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speckit-clarify

Generate targeted clarification questions for feature specs and encode answers back into them.

Updated Apr 18, 2026
Search Tags:#workflow#documentation#specification#qa#clarification#questions
One-click install
npx skills add https://github.com/omerkllm/edris-antigravity --skill speckit-clarify-omerkllm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/omerkllm/edris-antigravity/tree/main/.cursor/skills/speckit-clarify
Command: npx skills add https://github.com/omerkllm/edris-antigravity --skill speckit-clarify-omerkllm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Ambiguities in feature specifications slow down development and increase rework. This Skill prompts up to five targeted clarification questions and encodes the answers back into the spec to create a traceable clarifications log.

Core Features & Use Cases

  • Generate up to five focused clarification questions to surface missing requirements.
  • Create or extend a "Clarifications" section in the active spec with a date-stamped session and captured answers.
  • Integrate answers into relevant sections (functional requirements, data models, user stories) to reduce downstream rework.

Quick Start

Ask targeted clarifying questions to surface ambiguities in the active feature spec and encode the answers back into the spec.

Frequently Asked Questions about speckit-clarify

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

FAQPage Schema
How do I identify ambiguities in a feature specification?▼

Identifying ambiguities in a feature specification involves generating up to five targeted clarification questions focusing on functional, data, and UX gaps to surface missing requirements.

What is the best way to document clarification questions in a spec-kit project?▼

The best way to document clarification questions in a spec-kit project is by creating a persistent Clarifications log under a date-stamped session directly within the active feature specification.

How do I encode clarification answers back into a specification?▼

Encoding clarification answers back into a specification involves integrating the captured responses into relevant sections like functional requirements, data models, and user stories to reduce downstream rework.

Can I generate clarification questions for functional, data, and UX gaps simultaneously?▼

Yes, generating clarification questions for functional, data, and UX gaps simultaneously is possible by applying targeted analysis to the active feature spec to produce up to five focused queries.

Why does missing specification context increase development rework?▼

Missing specification context increases development rework because underspecified areas in feature specs create ambiguities that slow down development and require costly downstream corrections.

Does this clarification workflow store answers in a testable format?▼

Yes, this clarification workflow stores answers in a structured, testable format within the active feature specification to ensure traceability and reduce missing requirements.

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