scientific-critical-thinking

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

Updated Sep 15, 2026
One-click install
npx skills add https://github.com/mrsonord2240/openscience-specialists --skill scientific-critical-thinking-mrsonord2240
Or copy as Structured Prompt for Agent▼
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Skill: scientific-critical-thinking
Source: https://github.com/mrsonord2240/openscience-specialists/tree/main/specialists/critical-appraisal-specialist/versions/1.0.0/package/skills/scientific-critical-thinking
Command: npx skills add https://github.com/mrsonord2240/openscience-specialists --skill scientific-critical-thinking-mrsonord2240

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Researchers, reviewers, and students often struggle to systematically judge whether a study's methods, statistics, and conclusions are trustworthy. This Skill provides structured frameworks for appraising scientific rigor so critiques are consistent, specific, and proportionate rather than ad hoc. ## Core Features & Use Cases - Methodology and Design Critique: Assess internal, external, construct, and statistical conclusion validity, including randomization, blinding, and measurement quality. - Bias and Fallacy Detection: Identify cognitive, selection, measurement, and analysis biases (p-hacking, HARKing, publication bias) plus named logical fallacies in scientific arguments. - Evidence Quality Grading: Apply the evidence hierarchy and GRADE criteria, with risk-of-bias tools like Cochrane ROB, Newcastle-Ottawa, and QUADAS-2. - Use Case: When peer-reviewing a clinical trial manuscript, use this Skill to check power analysis, multiple-comparison corrections, outcome switching against the registry, and whether causal language is justified by the design. ## Quick Start Ask the AI to critically appraise the attached research paper, evaluating its methodology, statistical analysis, potential biases, and whether the conclusions are supported by the data.

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 appraise a research paper's methodology?▼

Evaluate study design appropriateness, internal validity (randomization, blinding, confounding control), external validity (sample representativeness), and measurement quality. The Skill provides structured checklists covering each validity type with specific questions to ask.

What is the GRADE system for assessing evidence quality?▼

GRADE rates evidence as high, moderate, low, or very low quality. RCTs start as high and observational studies as low, then 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?▼

Check for preregistration and compare registered outcomes to published ones, look for suspicious p-value clustering just below .05, and watch for undisclosed subgroup analyses. The Skill's bias taxonomy covers detection and mitigation strategies for these analysis biases.

Which risk of bias tool should I use for different study designs?▼

Use Cochrane ROB for randomized trials, ROBINS-I or Newcastle-Ottawa for observational studies, QUADAS-2 for diagnostic accuracy studies, and AMSTAR-2 for systematic reviews. The references detail when each tool applies.

Can this Skill design a new experiment or only critique existing studies?▼

It supports both. Beyond critique, it includes a research design guidance workflow covering question refinement, power analysis, bias minimization, measurement strategy, prespecified analysis plans, and preregistration for planning rigorous new studies.

What are the limitations of critical appraisal checklists?▼

Checklists guide judgment but cannot replace domain expertise; a well-conducted observational study can outweigh a flawed RCT. The Skill emphasizes proportionate critique, acknowledging uncertainty, and distinguishing fatal flaws from minor limitations.