scientific-critical-thinking

Evaluate research methodology, statistical validity, biases, and evidence quality using GRADE and Cochrane frameworks.

Updated Jun 18, 2026
One-click install
npx skills add https://github.com/svpfahad/RES200 --skill scientific-critical-thinking-svpfahad
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: scientific-critical-thinking
Source: https://github.com/svpfahad/RES200/tree/main/claude-scientific-writer-main/.claude/skills/scientific-critical-thinking
Command: npx skills add https://github.com/svpfahad/RES200 --skill scientific-critical-thinking-svpfahad

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Researchers, reviewers, and analysts often struggle to systematically assess whether scientific claims are supported by rigorous methodology, sound statistics, and unbiased evidence, leading to acceptance of flawed conclusions. ## Core Features & Use Cases - Methodology and Design Critique: Evaluate study design, internal/external/construct validity, randomization, blinding, and measurement quality against established standards. - Bias and Fallacy Detection: Identify cognitive, selection, measurement, and analysis biases plus logical fallacies such as p-hacking, HARKing, and correlation-causation confusion. - Evidence Quality Assessment: Apply GRADE criteria, Cochrane risk-of-bias tools, and evidence hierarchies to weigh confidence in findings. - Use Case: When reviewing a clinical trial paper claiming a treatment effect, use this Skill to check randomization quality, power analysis, multiple comparison corrections, and whether causal language is justified by the design. ## Quick Start Ask the AI to critically evaluate the methodology, statistical validity, and potential biases of an attached research paper using GRADE and Cochrane risk-of-bias frameworks.

Frequently Asked Questions about scientific-critical-thinking

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

FAQPage Schema
How do I critically evaluate a research paper's methodology?

Assess study design appropriateness, internal validity (randomization, confounding control, attrition), external validity (sample representativeness), construct validity (measurement quality), and statistical conclusion validity (power, test assumptions). The skill provides structured checklists for each dimension.

What is the GRADE system for assessing evidence quality?

GRADE rates evidence as high, moderate, low, or very low quality. RCTs start high and observational studies start low, then ratings are downgraded for risk of bias, inconsistency, indirectness, imprecision, or publication bias, and upgraded for large effects or dose-response relationships.

How do I detect p-hacking and HARKing in published studies?

Look for p-values clustering just below .05, undisclosed multiple analyses, outcome switching versus preregistration, and hypotheses presented as a priori that were formed after seeing results. Compare published outcomes against trial registrations when available.

Can observational studies ever provide strong causal evidence?

Yes, when they show large effects, dose-response relationships, consistency across populations and methods, biological plausibility, and no plausible confounders. A well-designed cohort study can outweigh a poorly conducted RCT.

What are the most common statistical pitfalls in research papers?

Common pitfalls include interpreting non-significance as no effect, ignoring multiple comparison corrections, underpowered samples, dichotomizing continuous variables, confusing correlation with causation, and failing to report effect sizes with confidence intervals.