smartspec

Generates AI-ready requirements specifications in BMAD Story Format and Spec-Kit outputs.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/gowerlin/SmartSpec --skill smartspec
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: smartspec
Source: https://github.com/gowerlin/SmartSpec/tree/main/claude-skill
Command: npx skills add https://github.com/gowerlin/SmartSpec --skill smartspec

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill transforms vague product ideas into professional, AI-ready specification documents, eliminating manual drafting and ensuring clarity for AI development tools. It bridges the gap between non-technical users and AI developers, allowing you to rest while AI handles the complexity.

Core Features & Use Cases

  • Intelligent Guided Conversations: Engages users in a multi-round dialogue to clarify requirements, identify gaps, and gather comprehensive details, ensuring no critical information is missed.
  • AI-Ready Output: Generates structured specifications in both BMAD Story Format and GitHub Spec-Kit Format, directly usable by AI development agents like /BMad:dev or /speckit.implement.
  • Quality Assurance: Automatically validates generated documents against strict AI-Ready quality standards (≥95% score) for completeness, executability, and consistency, guaranteeing high-quality output.
  • Use Case: You have a rough concept for a new mobile app. Instead of spending days writing a PRD, use SmartSpec to interactively refine your idea. It will ask targeted questions, fill in the blanks, and then output a detailed, AI-ready specification that your AI developer can immediately use to start coding.

Quick Start

Use the smartspec skill to generate a BMAD Story for my new app idea: 'I want an app to track my daily expenses and show me charts.'

Frequently Asked Questions about smartspec

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

FAQPage Schema
How do I generate AI-ready specification documents from rough product ideas?

SmartSpec transforms vague concepts into structured AI-ready specifications through guided conversation. It asks clarifying questions over multiple rounds, identifies requirement gaps, and outputs specifications in BMAD Story Format and GitHub Spec-Kit Format ready for AI development agents to execute.

What's the best way to convert user stories and requirements into formats AI developers can use?

SmartSpec automates this conversion by analyzing your initial idea, engaging in targeted dialogue to fill gaps, then producing dual-format outputs—BMAD Story Format and Spec-Kit—validated against AI-ready quality standards (≥95% score) for completeness and executability.

Can I use SmartSpec to create specifications suitable for Claude development workflows?

Yes. SmartSpec generates specifications explicitly designed for Claude-powered projects and AI development agents. Output integrates directly with tools like `/BMad:dev` and `/speckit.implement`, eliminating manual spec drafting for AI-driven development.

How do I ensure generated specifications meet quality standards for AI development?

SmartSpec includes built-in quality assurance that validates generated documents against strict AI-ready standards, guaranteeing ≥95% scores for completeness, consistency, and executability before delivery to development agents.

What information do I need to provide to get a complete specification?

You start with a rough concept or idea. SmartSpec conducts 3–5 interactive clarification rounds, asking targeted questions to extract functional requirements, scope, constraints, and edge cases, requiring only your initial description and responses to its guided prompts.

Does SmartSpec support requirements in languages other than English?

SmartSpec includes language support beyond English, enabling specification generation for Claude projects across multiple languages while maintaining AI-ready output formats and quality validation standards.