R Specialized Domain Tutorials

Generate comprehensive R tutorials for specialized applications with professional domain knowledge and complete analytical workflows.

What This Skill Does

This skill generates detailed R tutorials (.rmd/.qmd files) for specialized application domains including:

Each tutorial follows a "domain background → terminology → analytical framework → practical workflow → domain-specific interpretation" structure.

When to Use This Skill

Use this skill when:

1. User requests domain-specific R tutorials for specialized applications

2. File names match the pattern `[number]-[topic].rmd` or `.qmd`

3. Keywords appear: TreeAge, CEA, cost-effectiveness, text mining, qualitative, wavelet, VMD, DLNM, WQS, BKMR, environmental epidemiology

4. Tutorial needs to combine statistical methods with domain-specific expertise

Instructions

Step 1: Identify Domain and Scope

1. Confirm the specialized domain (e.g., "Health Economics CEA")

2. Identify core domain concepts, terminology, and methodological frameworks

3. Review `references/content-structure.md` for YAML frontmatter and section structure templates

4. Review `references/domain-terminology.md` for domain-specific terminology

Step 2: Generate Tutorial Content

Create the `.rmd` or `.qmd` file following this structure:

**Required Content (Minimum 300 lines, 70% text / 30% code):**

1. **Domain Background Section**

- Introduce the domain context (e.g., health economics, environmental health)

- Explain why specialized methods are needed

- Provide real-world applications and use cases

2. **Core Concepts & Terminology**

- List key terms with Chinese-English bilingual definitions

- Provide plain-language explanations for technical concepts

- Include domain-specific standards and guidelines

3. **Methodological Framework**

- Explain the theoretical foundation of the method

- Describe the analytical workflow step-by-step

- Include mathematical formulations when appropriate

4. **Practical Implementation**

- Provide complete, runnable R code examples

- Include data preparation, analysis, and visualization steps

- Add detailed code comments explaining each step

5. **Results Interpretation**

- Explain how to interpret statistical outputs from a domain perspective

- Provide examples of clinical significance, policy implications, or domain-specific insights

- Include guidance on reporting standards (e.g., CHEERS for CEA)

6. **Data Ethics & Best Practices** (if applicable)

- Address ethical considerations specific to the domain

- Mention relevant reporting guidelines and standards

Step 3: Generate Cover Image (MANDATORY)

Create a cover image using SVG format:

```bash

Generate cover image at this path

doc/images/[number]-[topic]-cover.svg

```

Refer to `references/visual-templates.md` for SVG template examples. The cover should visually represent the domain and methodology.

Step 4: Generate Diagrams (for Complex Concepts)

For complex logic, frameworks, or concepts that are difficult to express in code:

```bash

Generate diagram at this path

doc/images/diagrams/stat-[topic].svg # or .png

```

Use AI image generation for:

Reference images in the tutorial using standard markdown syntax:

```markdown


```

Step 5: Validate Rendering (CRITICAL)

Before committing, validate that the tutorial renders correctly:

```bash

Render the single file to check for errors

quarto render doc/[number]-[topic].rmd

Check for:

- No rendering errors

- All R packages available

- Code chunks execute successfully

- Images display correctly

```

Fix any errors before proceeding.

Step 6: Update Navigation System (CRITICAL)

The tutorial will not appear on the website without these updates:

1. **Update `doc/_quarto.yml`:**

- Locate `sidebar` → `contents` → `特殊应用` section

- Add new entry with correct indentation:

```yaml

- text: "Tutorial Title"

href: "[number]-[topic].rmd"

```

2. **Update `doc/0001-guide.rmd`:**

- Add entry to the appropriate category table:

```markdown

| [Topic] | [Tutorial Title]([number]-[topic].html) | [Brief description] |

```

3. **Run auto-generation script (MANDATORY):**

```bash

# Run from project root directory

workdir="doc" Rscript doc/generate_sections.R

```

This script updates category index pages like `sections/special.qmd` based on `_quarto.yml`.

4. **Update `README.md`:**

- Add link under `🧭 内容导航` → `🛠️ 特殊应用` section

Step 7: Final Render and Commit

1. **Re-render affected pages:**

```bash

quarto render doc/sections/special.qmd

quarto render doc/index.qmd

```

2. **Commit changes:**

```bash

git add doc/[number]-[topic].rmd doc/images/[number]-[topic]-cover.svg

git add doc/_quarto.yml doc/0001-guide.rmd README.md doc/sections/special.qmd

git commit -m "feat(spc): Add [domain-method] specialized application tutorial"

```

Content Standards

Reference Files

Example Usage

**User Request:**

"Create a tutorial on cost-effectiveness analysis in health economics using R and TreeAge"

**Agent Actions:**

1. Read `references/content-structure.md` and `references/domain-terminology.md`

2. Generate `doc/0025-health-economics-cea.rmd` with:

- Introduction to health economics and CEA

- Terminology: ICER, QALY, WTP threshold (with Chinese translations)

- CEA methodology and decision tree frameworks

- R code for TreeAge integration, probabilistic sensitivity analysis

- Interpretation from health policy perspective

- CHEERS reporting checklist

3. Generate `doc/images/0025-health-economics-cea-cover.svg`

4. Generate `doc/images/diagrams/stat-cea-decision-tree.svg` for decision tree framework

5. Validate rendering with `quarto render doc/0025-health-economics-cea.rmd`

6. Update `_quarto.yml`, `0001-guide.rmd`, run `generate_sections.R`, update `README.md`

7. Re-render index pages and commit all changes

Notes