scientific-critical-thinking

Name: scientific-critical-thinking
Author: LeonChaoX

698stars61forks

How to install scientific-critical-thinking?

leonchaox/qinyan-academic-skills/scientific-critical-thinking

$npx -y skills add LeonChaoX/qinyan-academic-skills --skill scientific-critical-thinking

Installs into the current project.

Summary

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identi

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SKILL.md

1	# Scientific Critical Thinking
2
3	## Overview
4
5	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.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Evaluating research methodology and experimental design
11	- Assessing statistical validity and evidence quality
12	- Identifying biases and confounding in studies
13	- Reviewing scientific claims and conclusions
14	- Conducting systematic reviews or meta-analyses
15	- Applying GRADE or Cochrane risk of bias assessments
16	- Providing critical analysis of research papers
17
18	## Visual Enhancement with Scientific Schematics
19
20	When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
21
22	If your document does not already contain schematics or diagrams:
23	- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
24	- Simply describe your desired diagram in natural language
25	- Nano Banana Pro will automatically generate, review, and refine the schematic
26
27	For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
28
29	How to generate schematics:
30	```bash
31	python scripts/generate_schematic.py "your diagram description" -o figures/output.png
32	```
33
34	The AI will automatically:
35	- Create publication-quality images with proper formatting
36	- Review and refine through multiple iterations
37	- Ensure accessibility (colorblind-friendly, high contrast)
38	- Save outputs in the figures/ directory
39
40	When to add schematics:
41	- Critical thinking framework diagrams
42	- Bias identification decision trees
43	- Evidence quality assessment flowcharts
44	- GRADE assessment methodology diagrams
45	- Risk of bias evaluation frameworks
46	- Validity assessment visualizations
47	- Any complex concept that benefits from visualization
48
49	For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
50
51	---
52
53	## Core Capabilities
54
55	### 1. Methodology Critique
56
57	Evaluate research methodology for rigor, validity, and potential flaws.
58
59	Apply when:
60	- Reviewing research papers
61	- Assessing experimental designs
62	- Evaluating study protocols
63	- Planning new research
64
65	Evaluation framework:
66
67	1. Study Design Assessment
68	- Is the design appropriate for the research question?
69	- Can the design support causal claims being made?
70	- Are comparison groups appropriate and adequate?
71	- Consider whether experimental, quasi-experimental, or observational design is justified
72
73	2. Validity Analysis
74	- Internal validity: Can we trust the causal inference?
75	- Check randomization quality
76	- Evaluate confounding control
77	- Assess selection bias
78	- Review attrition/dropout patterns
79	- External validity: Do results generalize?
80	- Evaluate sample representativeness
81	- Consider ecological validity of setting
82	- Assess whether conditions match target application
83	- Construct validity: Do measures capture intended constructs?
84	- Review measurement validation
85	- Check operational definitions
86	- Assess whether measures are direct or proxy
87	- Statistical conclusion validity: Are statistical inferences sound?
88	- Verify adequate power/sample size
89	- Check assumption compliance
90	- Evaluate test appropriateness
91
92	3. Control and Blinding
93	- Was randomization properly implemented (sequence generation, allocation concealment)?
94	- Was blinding feasible and implemented (participants, providers, assessors)?
95	- Are control conditions appropriate (placebo, active control, no treatment)?
96	- Could performance or detection bias affect results?
97
98	4. Measurement Quality
99	- Are instruments validated and reliable?
100	- Are measures objective when possible, or subjective with acknowledged limitations?
101	- Is outcome assessment standardized?
102	- Are multiple measures used to triangulate findings?
103
104	Reference: See `references/scientific_method.md` for detailed principles and `references/experimental_design.md` for comprehensive design checklist.
105
106	### 2. Bias Detection
107
108	Identify and evaluate potential sources of bias that could distort findings.
109
110	Apply when:
111	- Reviewing published research
112	- Designing new st

