ontology

Name: ontology
Availability: InStock
Author: dsactivi-2

Manage typed knowledge graphs with enforced entity and relation constraints.

Updated Feb 16, 2026

Search Tags:#knowledge graph #ontology #data management #graph database #entity resolution #structured memory

Ready to run

npx skills add https://github.com/dsactivi-2/Mujo-Team --skill ontology-dsactivi-2

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: ontology
Source: https://github.com/dsactivi-2/Mujo-Team/tree/main/skills/ontology
Command: npx skills add https://github.com/dsactivi-2/Mujo-Team --skill ontology-dsactivi-2

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a structured and verifiable way to store, query, and manage complex knowledge graphs, enabling agents to maintain consistent state and share information effectively.

Core Features & Use Cases

Typed Knowledge Representation: Define entities with types, properties, and relations, enforcing constraints for data integrity.
Graph Operations: Supports CRUD operations, relation linking, and complex graph traversals for sophisticated data retrieval.
Use Case: An agent needs to remember details about a project, its tasks, and the people involved. It can create Project, Task, and Person entities, link them with relations like has_task and assigned_to, and later query for all open tasks assigned to a specific person within that project.

Quick Start

Use the ontology skill to create a new person entity named Alice.

Frequently Asked Questions about ontology

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

FAQPage Schema

How do I build a structured knowledge graph for agent memory?▼

A typed knowledge graph enables structured agent memory by creating entities like Person, Project, and Task, then linking them with validated relations such as assigned_to. It enforces type constraints for consistent state management.

What's the best way to manage entity resolution and data integrity in a graph database?▼

Managing entity resolution in a graph database is best handled through enforced type constraints and relation validation. Defining entities with specific properties ensures data integrity during complex graph traversals and CRUD operations.

How do I query open tasks assigned to a specific person within a project knowledge graph?▼

To query open tasks assigned to a person within a project knowledge graph, you perform complex graph traversals. You link Project, Task, and Person entities with relations like has_task and assigned_to, then retrieve matching nodes.

Can I use CLI scripts for deterministic graph transformations and state management?▼

Yes, you can use CLI scripts for deterministic graph transformations and state management. The ontology skill operates via command line scripts to execute reliable CRUD operations and relation linking without ambiguity.

Does this knowledge graph approach support composable skills with enforced type constraints?▼

Yes, this knowledge graph approach supports composable skills by enforcing strict type constraints on entities and relations. This validation ensures that different skills can reliably share and query structured memory without data conflicts.