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speckit-clarify

Identify underspecified areas in feature specs and resolve them through targeted questions.

Updated Jun 14, 2026
Search Tags:#specification#requirements#clarification#spec-kit#product-management#acceptance-criteria#feature-planning
One-click install
npx skills add https://github.com/basmawebinfo-hub/lover-diet-center --skill speckit-clarify-basmawebinfo-hub
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/basmawebinfo-hub/lover-diet-center/tree/main/.agents/skills/speckit-clarify
Command: npx skills add https://github.com/basmawebinfo-hub/lover-diet-center --skill speckit-clarify-basmawebinfo-hub

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill reduces ambiguity in active feature specifications by identifying missing decisions, asking a small number of high-impact clarification questions, and writing the accepted answers back into the spec.

Core Features & Use Cases

  • Ambiguity Detection: Scans a feature spec across functional scope, data model, UX, non-functional requirements, integrations, edge cases, constraints, and terminology.
  • Interactive Clarification Loop: Asks up to five targeted questions one at a time, with recommended answers or suggested options to speed up decision-making.
  • Spec Updating & Validation: Inserts clarifications into the correct spec sections, preserves structure, re-validates any requirements checklist, and reports remaining gaps.
  • Use Case: When a product team has drafted a feature spec but key details like user roles, acceptance criteria, or failure behavior are still unclear, this Skill helps finalize the spec before planning and implementation begin.

Quick Start

Ask the AI to run the speckit-clarify skill on your current spec so it can identify the most important unresolved requirements and guide you through answering them.

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 requirements in a feature spec?▼

To identify underspecified requirements in a feature spec, scan the document across functional scope, data model, UX, non-functional requirements, integrations, edge cases, constraints, and terminology to detect missing decisions and ambiguity.

What is the best way to clarify vague product specifications before planning?▼

The best way to clarify vague product specifications is using an interactive clarification loop that asks up to five targeted questions sequentially, provides recommended answers or suggested options, and writes accepted answers directly back into the spec.

How do I update and revalidate a requirements checklist after adding clarifications to a spec?▼

To update and revalidate a requirements checklist after adding clarifications, insert the resolved answers into the correct spec sections, preserve the existing structure, re-validate the checklist, and generate a report detailing any remaining gaps.

Does spec-kit clarification work with my existing .specify directory and governance documents?▼

Yes, spec-kit clarification works with workflows using a .specify directory, feature spec files, optional governance documents, and requirements checklists, applying taxonomy-based ambiguity analysis before planning begins.

What specific areas of a feature specification are analyzed for ambiguity?▼

Ambiguity analysis scans a feature specification across functional scope, data model, UX, non-functional requirements, integrations, edge cases, constraints, and terminology to pinpoint unresolved decisions requiring targeted clarification.

Can I use extension hooks before and after clarifying feature spec requirements?▼

Yes, you can use optional pre- and post-clarification extension hooks to execute custom logic before and after the interactive clarification loop resolves underspecified areas within your feature spec.

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