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scientific-critical-thinking

698stars61forks

View on GitHub

How to install scientific-critical-thinking?

leonchaox/qinyan-academic-skills/scientific-critical-thinking

$npx -y skills add LeonChaoX/qinyan-academic-skills --skill scientific-critical-thinking

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Scientific Critical Thinking
2
3	## Overview
4
5	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.
6
7	## When to Use This Skill
8
9	This skill should be used when:
10	- Evaluating research methodology and experimental design
11	- Assessing statistical validity and evidence quality
12	- Identifying biases and confounding in studies
13	- Reviewing scientific claims and conclusions
14	- Conducting systematic reviews or meta-analyses
15	- Applying GRADE or Cochrane risk of bias assessments
16	- Providing critical analysis of research papers
17
18	## Visual Enhancement with Scientific Schematics
19
20	When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
21
22	If your document does not already contain schematics or diagrams:
23	- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
24	- Simply describe your desired diagram in natural language
25	- Nano Banana Pro will automatically generate, review, and refine the schematic
26
27	For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
28
29	How to generate schematics:
30	```bash
31	python scripts/generate_schematic.py "your diagram description" -o figures/output.png
32	```
33
34	The AI will automatically:
35	- Create publication-quality images with proper formatting
36	- Review and refine through multiple iterations
37	- Ensure accessibility (colorblind-friendly, high contrast)
38	- Save outputs in the figures/ directory
39
40	When to add schematics:
41	- Critical thinking framework diagrams
42	- Bias identification decision trees
43	- Evidence quality assessment flowcharts
44	- GRADE assessment methodology diagrams
45	- Risk of bias evaluation frameworks
46	- Validity assessment visualizations
47	- Any complex concept that benefits from visualization
48
49	For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
50
51	---
52
53	## Core Capabilities
54
55	### 1. Methodology Critique
56
57	Evaluate research methodology for rigor, validity, and potential flaws.
58
59	Apply when:
60	- Reviewing research papers
61	- Assessing experimental designs
62	- Evaluating study protocols
63	- Planning new research
64
65	Evaluation framework:
66
67	1. Study Design Assessment
68	- Is the design appropriate for the research question?
69	- Can the design support causal claims being made?
70	- Are comparison groups appropriate and adequate?
71	- Consider whether experimental, quasi-experimental, or observational design is justified
72
73	2. Validity Analysis
74	- Internal validity: Can we trust the causal inference?
75	- Check randomization quality
76	- Evaluate confounding control
77	- Assess selection bias
78	- Review attrition/dropout patterns
79	- External validity: Do results generalize?
80	- Evaluate sample representativeness
81	- Consider ecological validity of setting
82	- Assess whether conditions match target application
83	- Construct validity: Do measures capture intended constructs?
84	- Review measurement validation
85	- Check operational definitions
86	- Assess whether measures are direct or proxy
87	- Statistical conclusion validity: Are statistical inferences sound?
88	- Verify adequate power/sample size
89	- Check assumption compliance
90	- Evaluate test appropriateness
91
92	3. Control and Blinding
93	- Was randomization properly implemented (sequence generation, allocation concealment)?
94	- Was blinding feasible and implemented (participants, providers, assessors)?
95	- Are control conditions appropriate (placebo, active control, no treatment)?
96	- Could performance or detection bias affect results?
97
98	4. Measurement Quality
99	- Are instruments validated and reliable?
100	- Are measures objective when possible, or subjective with acknowledged limitations?
101	- Is outcome assessment standardized?
102	- Are multiple measures used to triangulate findings?
103
104	Reference: See `references/scientific_method.md` for detailed principles and `references/experimental_design.md` for comprehensive design checklist.
105
106	### 2. Bias Detection
107
108	Identify and evaluate potential sources of bias that could distort findings.
109
110	Apply when:
111	- Reviewing published research
112	- Designing new st

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