Which scientific disciplines is this skill suitable for?

While it draws from frameworks common in health sciences, its core principles of methodology, bias detection, and logical analysis are applicable across all quantitative and qualitative scientific fields.

Can this skill identify issues like p-hacking?

Yes, it specifically checks for statistical conclusion validity, including p-hacking, multiple comparison errors, and power inadequacies.

What frameworks does this skill use for evaluation?

The skill utilizes the GRADE (Grading of Recommendations, Assessment, Development and Evaluations) and Cochrane Risk of Bias (ROB) frameworks to evaluate evidence quality and study rigor.

Does it help in detecting logical fallacies?

Absolutely. It identifies common scientific fallacies such as the 'Galileo gambit', post hoc ergo propter hoc, and the Texas sharpshooter fallacy.

Scientific Critical Thinking

Name: Scientific Critical Thinking
Author: shanelindsay

byshanelindsay

•

Data Science & ML

Evaluates research rigor and scientific claims by assessing methodology, statistical validity, and potential biases using standardized frameworks.

The Scientific Critical Thinking skill provides a systematic framework for Claude to perform high-level analysis of research papers and scientific arguments. It enables the identification of methodological flaws, cognitive biases, and statistical pitfalls such as p-hacking or insufficient power. By incorporating industry-standard evidence assessment tools like GRADE and Cochrane Risk of Bias, this skill allows users to weigh the quality of conflicting evidence, detect logical fallacies, and determine the practical significance of research findings. It is an essential tool for researchers, students, and data scientists who need to audit the credibility of scientific information.

Key Features

01Comprehensive methodology and experimental design critique

02Statistical validity assessment including p-value and effect size analysis

03Logical fallacy identification in scientific discourse and conclusions

042 GitHub stars

05Systematic detection of cognitive, selection, and measurement biases

06Evidence quality grading using GRADE and Cochrane ROB frameworks

Use Cases

01Peer-reviewing academic papers and research protocols

02Conducting systematic reviews and meta-analyses

03Validating the statistical soundness of data-driven claims

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add shanelindsay/agentic-r scientific-thinking

For use in Claude.ai and ChatGPT

Download Skill