Generate structured questions and hypotheses to convert vague requests into concrete specifications.
npx skills add https://github.com/treejh/ai-agent-skills --skill vague-treejh
Please help me install this Agent Skill. Skill: vague Source: https://github.com/treejh/ai-agent-skills/tree/main/plugins/clarify/skills/vague Command: npx skills add https://github.com/treejh/ai-agent-skills --skill vague-treejh
Ambiguous requirements slow teams and derail projects. This skill automatically structures iterative clarification to transform unclear requests into precise, testable specifications.
Initiate iterative clarification by asking up to four targeted questions to turn a vague request into a concrete specification.
High-intent search queries and answers about installing and using this skill.
To clarify vague product requirements into actionable specifications, the skill generates hypotheses and batches up to four targeted questions per interaction. It guides you through selecting plausible options to transform ambiguous requests into concrete specs.
The best way to handle underspecified workflow requests is presenting plausible interpretations as selectable options rather than open questions. This hypothesis-driven approach minimizes cognitive load and routes clarifications safely through structured prompts.
You convert ambiguous user requests into testable specifications by iteratively asking clarifying questions and documenting the choices. This process produces a before and after summary and a decision log to ensure the final requirements are precise and testable.
Yes, you can batch clarifying questions to reduce cognitive load during requirements gathering. The workflow proposes up to four related questions per interaction, allowing you to efficiently resolve ambiguous requirements without overwhelming the user.
Ambiguous requirements derail projects by slowing teams down and causing misaligned execution. You prevent this by applying an iterative clarification process that converts vague requests into structured, decision-logged specifications before development begins.
team-attentionConverts vague requests into actionable specifications using structured, hypothesis-driven questioning and summaries.
wachawoDecompose project specifications into vertical slices with dependency mapping.
Hopin-incAnalyze requirement documents to generate a prioritized 20-question clarifying questionnaire.
onejaejaeInterview non-technical stakeholders to produce structured requirements in markdown.
