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scientific-critical-thinking

Evaluate scientific claims by critiquing methodology, bias, and statistical reasoning.

4|Updated Mar 2, 2026
Search Tags:#critical thinking#bias detection#research design#peer review#logical fallacies#statistical validity#evidence grading
One-click install
npx skills add https://github.com/shushuzn/Rairos --skill scientific-critical-thinking-shushuzn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scientific-critical-thinking
Source: https://github.com/shushuzn/Rairos/tree/main/skills/scientific-critical-thinking
Command: npx skills add https://github.com/shushuzn/Rairos --skill scientific-critical-thinking-shushuzn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

It helps you evaluate scientific claims by systematically checking experimental design quality, sources of bias, statistical validity, and overall evidence strength so your conclusions match what the data actually support.

Core Features & Use Cases

  • Methodology critique: Assess internal/external/construct validity, blinding and controls, measurement quality, and statistical conclusion validity.
  • Bias detection: Identify cognitive, selection, measurement, analysis, reporting, and confounding threats that can distort results.
  • Statistical analysis evaluation: Check power/sample size, test appropriateness, multiple comparisons, p-value interpretation, effect sizes/CI, missing data handling, and modeling pitfalls.
  • Evidence quality assessment: Apply evidence hierarchies and GRADE-style reasoning (including downgrades/upgrades) and weigh convergence across studies.
  • Logical fallacy identification & claim evaluation: Detect causation/logic errors and flag red-line reasoning gaps in claims and conclusions.
  • Research design guidance: Provide actionable checklists for rigorous study planning (question formulation through analysis transparency).

Quick Start

Use the scientific-critical-thinking skill to evaluate a research paper by asking for a structured critique that covers validity threats, bias risks, statistical soundness, evidence strength (GRADE-style), and specific, actionable recommendations.

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 study methodology and assess bias in a research paper?▼

Evaluating study methodology involves critiquing internal, external, and construct validity, blinding, controls, and measurement quality to identify selection, measurement, and confounding bias threats that distort results.

What is the best way to grade evidence strength for scientific claims?▼

Grading evidence strength uses GRADE-style reasoning to weigh convergence across studies, applying evidence hierarchies with appropriate downgrades or upgrades to produce a proportionate, actionable assessment of conclusions.

How do I check statistical validity and detect p-hacking in experimental results?▼

Checking statistical validity requires evaluating power, sample size, test appropriateness, multiple comparisons, effect sizes, confidence intervals, and missing data handling to detect red flags like p-hacking and selective reporting.

Can I use this critical thinking approach to review observational studies and experiments?▼

Yes, this critical thinking approach supports evidence grading across design types, allowing you to review both experiments and observational studies by identifying logical fallacies, causation errors, and reasoning gaps in claims.

What frameworks are used to identify risk of bias and logical fallacies in scientific literature?▼

Frameworks like GRADE and risk-of-bias tools are applied to systematically identify cognitive and analysis threats, detect causation errors, and flag red-line reasoning gaps in scientific claims, abstracts, and conclusions.

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