What kind of interactive options does it provide?

It provides buttons and multi-select lists for technology stacks (React, Vue, Node.js), project features (Auth, CRUD, WebSockets), and optimization types.

Will this skill interrupt my workflow if my prompt is already detailed?

No. The skill includes 'When Not' criteria; if your instructions are clear and detailed, Claude will proceed directly to the task without asking unnecessary questions.

How does Prompt Clarifier identify ambiguity?

It analyzes prompts for short word counts, lack of context, vague verbs like 'optimize,' or missing technical specifications such as tech stack preferences.

Does this work with custom project hooks?

Yes, it is designed to work with the UserPromptSubmit hook and can be triggered by specific internal indicators to ensure context is preserved.

Prompt Clarifier

Name: Prompt Clarifier
Author: physics91

byphysics91

生产力与工作流

Detects ambiguous instructions and uses interactive questions to resolve vague requirements before starting tasks.

关于

The Prompt Clarifier skill acts as an intelligent requirement-gathering layer for Claude Code, identifying vague or underspecified prompts before execution begins. By monitoring for short instructions, missing tech stacks, and ambiguous verbs like 'optimize' or 'fix', it triggers an interactive clarification loop using the AskUserQuestion interface. This ensures that Claude has the exact context, feature list, and performance targets needed to produce high-quality code, saving time and reducing the need for iterative corrections.

主要功能

Interactive multiple-choice selections for tech stack and feature scoping
Automatic ambiguity detection for vague or context-light prompts
0 GitHub stars
Targeted clarification patterns for code optimization and bug fixes
Support for multi-select options in complex project requirements
Seamless integration with Claude Code hooks for automated activation

使用场景

Resolving ambiguous file references and missing paths in maintenance tasks
Narrowing down optimization goals between performance, memory, or readability
Turning high-level requests like 'build a website' into defined technical specifications

关于

主要功能

Interactive multiple-choice selections for tech stack and feature scoping
Automatic ambiguity detection for vague or context-light prompts
0 GitHub stars
Targeted clarification patterns for code optimization and bug fixes
Support for multi-select options in complex project requirements
Seamless integration with Claude Code hooks for automated activation

使用场景

Resolving ambiguous file references and missing paths in maintenance tasks
Narrowing down optimization goals between performance, memory, or readability
Turning high-level requests like 'build a website' into defined technical specifications