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create-quarto-report

Create a Quarto document for reproducible reports, presentations, or websites. Covers YAML configuration, code chunk options, output formats, cross-references, and rendering. Use when creating a reproducible analysis report, building a presentation with embedded code, generating HTML, PDF, or Word documents from code, or migrating an existing R Markdown document to Quarto.

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  • SKILL.md6.7 KB

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Create Quarto Report

Set up and write a reproducible Quarto document for analysis reports, presentations, or websites.

When to Use

  • Creating a reproducible analysis report
  • Building a presentation with embedded code
  • Generating HTML, PDF, or Word documents from code
  • Migrating from R Markdown to Quarto

Inputs

  • Required: Report topic and target audience
  • Required: Output format (html, pdf, docx, revealjs)
  • Optional: Data sources and analysis code
  • Optional: Citation bibliography (.bib file)

Procedure

Step 1: Create Quarto Document

Create report.qmd:

---
title: "Analysis Report"
author: "Author Name"
date: today
format:
  html:
    toc: true
    toc-depth: 3
    code-fold: true
    theme: cosmo
    self-contained: true
execute:
  echo: true
  warning: false
  message: false
bibliography: references.bib
---

Expected: File report.qmd exists with valid YAML frontmatter including title, author, date, format configuration, and execution options.

On failure: Validate the YAML header by checking for matching --- delimiters and correct indentation. Ensure format: key matches one of the supported Quarto output formats (html, pdf, docx, revealjs).

Step 2: Write Content with Code Chunks

## Introduction

This report analyzes the relationship between variables X and Y.

## Data

```{r}
#| label: load-data
library(dplyr)
library(ggplot2)

data <- read.csv("data.csv")
glimpse(data)
```

## Analysis

```{r}
#| label: fig-scatter
#| fig-cap: "Scatter plot of X vs Y"
#| fig-width: 8
#| fig-height: 6

ggplot(data, aes(x = x_var, y = y_var)) +
  geom_point(alpha = 0.6) +
  geom_smooth(method = "lm") +
  theme_minimal()
```

As shown in @fig-scatter, there is a positive relationship.

## Results

```{r}
#| label: tbl-summary
#| tbl-cap: "Summary statistics"

data |>
  summarise(
    mean_x = mean(x_var),
    sd_x = sd(x_var),
    mean_y = mean(y_var),
    sd_y = sd(y_var)
  ) |>
  knitr::kable(digits = 2)
```

See @tbl-summary for descriptive statistics.

Expected: Content sections contain properly formatted code chunks with {r} language identifier and #| chunk options for labels, captions, and dimensions.

On failure: Verify code chunks use the ```{r} syntax (not inline backticks), that #| options are inside the chunk (not in the YAML header), and that label prefixes match cross-reference types (fig- for figures, tbl- for tables).

Step 3: Configure Chunk Options

Common chunk-level options (use #| syntax):

#| label: chunk-name        # Required for cross-references
#| echo: false               # Hide code
#| eval: false               # Show but don't run
#| output: false             # Run but hide output
#| fig-width: 8              # Figure dimensions
#| fig-height: 6
#| fig-cap: "Caption text"   # Enable @fig-name references
#| tbl-cap: "Caption text"   # Enable @tbl-name references
#| cache: true               # Cache expensive computations

Expected: Chunk options are applied at the chunk level using #| syntax, and labels follow naming conventions required for cross-referencing.

On failure: Ensure chunk options use #| syntax (Quarto-native), not the legacy {r, option=value} R Markdown syntax. Verify that label names contain only alphanumeric characters and hyphens.

Step 4: Add Cross-References and Citations

See @fig-scatter for the visualization and @tbl-summary for statistics.

This approach follows @smith2023 methodology.

::: {#fig-combined layout-ncol=2}
![Plot A](plot_a.png){#fig-plotA}
![Plot B](plot_b.png){#fig-plotB}

Combined figure caption
:::

Expected: Cross-references (@fig-name, @tbl-name) resolve to the correct figures and tables, and citations (@key) match entries in the .bib file.

On failure: Verify that referenced labels exist in code chunks with the correct prefix (fig-, tbl-). For citations, check that .bib keys match exactly (case-sensitive) and that bibliography: is set in the YAML header.

Step 5: Render the Document

quarto render report.qmd

# Specific format
quarto render report.qmd --to pdf
quarto render report.qmd --to docx

# Preview with live reload
quarto preview report.qmd

Expected: Output file generated in the specified format.

On failure:

Step 6: Multi-Format Output

format:
  html:
    toc: true
    theme: cosmo
  pdf:
    documentclass: article
    geometry: margin=1in
  docx:
    reference-doc: template.docx

Render all formats: quarto render report.qmd

Expected: All specified output formats generate successfully, each with correct styling and layout for the target format.

On failure: If one format fails while others succeed, check format-specific requirements: PDF needs a LaTeX engine (install with quarto install tinytex), DOCX needs a valid reference template if specified, and format-specific YAML options must be correctly nested under each format key.

Validation

  • Document renders without errors
  • All code chunks execute correctly
  • Cross-references resolve (figures, tables, citations)
  • Table of contents is accurate
  • Output format is appropriate for the audience

Common Pitfalls

  • Missing label prefix: Cross-referenceable figures need fig- prefix in label, tables need tbl-
  • Cache invalidation: Cached chunks won't re-run when upstream data changes. Delete _cache/ to force.
  • PDF without LaTeX: Install TinyTeX or use format: pdf with pdf-engine: weasyprint for CSS-based PDF
  • R Markdown syntax in Quarto: Use #| chunk options instead of {r, echo=FALSE} style

Related Skills

  • format-apa-report - APA-formatted academic reports
  • build-parameterized-report - parameterized multi-report generation
  • generate-statistical-tables - publication-ready tables
  • write-vignette - Quarto vignettes in R packages

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