How does it handle logical fallacies in scientific writing?

The skill identifies a wide range of fallacies, from causation errors (post hoc) and generalization errors to science-specific fallacies like the 'Galileo gambit'.

Can this skill help identify issues like p-hacking?

Yes, it includes specific capabilities for detecting statistical analysis biases such as p-hacking, outcome switching, and multiple comparison errors.

Can I use this to improve my own research design?

Yes, it can be used during the planning phase to review study protocols for internal and external validity before data collection begins.

Is this skill suitable for non-experimental research?

Absolutely. It provides evaluation criteria for observational, quasi-experimental, and cross-sectional designs, not just randomized controlled trials.

What frameworks does this skill use for evidence assessment?

The skill utilizes industry-standard frameworks including GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) and the Cochrane Risk of Bias (ROB) tools.

Scientific Critical Thinking

Name: Scientific Critical Thinking
Author: x-cmd

byx-cmd

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数据科学与机器学习

Evaluates research rigor, methodology, and statistical validity to critically analyze scientific claims and evidence quality.

This skill empowers Claude to perform high-level scientific analysis by applying established frameworks like GRADE and Cochrane Risk of Bias. It provides a systematic approach to assessing experimental designs, identifying subtle cognitive and statistical biases—such as p-hacking or confounding—and evaluating the strength of evidence across various study types. Whether you are reviewing academic papers, planning research protocols, or debunking flawed claims, this skill ensures that logical fallacies and methodological weaknesses are identified to maintain the highest standards of scientific integrity.

主要功能

01Systematic detection of cognitive, selection, and analysis biases

02Identification of logical fallacies in scientific arguments

03Rigorous methodology and experimental design critique

04Evidence quality assessment using GRADE and Cochrane frameworks

05Comprehensive statistical evaluation and pitfall identification

068 GitHub stars

使用场景

01Conducting systematic reviews and meta-analyses with standardized risk-of-bias assessments

02Evaluating data-driven scientific claims to support evidence-based decision making

03Peer-reviewing academic research papers and study protocols for methodological flaws

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add x-cmd/skill scientific-critical-thinking

For use in Claude.ai and ChatGPT

Download Skill