speckit-clarify

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

Updated Dec 12, 2024
One-click install
npx skills add https://github.com/kipariss1/czech_out_auto_bot --skill speckit-clarify-kipariss1
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/kipariss1/czech_out_auto_bot/tree/main/.claude/skills/speckit-clarify
Command: npx skills add https://github.com/kipariss1/czech_out_auto_bot --skill speckit-clarify-kipariss1

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Feature specifications often contain ambiguities, missing decisions, and vague requirements that cause rework during planning and implementation. This Skill systematically scans a spec for gaps and resolves them through focused clarification questions before planning begins. ## Core Features & Use Cases - Structured Ambiguity Scan: Evaluates the spec across a taxonomy of categories including functional scope, data model, non-functional requirements, edge cases, and terminology. - Interactive Questioning Loop: Asks up to 5 high-impact questions one at a time, each with a recommended answer and multiple-choice or short-answer format. - Incremental Spec Updates: Writes each accepted answer back into the spec under a Clarifications section and updates the relevant requirement sections, then re-validates the spec quality checklist. - Use Case: Before running /speckit-plan on a new feature, run this Skill to resolve open questions about security posture, data constraints, or acceptance criteria so the plan is built on solid requirements. ## Quick Start Ask the assistant to run the speckit-clarify skill to review the current feature spec and clarify any ambiguous requirements before planning.

Frequently Asked Questions about speckit-clarify

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

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

Run the speckit-clarify skill in a spec-kit project. It scans the active feature spec across categories like functional scope, data model, and edge cases, then asks up to 5 targeted questions and writes the answers directly into the spec file.

When should I run spec clarification in spec-kit?▼

Run clarification after /speckit-specify and before /speckit-plan. Resolving ambiguities at this stage reduces downstream rework risk in planning, task decomposition, and acceptance test design.

Does speckit-clarify require a specific project structure?▼

Yes, it requires a spec-kit project with a .specify directory. It runs check-prerequisites.sh to locate the feature spec and optionally loads .specify/memory/constitution.md for project governance constraints.

How many clarification questions does the skill ask?▼

It asks a maximum of 5 questions per session, presented one at a time. Questions are prioritized by impact and uncertainty, and each must be answerable with a multiple-choice selection or a short answer of five words or fewer.

What happens to the spec after clarification answers are given?▼

Each accepted answer is appended to a Clarifications section with a dated session heading and applied to the relevant spec sections. The spec quality checklist at checklists/requirements.md is then re-validated against the updated spec.