ontology

Manage typed knowledge graphs with Python scripts and a JSONL store.

1|Updated Mar 11, 2026
One-click install
npx skills add https://github.com/zhengxuyu/default-talents --skill ontology-zhengxuyu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ontology
Source: https://github.com/zhengxuyu/default-talents/tree/main/general-assistant/skills/ontology
Command: npx skills add https://github.com/zhengxuyu/default-talents --skill ontology-zhengxuyu

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a structured way to manage and query information, enabling agents to build a persistent, verifiable knowledge graph for memory and complex reasoning.

Core Features & Use Cases

  • Knowledge Representation: Define and manage entities (Person, Project, Task, etc.) with types, properties, and relations.
  • Data Validation: Enforce constraints and schemas to ensure data integrity.
  • Graph Traversal: Query and navigate relationships between entities for complex information retrieval.
  • Use Case: An agent needs to track project dependencies. It can use the ontology skill to link tasks, mark blockers, and query for tasks that are currently impeding progress.

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?

You build a structured knowledge graph for agent memory by defining typed entities like Person, Project, and Task, then linking them through relations. This creates a persistent, verifiable memory store for complex reasoning using a JSONL graph format.

What is the best way to enforce schema validation on a knowledge graph?

The best way to enforce schema validation on a knowledge graph is using scripts that apply constraints to your entity properties and relations. This ensures data integrity by validating types before any CRUD operations are committed to the graph store.

How do I query entity relationships in a typed graph database?

You query entity relationships in a typed graph database by using command-line scripts to perform graph traversal. This allows you to navigate and retrieve complex relational data, such as finding tasks impeding a project's progress.

Can I use Python scripts to manage graph transformations on a JSONL store?

Yes, you can use Python scripts to manage graph transformations on a JSONL store. The Skill operates via a command-line interface that executes Python scripts for CRUD and relational operations, enabling composable transformations.

Do I need a separate graph database to track project dependencies and blockers?

No, you do not need a separate graph database to track project dependencies and blockers. The Skill operates on a local JSONL graph store, allowing you to link tasks, mark blockers, and query impediments directly via the command line.