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Scientific Critical Thinking

技能 已验证 活跃

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.

目的

To empower AI agents to critically evaluate scientific claims and evidence, identify research flaws, and assess the quality and validity of scientific studies.

功能

  • Evaluate scientific claims and evidence quality
  • Assess experimental design validity
  • Identify biases and confounders
  • Apply evidence grading frameworks (GRADE, Cochrane)
  • Teach critical analysis of research

使用场景

  • Evaluating research methodology and experimental design
  • Assessing statistical validity and evidence quality
  • Identifying biases and confounding in studies
  • Reviewing scientific claims and conclusions

非目标

  • Performing formal peer review writing (suggests using 'peer-review' skill)
  • Generating scientific papers (focus is on evaluation)
  • Executing scientific experiments directly (focus is on analysis of claims)

工作流

  1. User prompts skill to evaluate a scientific claim or study.
  2. Skill analyzes the claim/study based on provided information and bundled references.
  3. Skill identifies methodological flaws, biases, statistical issues, or logical fallacies.
  4. Skill assesses evidence quality using frameworks like GRADE or Cochrane.
  5. Skill provides a structured critique, highlighting strengths, weaknesses, and evidence for/against the claim.

安装

npx skills add K-Dense-AI/claude-scientific-skills

通过 npx 运行 Vercel skills CLI(skills.sh)— 需要本地安装 Node.js,以及至少一个兼容 skills 的智能体(Claude Code、Cursor、Codex 等)。前提是仓库遵循 agentskills.io 格式。

质量评分

已验证
99 /100
1 day ago 分析

信任信号

最近提交3 days ago
星标21k
许可证MIT
状态
查看源代码

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