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scientific-critical-thinking

Assess scientific claims and evidence quality using structured critical appraisal frameworks.

74|5|Updated Dec 10, 2025
Search Tags:#bias detection#research evaluation#experimental design#logical fallacies#evidence grading#statistical pitfalls#scientific thinking
One-click install
npx skills add https://github.com/dralkh/seerai --skill scientific-critical-thinking-dralkh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-critical-thinking
Source: https://github.com/dralkh/seerai/tree/main/skills/scientific-critical-thinking
Command: npx skills add https://github.com/dralkh/seerai --skill scientific-critical-thinking-dralkh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you judge whether a scientific claim is actually supported by the evidence, instead of being driven by weak methods, bias, or overconfident interpretation.

Core Features & Use Cases

  • Methodology critique: Check whether a study design can support the conclusion it makes.
  • Bias and confounding detection: Identify selection bias, measurement bias, p-hacking, HARKing, and alternative explanations.
  • Evidence quality assessment: Apply GRADE-style thinking, risk-of-bias appraisal, and study hierarchy logic.
  • Logical claim review: Spot fallacies such as correlation-causation errors, cherry-picking, and overgeneralization.
  • Research planning guidance: Improve a proposed study by strengthening sampling, controls, blinding, measurement, and analysis planning.
  • Use case: A researcher can use this Skill to review a manuscript, flag the weakest parts of the argument, and rewrite conclusions so they match the data.

Quick Start

Use this Skill to evaluate the methods, biases, statistics, and conclusions of the attached research paper.

Frequently Asked Questions about scientific-critical-thinking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate research claims for bias and methodological flaws?▼

To evaluate research claims, assess study design limitations, identify selection bias, detect p-hacking, and check for unsupported conclusions using structured critical appraisal frameworks and evidence grading.

What is the best way to detect logical fallacies in a scientific paper?▼

Detecting logical fallacies in a scientific paper requires reviewing claims for correlation-causation errors, cherry-picking, and overgeneralization to ensure the conclusions strictly match the presented data.

How do I apply GRADE-style evidence grading to a systematic review?▼

Apply GRADE-style evidence grading by appraising the risk of bias, evaluating study hierarchy logic, and checking statistical errors to determine the validity and reliability of the systematic review conclusions.

Can I use critical appraisal to improve an experimental design before data collection?▼

Yes, applying critical appraisal to an experimental protocol improves research planning by strengthening sampling methods, controls, blinding, measurement procedures, and statistical analysis planning before collection.

What are common statistical pitfalls to check for during research evaluation?▼

Common statistical pitfalls during research evaluation include p-hacking, HARKing, measurement bias, and confounding factors that can lead to overconfident interpretation and unsupported scientific conclusions.

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