What does Speckit Clarify actually do?

It analyzes your current feature specification for missing details or contradictions and asks up to 5 targeted questions to fill those gaps, then writes the answers back into your spec file.

Can I limit the number of questions asked?

The skill is hard-coded to ask no more than 5 questions per session to ensure efficiency and avoid 'analysis paralysis'.

Is it required before using speckit-plan?

While not strictly mandatory, it is highly recommended to run speckit-clarify first to ensure the plan is based on clear, unambiguous requirements.

Where are the clarified details saved?

Clarifications are saved directly into your FEATURE_SPEC file, typically under a dedicated 'Clarifications' section and integrated into the relevant technical sub-sections.

Does it support English and Chinese?

The 'zh' version is optimized for Chinese-speaking users and projects, providing prompts and processing inputs in Chinese while maintaining technical consistency.

Speckit Requirement Clarifier (ZH)

Name: Speckit Requirement Clarifier (ZH)
Author: forztf

byforztf

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生産性とワークフロー

Eliminates technical ambiguity in functional specifications through targeted interactive questioning and automated documentation updates.

概要

Speckit Clarify (ZH) is a specialized tool for Spec-driven Development (SDD) that identifies gaps in active feature specifications. It scans for missing details in data models, user flows, and non-functional requirements, then engages the user in a brief, high-impact dialogue of up to five questions. By providing intelligent recommendations and automatically encoding answers back into the project's specification files, it ensures a clear, actionable foundation before moving to the implementation or planning phase, significantly reducing the risk of downstream rework.

主な機能

Incremental, atomic updates to Markdown specification files
Automated structural scanning for functional and non-functional ambiguities
Smart recommendations for ambiguity resolution based on industry best practices
2 GitHub stars
Interactive Q&A loop with a maximum of 5 high-impact questions
Structured session logging for historical tracking of requirement decisions

ユースケース

Translating vague project goals into measurable technical constraints
Standardizing data models and edge cases across a development team
Refining a draft specification before generating an implementation plan

概要

主な機能

Incremental, atomic updates to Markdown specification files
Automated structural scanning for functional and non-functional ambiguities
Smart recommendations for ambiguity resolution based on industry best practices
2 GitHub stars
Interactive Q&A loop with a maximum of 5 high-impact questions
Structured session logging for historical tracking of requirement decisions

ユースケース

Translating vague project goals into measurable technical constraints
Standardizing data models and edge cases across a development team
Refining a draft specification before generating an implementation plan