speckit-specify

Convert natural language feature descriptions into structured implementation specs.

Updated Feb 26, 2026
One-click install
npx skills add https://github.com/tomlm/Boxcars --skill speckit-specify-tomlm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-specify
Source: https://github.com/tomlm/Boxcars/tree/main/.agents/skills/speckit-specify
Command: npx skills add https://github.com/tomlm/Boxcars --skill speckit-specify-tomlm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Turning vague feature ideas into structured, testable specifications that guide planning and delivery.

Core Features & Use Cases

  • Converts natural language feature descriptions into formal, implementable specs.
  • Validates and aligns specs with templates and required sections for consistent documentation.
  • Facilitates handoff to design, engineering, and QA with a single, comprehensive spec artifact.

Quick Start

Provide a feature description and run speckit-specify to generate a spec.

Frequently Asked Questions about speckit-specify

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

FAQPage Schema
How do I turn natural language feature descriptions into structured specs?

To turn natural language feature descriptions into structured specs, provide your text input to generate a precise, templated specification file ready for planning, implementation, and team handoff.

What is the best way to write feature specifications for engineering and QA handoff?

The best way to write feature specifications for handoff is to generate a comprehensive spec artifact that validates requirements against templates, ensuring consistent documentation across design, engineering, and QA teams.

Can I validate feature requirements against a template before planning?

Yes, you can validate feature requirements against a template before planning. The process checks for required sections and applies a built-in quality checklist to ensure documentation consistency.

How does natural language processing work for product planning specifications?

Natural language processing for product planning specifications works by analyzing your feature descriptions and outputting a precise, structured spec file with mandatory frontmatter and extension hooks for discovery.

Do I need a specific format to outline feature requirements for product teams?

You do not need a specific input format to outline feature requirements. You can provide a standard natural language feature description, and the system outputs a structured, templated specification file.

What are the limitations of automated feature specification generation?

Automated feature specification generation requires clear natural language input to function effectively. It produces a structured spec file for review, but human validation remains necessary to ensure contextual accuracy before planning.