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create-specification

Generate AI-ready specification documents with YAML frontmatter and structured sections.

9|Updated Apr 12, 2020
Search Tags:#template#documentation#specification#requirements#structure#guidelines#ai-ready
One-click install
npx skills add https://github.com/Wtyd/githooks --skill create-specification-wtyd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: create-specification
Source: https://github.com/Wtyd/githooks/tree/main/.claude/skills/create-specification
Command: npx skills add https://github.com/Wtyd/githooks --skill create-specification-wtyd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Create AI-ready specifications that define requirements, constraints, and interfaces for AI-driven solutions in a clear, machine-readable format.

Core Features & Use Cases

  • Templates: Provides a structured front matter and sections to ensure consistency across specs.
  • Guidance: Enforces inclusion of problem statements, scope, definitions, interfaces, and acceptance criteria.
  • Use Case: Teams document a new feature's AI integration requirements using the standardized spec template.

Quick Start

Save the new specification under /spec/ with a filename that matches spec-[a-z0-9-]+.md.

Frequently Asked Questions about create-specification

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

FAQPage Schema
How do I create AI-ready specifications for machine-readable development requirements?▼

To create AI-ready specifications, you generate structured documents defining requirements, constraints, and interfaces with YAML frontmatter and standardized sections like problem statements, scope, and acceptance criteria to guide AI integrations.

What should be included in a specification template for AI-driven solutions?▼

A specification template for AI-driven solutions should include YAML frontmatter with metadata, problem statements, scope definitions, interface details, and acceptance criteria to ensure clear, machine-readable guidance for development teams.

How do I structure specification documents for AI integrations in engineering contexts?▼

Structure specification documents for AI integrations by applying a defined template with naming conventions, storing files under the /spec/ directory, and enforcing clearly structured sections for consistent machine-readable requirements.

Does this specification template work for product and design requirements as well as engineering?▼

Yes, this specification template works for product, design, and engineering contexts, applying standardized front matter and structured sections to define requirements, constraints, and interfaces clearly across different development disciplines.

What is the best way to name and store AI-ready specification files?▼

The best way to store AI-ready specification files is under the /spec/ directory using a defined naming convention that matches the pattern spec-[a-z0-9-]+.md, ensuring consistent retrieval and machine-readable structure.

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