speckit-clarify

Identifies underspecified areas in feature specs and records up to five targeted clarification answers.

120|25|Updated Jan 5, 2026

Search Tags:#workflow #specification #spec #questions #clarifications #clarify

Ready to run

npx skills add https://github.com/dceoy/speckit-agent-skills --skill speckit-clarify-dceoy

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/dceoy/speckit-agent-skills/tree/main/skills/speckit-clarify
Command: npx skills add https://github.com/dceoy/speckit-agent-skills --skill speckit-clarify-dceoy

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Underspecified feature specs are identified and clarified by posing up to five targeted questions, reducing ambiguity before planning.

Core Features & Use Cases

Interactive ambiguity detection across functional, data, UX, and non-functional aspects.
Structured question generation with clear acceptance criteria for downstream planning.
Automatic integration of answers into the spec to maintain a single source of truth.

Quick Start

Run the speckit-clarify workflow to pose up to five targeted questions and integrate the answers 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 clarify ambiguous feature specs before planning?▼

You clarify ambiguous feature specs by generating up to five targeted questions that identify missing constraints and edge cases. The workflow detects underspecified areas across functional, data, UX, and non-functional dimensions to reduce ambiguity before planning.

What is the best way to identify missing acceptance criteria in a specification?▼

Identifying missing acceptance criteria involves applying a structured taxonomy for ambiguity to prompt focused clarification questions. This process highlights concrete constraints and edge cases required for downstream planning.

How do I keep a single source of truth when adding clarifications to a spec?▼

Keeping a single source of truth requires updating the specification after each accepted answer. The workflow automatically integrates responses directly into the spec to ensure all constraints and acceptance criteria remain centralized.

Can I use structured questions to cover edge cases across functional and UX dimensions?▼

Yes, you can use structured questions to cover edge cases across functional, data, UX, and non-functional dimensions. The workflow prioritizes these clarification questions by impact to address the most critical ambiguities first.

What happens if a feature spec has more than five underspecified areas?▼

If a feature spec has more than five underspecified areas, the workflow poses a maximum of five targeted questions. It prioritizes these questions by impact to resolve the most critical ambiguities and constraints first.

Does clarifying a specification require any external dependencies?▼

Clarifying a specification does not require any external dependencies. The workflow operates independently to identify ambiguities, generate acceptance criteria, and update the spec without needing additional tools or components.