使用方法
- 复制安装命令，在自己的智能体环境安装前先检查源码包。
- 从原始文档核对所需工具、凭据和支持的宿主。
- 说明输入材料与期望交付物，并对照来源检查输出。
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill assess-question-quality开始前需了解
- 安装不包含模型订阅、API 额度或访问文件的权限。
- 仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。
仓库原始内容
按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。
assess-question-quality
Purpose
Assess whether a research question is clear, focused, answerable, relevant, and appropriately scoped.
Input contract
yaml
required: [research_question, intended_use]
optional: [constraints, evidence_context, stakeholder_needs]
constraints: [each quality judgment requires a criterion and textual evidence]Procedure
- Evaluate clarity, focus, answerability, relevance, and scope fit.
- Identify ambiguity, hidden assumptions, and unbounded terms.
- Propose the smallest wording changes that resolve material defects.
- Return a scored or categorical assessment with unresolved issues.
Output contract
yaml
produces: [quality_assessment, criterion_evidence, revision_candidates, unresolved_issues]
delta_fields: [findings, decisions, uncertainties, open_questions]Quality gates
- Judgments cite exact question terms.
- Revision candidates preserve the intended decision or outcome.
Failure and counterexamples
Do not reward complexity as rigor or call a question answerable when its outcome cannot be observed.
Provenance map
resolved: assess-question-quality
