speckit-clarify

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

Updated Aug 5, 2026
One-click install
npx skills add https://github.com/zhangliuliuzhang/memcached-rvv-v2 --skill speckit-clarify-zhangliuliuzhang
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-clarify
Source: https://github.com/zhangliuliuzhang/memcached-rvv-v2/tree/main/.claude/skills/speckit-clarify
Command: npx skills add https://github.com/zhangliuliuzhang/memcached-rvv-v2 --skill speckit-clarify-zhangliuliuzhang

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 detects those gaps and resolves them through structured questioning 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 targeted questions one at a time, each with a recommended option or suggested answer based on best practices. - Incremental Spec Integration: Writes each accepted answer directly into the spec under a Clarifications section and updates the relevant requirement sections, then re-validates the spec quality checklist. - Use Case: Before running implementation planning on a new feature spec, invoke this Skill to resolve open questions about security posture, scale targets, and edge-case handling so downstream tasks are unambiguous. ## Quick Start Ask the assistant to clarify the current feature spec, optionally naming specific areas such as security or performance to prioritize.

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 clarify workflow on your spec file, which scans categories like functional scope, data model, and edge cases, then asks up to 5 targeted questions. Accepted answers are written directly into a Clarifications section and the relevant spec sections.

When should I run spec clarification in a spec-driven workflow?

Run clarification after creating the feature spec and before invoking the planning step. Skipping it is possible for exploratory spikes, but it increases the risk of downstream rework during planning and task decomposition.

What project structure does spec clarification require?

It requires a spec-kit project structure with a .specify directory containing the feature spec and supporting scripts. If the spec file is missing, you must run the specify command first to generate it.

How many clarification questions can be asked per session?

A maximum of 5 questions per session, asked one at a time. Each question is either multiple-choice with a recommended option or a short answer constrained to 5 words or fewer.

Does clarification update the spec quality checklist automatically?

Yes, if a requirements checklist exists in the feature directory, it is re-validated against the updated spec. Checkbox states are toggled only when items actually change pass or fail status, and a before/after summary is reported.