create-specification

Name: create-specification
Availability: InStock
Author: tamago0224

Generate machine-readable specification documents with YAML frontmatter and structured Markdown sections.

Updated Mar 8, 2026

Search Tags:#automation #templates #documentation #specification #ai #yaml #frontmatter

Ready to run

npx skills add https://github.com/tamago0224/kuroshio-mta --skill create-specification-tamago0224

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: create-specification
Source: https://github.com/tamago0224/kuroshio-mta/tree/main/.agents/skills/create-specification
Command: npx skills add https://github.com/tamago0224/kuroshio-mta --skill create-specification-tamago0224

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the creation of structured, machine-readable specifications to guide AI-driven implementations, reducing drafting time and ambiguity.

Core Features & Use Cases

Generates a standardized specification template with required frontmatter and sections.
Ensures consistent structure across projects for machine readability and AI consumption.
Supports saving the finished document to the /spec/ directory with a descriptive name.

Quick Start

Save a new specification named spec-[your-purpose].md to the /spec/ directory using the required frontmatter and section template.

Frequently Asked Questions about create-specification

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

FAQPage Schema

How do I generate machine-readable specification documents for AI workflows?▼

Specification documents for AI implementations require standardized YAML frontmatter containing name and description fields, followed by a structured Markdown body with defined sections to ensure consistent machine readability and unambiguous AI consumption.

How do I create standardized spec templates with YAML frontmatter for AI projects?▼

Standardized spec templates with YAML frontmatter are created by defining required name and description fields in the frontmatter header, then structuring the Markdown body with consistent sections that AI agents can reliably parse and consume.

What is the best way to automate specification creation for AI-driven implementations?▼

Automating specification creation for AI-driven implementations is best achieved by applying a standardized template that enforces required YAML frontmatter and structured Markdown sections, reducing manual drafting time and eliminating ambiguity for AI consumption.

Can I use Markdown and YAML frontmatter to create AI-ready specification files?▼

Yes, you can use Markdown and YAML frontmatter to create AI-ready specification files by including required name and description properties in the YAML header and organizing the Markdown body into defined, consistent sections for reliable machine parsing.

Where should I save generated specification files for AI project workflows?▼

Generated specification files for AI project workflows should be saved to a dedicated /spec/ directory using a descriptive naming convention, such as spec-[your-purpose].md, to maintain consistent organization and easy retrieval across projects.

Does automated specification generation work for product, design, and engineering workflows?▼

Automated specification generation works across product, design, and engineering workflows by applying a consistent template with YAML frontmatter and structured Markdown sections, ensuring machine-readable spec files are standardized regardless of the specific project discipline.