Design Metadata Schema

Community

dandye

design-metadata-schema

Design comprehensive metadata frameworks. Develops structured metadata templates and tagging systems.

Overview

Publisher	dandye
Repository	`ai-runbooks`
Skill name	`design-metadata-schema`
Stars	126
Forks	34
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by dandye on GitHub. Read the source before you install it.

Installation

Install the Design Metadata Schema AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/dandye/ai-runbooks.git /tmp/ai-runbooks
mkdir -p .claude/skills
cp -r /tmp/ai-runbooks/skills/design-metadata-schema .claude/skills/design-metadata-schema

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design Metadata Schema in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Design Metadata Schema on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Design Metadata Schema is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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.

Frequently asked questions

What does the Design Metadata Schema AI skill do?

Design comprehensive metadata frameworks. Develops structured metadata templates and tagging systems.

Why use Design Metadata Schema on TypingMind?

Because you install it once and use it with any model. Design Metadata Schema is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Design Metadata Schema in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dandye/ai-runbooks/tree/main/skills/design-metadata-schema. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Design Metadata Schema?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Design Metadata Schema?

As many as you like. As long as a model supports skills, you can use Design Metadata Schema with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Design Metadata Schema AI skill free?

Yes. It is published on GitHub by dandye under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Design Metadata Schema Skill

Inputs

Workflow

Step 1: Requirement Analysis

Step 2: Schema Definition

Step 3: Constraints & Validation

Step 4: Schema Output

Required Outputs

Quick Reference

Frequently asked questions

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