speckit.clarify

Identify ambiguous areas in feature specs and record answers back.

Updated Jan 8, 2026
One-click install
npx skills add https://github.com/invowk/invowk --skill speckit-clarify-invowk
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit.clarify
Source: https://github.com/invowk/invowk/tree/main/.claude/skills/speckit.clarify
Command: npx skills add https://github.com/invowk/invowk --skill speckit-clarify-invowk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify underspecified areas in feature specifications by prompting targeted clarifications and encoding answers back into the spec.

Core Features & Use Cases

  • Structured ambiguity scan across functional scope, domain & data model, interaction & UX flow, non-functional attributes, and integration dependencies.
  • Interactive session that generates a prioritized queue of clarifying questions (max 5) and records accepted answers back into the spec.
  • Automatic integration of clarifications into Functional Requirements, Data Model, User Stories, Non-Functional Attributes, and Edge Cases, with versioned updates.

Quick Start

Run speckit.clarify on your feature spec to begin a guided clarification session.

Frequently Asked Questions about speckit.clarify

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

FAQPage Schema
How do I identify underspecified areas in a feature specification?

You can identify underspecified areas in a feature specification by running an interactive clarification session that scans functional scope, data models, and edge cases to generate a prioritized queue of up to five targeted questions.

How do I clarify feature requirements and record answers back into the spec?

To clarify feature requirements and record answers, you accept responses during an interactive clarification session. The tool automatically integrates these accepted answers back into the Functional Requirements, Data Model, User Stories, and Edge Cases sections with versioned updates.

What is the best way to reduce downstream rework when writing feature specs?

The best way to reduce downstream rework when writing feature specs is to apply a structured taxonomy that prompts targeted clarifications across non-functional attributes and integration dependencies, ensuring ambiguities are resolved before development begins.

Do I need an existing spec file to run a feature specification clarification session?

Yes, you need an existing spec file. The clarification process requires a feature specification present at the repository path to function, as it uses this document as the base for generating questions and recording versioned updates.

Can I limit the number of clarifying questions generated for my feature spec?

Yes, the interactive clarification session generates a prioritized queue of a maximum of five targeted questions, ensuring the feature spec clarification process remains focused and manageable without overwhelming the user.