scientific-critical-thinking
Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scientific-critical-thinking --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Evaluates research rigor by assessing methodology, experimental design, statistical validity, biases, confounding, and evidence quality using GRADE and Cochrane ROB frameworks for critical analysis of scientific claims.
How it works
The skill provides a structured critique across: 1) Methodology Critique — evaluates study design, validity (internal, external, construct, statistical conclusion), control and blinding, and measurement quality using a stepwise checklist. 2) Bias Detection — identifies cognitive, selection, measurement, analysis biases, and confounding with guided questions. 3) Statistical Analysis Evaluation — reviews sample size/power, test appropriateness, multiple comparisons, p-values, effect sizes with confidence intervals, missing data handling, regression/model considerations, and common pitfalls. 4) Evidence Quality Assessment — ranks study design hierarchy, assesses quality within design, applies GRADE considerations, and examines convergence of evidence and contextual factors. 5) Logical Fallacy Identification — labels specific fallacies (causation, generalization, authority, statistical, structural, science-specific) with diagnostic steps. 6) Research Design Guidance — offers guidance for planning rigorous studies including question refinement, design selection, bias minimization, sample planning, measurement strategy, analysis planning, and transparency.
It instructs the agent to apply these frameworks and perform rigorous, structured evaluation of scientific claims and studies.
When to use it
Use when evaluating research methodology and experimental design, assessing statistical validity and evidence quality, identifying biases and confounding, reviewing scientific claims, conducting systematic reviews or meta-analyses, applying GRADE or Cochrane risk of bias assessments, and providing critical analysis of research papers.
What it can touch
The skill specifies allowed-tools: Read, Write, Edit, Bash. It references using a dedicated schematic generation workflow via the scientific-schematics approach, including a Python command:
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
Outputs are saved in the figures/ directory when schematics are generated.
Caveats
The skill references external reference documents for deeper principles (e.g., references/scientific_method.md, references/common_biases.md, references/statistical_pitfalls.md, references/evidence_hierarchy.md, references/logical_fallacies.md) and emphasizes applying GRADE and Cochrane ROB frameworks. No explicit outcomes are guaranteed; evaluation depends on the input studies and the checks described.
# Scientific Critical Thinking ## Overview Critical thinking is a systematic process for evaluating scientific rigor. Assess methodology, experimental design, statistical validity, biases, confounding, and evidence quality using GRADE and Cochrane ROB frameworks. Apply this skill for critical analysis of scientific claims. ## When to Use This Skill This skill should be used when: - Evaluating research methodology and experimental design - Assessing statistical validity and evidence quality - Identifying biases and confounding in studies - Reviewing scientific claims and conclusions - Conducting systematic reviews or meta-analyses - Applying GRADE or Cochrane risk of bias assessments - Providing critical analysis of research papers ## Visual Enhancement with Scientific Schematics **When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.** If your document does not already contain schematics or diagrams: - Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams - Simply describe your desired diagram in natural language - Nano Banana Pro will automatically generate, review,
- Overview
- When to Use This Skill
- Visual Enhancement with Scientific Schematics
- Core Capabilities
- 1. Methodology Critique
- 2. Bias Detection
- 3. Statistical Analysis Evaluation
- 4. Evidence Quality Assessment
- 5. Logical Fallacy Identification
- 6. Research Design Guidance
- 7. Claim Evaluation
- Application Guidelines
- General Approach
- When Providing Critique
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
What does the scientific-critical-thinking skill do?
Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scientific-critical-thinking --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.