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speckit-clarify

Identify underspecified areas in feature specifications and record clarifications.

1.0k|514|Updated Jan 21, 2026
Search Tags:#specification#requirements#clarification#acceptance criteria#yaml#spec-kit
One-click install
npx skills add https://github.com/unipds-engenharia-de-ia-aplicada/engenharia-de-software-com-ia-aplicada --skill speckit-clarify-unipds-engenharia-de-ia-aplicada
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/unipds-engenharia-de-ia-aplicada/engenharia-de-software-com-ia-aplicada/tree/main/lives/2026-05-27/001-pos-live/.claude/skills/speckit-clarify
Command: npx skills add https://github.com/unipds-engenharia-de-ia-aplicada/engenharia-de-software-com-ia-aplicada --skill speckit-clarify-unipds-engenharia-de-ia-aplicada

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes ambiguity from feature specifications by asking targeted clarification questions before planning begins.

Core Features & Use Cases

  • Targeted Clarification: Identifies the highest-impact gaps in scope, data, UX, integrations, edge cases, and non-functional requirements.
  • Spec Editing: Records answers directly into the active specification so the document stays current and actionable.
  • Workflow Awareness: Checks prerequisite project structure and supports extension hooks around clarification steps when present.
  • Use Case: A product team has a partially written feature spec and needs a short, focused clarification pass before starting planning or implementation.

Quick Start

Use the speckit-clarify skill to find the most important ambiguities in the current spec and write concise answers back into the document.

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 before planning begins?▼

Feature specification clarification identifies underspecified areas across scope, data, UX, and edge cases, converting them into targeted one-question-at-a-time refinement prompts before planning starts.

How do I refine vague acceptance criteria in a YAML spec-kit project?▼

Refining vague acceptance criteria in a spec-kit project targets the highest-impact gaps in functional scope and non-functional requirements, writing concise answers directly back into the active YAML specification.

Do I need a .specify directory to clarify feature requirements?▼

Yes, requirement clarification requires a valid .specify directory to function. It checks this prerequisite project structure to enable incremental spec updates and optional extension-hook execution.

What's the best way to resolve underspecified data models and integration flows?▼

Resolving underspecified data models and integration flows involves asking focused clarification questions that cover functional scope, edge cases, and integrations, recording answers back into the active specification document.

Can I run custom workflow hooks before and after clarifying specifications?▼

Yes, specification clarification supports optional extension-hook execution for before and after clarification workflows when present, allowing custom automation around the targeted refinement process.

Why does my feature spec clarification pass keep missing non-functional requirements?▼

Specification clarification passes miss non-functional requirements when gaps remain underspecified. The targeted clarification process explicitly identifies and covers non-functional requirements alongside UX flow and edge cases.

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