How does the 'vague' skill differ from normal chatting?

Unlike standard conversation, this skill uses a structured protocol that forces specific decisions through multiple-choice hypotheses, ensuring no ambiguity remains in the scope or success criteria.

Can I limit the number of questions asked?

Yes, you can use the --max-iterations flag to control how many rounds of clarification the skill performs before finalizing the specification.

What happens when the clarification loop finishes?

The skill generates a 'Requirement Clarification Summary' that maps out the final goal, constraints, and all decisions made, followed by a completion promise to signal it's ready for implementation.

When should I use this skill versus the 'unknown' skill?

Use 'vague' for clarifying underspecified requirements. Use 'unknown' specifically for identifying strategy blind spots or missing information in project planning.

Requirement Clarifier

Name: Requirement Clarifier
Author: october-academy

byoctober-academy

0•

Collaboration Tools

Transforms ambiguous requests into precise, actionable technical specifications through structured, hypothesis-driven questioning.

The Vague skill is a specialized tool for Claude Code designed to eliminate ambiguity at the start of the development process. When faced with underspecified requests like 'add a login feature' or 'fix the performance,' this skill initiates an iterative refinement loop that presents specific hypotheses as choices rather than asking open-ended questions. By guiding users through critical decisions regarding scope, constraints, and success criteria, it produces a clear 'Before and After' summary that ensures the final implementation aligns perfectly with user intent.

Key Features

01Iterative refinement loops with configurable maximum iterations (default 3)

02Multi-language support for triggers in both English and Korean

030 GitHub stars

04Comprehensive summary generation including goal, scope, and success criteria

05Hypothesis-driven questioning using multiple-choice options to minimize cognitive load

06Local state tracking in markdown for transparency and session persistence

Use Cases

01Determining the scope and constraints for ambiguous performance optimization requests

02Refining incomplete bug reports into reproducible technical tasks

03Converting high-level feature requests into detailed implementation specs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add october-academy/agent-plugins vague

For use in Claude.ai and ChatGPT

Key Features

01Iterative refinement loops with configurable maximum iterations (default 3)

02Multi-language support for triggers in both English and Korean

030 GitHub stars

04Comprehensive summary generation including goal, scope, and success criteria

05Hypothesis-driven questioning using multiple-choice options to minimize cognitive load

06Local state tracking in markdown for transparency and session persistence

Use Cases

01Determining the scope and constraints for ambiguous performance optimization requests

02Refining incomplete bug reports into reproducible technical tasks

03Converting high-level feature requests into detailed implementation specs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add october-academy/agent-plugins vague

For use in Claude.ai and ChatGPT