query traversals to derive insights and drive workflows.

How do I validate type constraints and cardinality in a knowledge graph?▼

Validate type constraints and cardinality by defining allowed entity types and relations in schema.yaml, then running the validate CLI command against your append-only graph store to enforce data integrity and schema compliance.

Do I need YAML to define schemas for a typed knowledge graph?▼

Yes, YAML is required to define schemas. The schema.yaml file specifies entity types such as Person, Project, and Task, along with their typed relations and cardinality constraints, serving as the foundation for graph validation.

Can I plan multi-step graph transformations and query traversals with this approach?▼

Yes, you can plan multi-step graph transformations and execute query traversals across the typed knowledge graph. This allows you to derive insights from related entities and drive complex workflows through the CLI interface.

What are the limitations of using an append-only graph store for knowledge modeling?▼

An append-only graph store prevents modification or deletion of existing entities and relations, meaning graph transformations must be planned as new additions rather than updates, which ensures data verifiability but limits destructive editing.