speckit-clarify

Identify underspecified areas in feature specs by asking up to five clarification questions.

1|1|Updated Nov 14, 2025

Search Tags:#workflow #planning #interactive #governance #spec #clarifications #clarify

Ready to run

npx skills add https://github.com/erikalira/python-tts --skill speckit-clarify-erikalira

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Identify underspecified areas in feature specifications by prompting up to five highly targeted clarification questions and encoding the answers back into the spec, reducing rework and misalignment.

Core Features & Use Cases

Structured ambiguity detection: scans the spec to surface missing details across functional scope, data model, UX flows, and non-functional criteria.
Interactive clarification session: asks up to five questions, records decisions under a Clarifications section, and updates the spec accordingly.
Plan integration: supports integration with speckit-like tooling to drive downstream planning and validation.

Quick Start

Run the Speckit Clarify workflow on your current spec to surface gaps and capture formal clarifications.

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 implementation?▼

To identify ambiguities in a feature specification, use a structured clarification workflow that scans for missing details across functional scope, data models, UX flows, and acceptance criteria, then records targeted decisions directly back into the spec.

How do I capture specification clarifications without losing traceability?▼

Capturing specification clarifications with traceability requires updating a dedicated Clarifications section within your spec, ensuring all decisions regarding runtime ownership and user interactions are formally persisted for governance.

What is the best way to surface underspecified areas in a planning workflow?▼

The best way to surface underspecified areas in a planning workflow is to apply an interactive clarification session that asks up to five highly targeted questions, encoding the answers to improve plan readiness and reduce rework.

Does this spec clarification process work with existing planning tooling?▼

Yes, this spec clarification process supports integration with speckit-like tooling to drive downstream planning and validation, encoding answers directly back into your repository feature specs.

Can I use targeted questions to resolve gaps in acceptance criteria and data models?▼

You can use highly targeted questions to resolve gaps in acceptance criteria and data models, as the interactive session specifically surfaces missing details across these dimensions and updates the spec accordingly.

Why does my feature spec still have missing details after initial planning?▼

Feature specs often have missing details after initial planning due to underspecified areas across runtime ownership and non-functional criteria, which require a structured ambiguity detection process to resolve before implementation.