speckit-specify

Generate and validate feature specifications from natural language prompts.

Updated Apr 26, 2026
One-click install
npx skills add https://github.com/victorevh/orbitarium-engine-sdd --skill speckit-specify-victorevh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-specify
Source: https://github.com/victorevh/orbitarium-engine-sdd/tree/main/.cursor/skills/speckit-specify
Command: npx skills add https://github.com/victorevh/orbitarium-engine-sdd --skill speckit-specify-victorevh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Create or update detailed feature specifications from natural-language feature descriptions, reducing ambiguity and speeding up planning.

Core Features & Use Cases

  • Generate structured specs with sections for user stories, acceptance criteria, data assumptions, and constraints.
  • Validate spec quality with built-in checklists and produce a ready-to-plan spec directory and template.
  • Support extension hooks for pre/post-spec actions and optional resources to enhance the spec.

Quick Start

Generate a complete, ready-to-plan feature specification from a natural-language description.

Frequently Asked Questions about speckit-specify

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

FAQPage Schema
How do I convert natural language prompts into ready-to-plan feature specifications?

Feature specifications are generated and validated from natural language prompts by applying a templated structure with sections for user stories, requirements, success criteria, assumptions, and risk assessment to produce ready-to-plan documents.

What sections should a structured feature specification include for product planning?

A structured feature specification should include sections for user stories, acceptance criteria, requirements, success criteria, data assumptions, constraints, and risk assessment to ensure consistent formats and traceable decisions.

How do I validate spec quality and reduce ambiguity during requirements planning?

Spec quality is validated using built-in checklists that enforce a templated structure, reducing ambiguity by ensuring every natural-language feature description includes traceable decisions, assumptions, and constraints before planning.

Can I generate a ready-to-plan spec directory from a simple feature description?

Yes, a complete ready-to-plan spec directory and template can be generated directly from a natural-language feature description, producing structured documents with user stories, acceptance criteria, and constraints.

Does this feature specification approach support extension hooks for custom pre and post spec actions?

Yes, extension hooks for pre-spec and post-spec actions are supported, allowing optional resources to enhance the generated feature specification and integrate custom actions into the product planning workflow.

When should I not use automated feature specification generation from natural language?

Automated feature specification generation is not ideal for product planning workflows that do not require consistent formats, traceable decisions, or repeatable spec templates, as its value relies on enforcing a strict templated structure.