Transform lengthy documents into a semantic tree structure. It extracts sections, summaries, and hierarchies optimized for use with Large Language Models (LLMs).

2026-04-092

ontology-define

dandye/information-architecture

Design formal ontologies using OWL/RDFS. Defines classes, properties, and relationships for complex semantic modeling.

2026-02-062

content-inventory

dandye/information-architecture

Systematic cataloging of information assets. Creates comprehensive inventories or card sorting materials from content.

2026-02-062

json-ld-generate

dandye/information-architecture

Generate JSON-LD structured data for web content. Maps content to Schema.org types to improve search engine understanding and rich result eligibility.

2026-02-062

name	metadata-schema-design
description	Design comprehensive metadata frameworks. Develops structured metadata templates and tagging systems.
required_roles	{"scribe":"roles/scribe.editor"}
personas	["information-architect","data-architect","content-strategist"]

Design Metadata Schema Skill

Develop a comprehensive metadata schema for content management. This skill defines structured fields, validation rules, and standards compliance to improve searchability and management.

Inputs

PATH - The content domain to apply the schema to (e.g., "/content")
OUTPUT_FORMAT - (Optional) The output format for the schema, e.g., "json-schema", "xml", "markdown" (default: "json-schema")
DUBLIN_CORE - (Optional) Boolean, whether to align with Dublin Core standards (default: true)
CUSTOM_FIELDS - (Optional) List of custom business-specific fields to include
VALIDATION_RULES - (Optional) Boolean, whether to define validation logic for fields (default: true)

Workflow

Step 1: Requirement Analysis

Analyze the content types at PATH to determine metadata needs.

Identify common attributes (Title, Date, Author).
Identify specific attributes (Product ID, Version, Region).

Step 2: Schema Definition

Define the fields and their properties.

Standard Fields: Map to Dublin Core (Title, Creator, Subject, etc.) if enabled.
Custom Fields: Define fields specified in CUSTOM_FIELDS or discovered during analysis.

Step 3: Constraints & Validation

If VALIDATION_RULES is true, define:

Data Types: String, Date, Integer, Boolean, Enum.
Required/Optional: Cardinality constraints.
Controlled Vocabularies: Allowed values for specific fields.

Step 4: Schema Output

Generate the schema definition in the requested OUTPUT_FORMAT (e.g., JSON Schema, XML Schema, or Markdown Table).

Required Outputs

A METADATA_SCHEMA object in the specified OUTPUT_FORMAT containing:

Field Dictionary: Name, Description, Type, Multiplicity.
Validation Logic: Rules for data entry.
Mapping: Correspondence to standards (like Dublin Core).

Quick Reference

Purpose: Standardize content tagging for consistency and interoperability.
Standards: Dublin Core, Schema.org.