speckit-clarify

Generate up to five targeted clarification questions for underspecified feature specs.

Updated Apr 6, 2026
One-click install
npx skills add https://github.com/linhnguyen125/ClaudeCodeWithSpecKit --skill speckit-clarify-linhnguyen125
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/linhnguyen125/ClaudeCodeWithSpecKit/tree/main/.claude/skills/speckit-clarify
Command: npx skills add https://github.com/linhnguyen125/ClaudeCodeWithSpecKit --skill speckit-clarify-linhnguyen125

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill identifies ambiguous, missing, or underspecified decisions in a feature specification and reduces downstream rework by generating targeted clarification questions and encoding accepted answers directly into the spec.

Core Features & Use Cases

  • Automated Ambiguity Detection: Scans a spec for coverage gaps across functional scope, domain/model, UX flows, non-functional requirements, integrations, edge cases, constraints, and terminology.
  • Prioritized Clarification Workflow: Produces a prioritized queue of up to five answer-constrained questions and runs an interactive loop to collect, validate, and integrate responses.
  • Spec Integration & Validation: Appends a dated Clarifications session to the spec, incrementally applies each accepted answer to the appropriate section, validates consistency, and saves the updated FEATURE_SPEC.
  • Use Case: Run this when finalizing a feature spec in a spec-kit repository to avoid misaligned architecture or acceptance tests before planning.

Quick Start

Run the clarification workflow on the active feature spec in your spec-kit repo by invoking the assistant to generate and integrate up to five targeted questions.

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 development?

To identify ambiguities in a feature specification, scan the spec for coverage gaps across functional scope, data models, UX flows, edge cases, and constraints, then generate targeted clarification questions to resolve them.

What is the best way to clarify underspecified requirements in a spec-kit repository?

The best way to clarify underspecified requirements in a spec-kit repository is to run an interactive workflow that produces up to five prioritized questions, collects validated responses, and appends them directly to the spec file.

Do I need a .specify directory to run the spec clarification workflow?

Yes, you need a spec-kit repository with a .specify directory to run the spec clarification workflow, as it requires reading FEATURE_SPEC and FEATURE_DIR from the check-prerequisites script to function properly.

When should I generate clarification questions for my feature spec?

You should generate clarification questions when finalizing a feature spec to avoid misaligned architecture or acceptance tests, ensuring ambiguous decisions are encoded before planning begins.

How does the specification clarification process update the spec file?

The specification clarification process updates the spec file by appending a dated Clarifications session, incrementally applying accepted answers to appropriate sections, validating consistency, and saving the updated FEATURE_SPEC.

Can I automate the detection of missing non-functional requirements in my spec?

Yes, you can automate the detection of missing non-functional requirements by scanning the specification for coverage gaps across integrations, constraints, terminology, and edge cases to prioritize areas needing clarification.