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L-LesterYu
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ontology-zh

Manage typed knowledge graphs with entity CRUD and relationship mapping.

51|8|Updated Feb 24, 2026
Search Tags:#knowledge graph#ontology#data modeling#memory#graph database#entity management
One-click install
npx skills add https://github.com/L-LesterYu/OpenClaw-hot-skills-zh --skill ontology-zh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ontology-zh
Source: https://github.com/L-LesterYu/OpenClaw-hot-skills-zh/tree/main/skills/ontology-zh
Command: npx skills add https://github.com/L-LesterYu/OpenClaw-hot-skills-zh --skill ontology-zh

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a structured, queryable knowledge graph to manage an AI's memory, enabling it to recall, relate, and reason about information effectively.

Core Features & Use Cases

  • Entity Management: Create, read, update, and delete typed entities (e.g., Person, Project, Task).
  • Relationship Mapping: Define and query relationships between entities (e.g., "Project X has owner Person Y").
  • Constraint Validation: Enforce data integrity through schema definitions and validation rules.
  • Use Case: When an AI needs to remember details about a project, its team members, and their assigned tasks, it can use this Skill to store and retrieve this information in a structured, interconnected way, facilitating complex planning and recall.

Quick Start

Use the ontology skill to remember that Alice is a person with the email [email protected].

Frequently Asked Questions about ontology-zh

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

FAQPage Schema
How do I structure persistent memory for an AI agent using a knowledge graph?▼

Structure persistent AI memory using a typed knowledge graph with JSONL storage. This enables entity CRUD operations, relationship mapping, and schema-based validation to ensure structured data persistence.

What is the best way to map relationships between entities in AI memory?▼

Map relationships by defining typed connections between entities within a knowledge graph. This allows an AI to query inter-entity relationships, such as linking a Project entity to a Person entity.

Can I enforce data integrity and schema validation in a JSONL knowledge graph?▼

Enforce data integrity in a JSONL knowledge graph through schema definitions and validation rules. This constraint validation ensures structured data persistence during entity management.

Does this knowledge graph approach work without a dedicated graph database?▼

Manage a typed knowledge graph without a dedicated graph database by using Python scripts and JSONL storage. This provides queryable state and inter-entity reasoning for AI agents.

When do I need a typed knowledge graph for AI state management?▼

Use a typed knowledge graph for AI state management when an AI agent requires persistent, queryable memory. It enables the agent to recall, relate, and reason about complex interconnected information like project team tasks.

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