Agent-almanac build-shiny-module
git clone https://github.com/pjt222/agent-almanac
T=$(mktemp -d) && git clone --depth=1 https://github.com/pjt222/agent-almanac "$T" && mkdir -p ~/.claude/skills && cp -r "$T/i18n/caveman-lite/skills/build-shiny-module" ~/.claude/skills/pjt222-agent-almanac-build-shiny-module && rm -rf "$T"
i18n/caveman-lite/skills/build-shiny-module/SKILL.mdBuild Shiny Module
Create reusable Shiny UI/server module pairs with proper namespace isolation, reactive communication, and composability.
When to Use
- Extracting a reusable component from a growing Shiny app
- Building a UI widget that will be used in multiple places
- Encapsulating complex reactive logic behind a clean interface
- Composing larger applications from smaller, testable units
Inputs
- Required: Module purpose and functionality description
- Required: Input/output contract (what the module receives and returns)
- Optional: Whether the module nests other modules (default: no)
- Optional: Framework context (golem, rhino, or vanilla)
Procedure
Step 1: Define the Module Interface
Before writing code, define what the module accepts and returns:
Module: data_filter Inputs: reactive dataset, column names to filter on Outputs: reactive filtered dataset UI: filter controls (selectInput, sliderInput, dateRangeInput)
Got: Clear contract specifying reactive inputs, reactive outputs, and UI elements.
If fail: If the interface is unclear, the module is probably too broad. Split it into smaller modules with single responsibilities.
Step 2: Create the Module UI Function
#' Data Filter Module UI #' #' @param id Module namespace ID #' @return A tagList of filter controls #' @export dataFilterUI <- function(id) { ns <- NS(id) tagList( selectInput( ns("column"), "Filter column", choices = NULL ), uiOutput(ns("filter_control")), actionButton(ns("apply"), "Apply Filter", class = "btn-primary") ) }
Key rules:
- Function name follows
convention<name>UI - First argument is always
id - Create
at the topns <- NS(id) - Wrap every
andinputId
withoutputIdns() - Return a
to allow flexible placementtagList()
Got: UI function that creates namespaced input/output elements.
If fail: If IDs collide when using the module twice, check that every ID is wrapped with
ns(). Common miss: IDs inside renderUI() or uiOutput() — these need ns() too.
Step 3: Create the Module Server Function
#' Data Filter Module Server #' #' @param id Module namespace ID #' @param data Reactive expression returning a data frame #' @param columns Character vector of filterable column names #' @return Reactive expression returning the filtered data frame #' @export dataFilterServer <- function(id, data, columns) { moduleServer(id, function(input, output, session) { ns <- session$ns # Update column choices when data changes observeEvent(data(), { available <- intersect(columns, names(data())) updateSelectInput(session, "column", choices = available) }) # Dynamic filter control based on selected column output$filter_control <- renderUI({ req(input$column) col_data <- data()[[input$column]] if (is.numeric(col_data)) { sliderInput( ns("value_range"), "Range", min = min(col_data, na.rm = TRUE), max = max(col_data, na.rm = TRUE), value = range(col_data, na.rm = TRUE) ) } else { selectInput( ns("value_select"), "Values", choices = unique(col_data), multiple = TRUE, selected = unique(col_data) ) } }) # Return filtered data as a reactive filtered <- eventReactive(input$apply, { req(input$column) col <- input$column df <- data() if (is.numeric(df[[col]])) { req(input$value_range) df[df[[col]] >= input$value_range[1] & df[[col]] <= input$value_range[2], ] } else { req(input$value_select) df[df[[col]] %in% input$value_select, ] } }, ignoreNULL = FALSE) return(filtered) }) }
Key rules:
- Function name follows
convention<name>Server - First argument is always
id - Additional arguments are reactive expressions or static values
- Use
moduleServer(id, function(input, output, session) { ... }) - Use
for dynamic UI created inside the serversession$ns - Return reactive values explicitly
Got: Server function that processes inputs and returns reactive output.
If fail: If reactive values don't update, check that inputs from dynamic UI use
session$ns (not the outer ns). If the module returns NULL, ensure return() is the last expression inside moduleServer().
Step 4: Wire the Module into the Parent App
# In app_ui.R or ui ui <- page_sidebar( title = "Analysis App", sidebar = sidebar( dataFilterUI("filter1") ), card( DT::dataTableOutput("table") ) ) # In app_server.R or server server <- function(input, output, session) { # Raw data source raw_data <- reactive({ mtcars }) # Call module — capture its return value filtered_data <- dataFilterServer( "filter1", data = raw_data, columns = c("cyl", "mpg", "hp", "wt") ) # Use the module's returned reactive output$table <- DT::renderDataTable({ filtered_data() }) }
Got: Module appears in the UI and its returned reactive flows into downstream outputs.
If fail: If the module UI doesn't render, verify the
id string matches between UI and server calls. If the returned reactive is NULL, check that the server function returns a value.
Step 5: Compose Nested Modules (Optional)
For modules that contain other modules:
analysisUI <- function(id) { ns <- NS(id) tagList( dataFilterUI(ns("filter")), plotOutput(ns("plot")) ) } analysisServer <- function(id, data) { moduleServer(id, function(input, output, session) { # Call inner module with namespaced ID filtered <- dataFilterServer("filter", data = data, columns = names(data())) output$plot <- renderPlot({ req(filtered()) plot(filtered()) }) return(filtered) }) }
Key rule: In the UI, nest with
ns("inner_id"). In the server, call with just "inner_id" — moduleServer handles the namespace chaining.
Got: Inner module renders correctly within the outer module's namespace.
If fail: If the inner module's UI doesn't appear, you likely forgot
ns() around the inner module's ID in the outer UI function. If server communication breaks, check that the inner module ID matches (no ns() in the server call).
Step 6: Test the Module in Isolation
# Quick test app for the module if (interactive()) { shiny::shinyApp( ui = fluidPage( dataFilterUI("test"), DT::dataTableOutput("result") ), server = function(input, output, session) { data <- reactive(iris) filtered <- dataFilterServer("test", data, names(iris)) output$result <- DT::renderDataTable(filtered()) } ) }
Got: Module works correctly in the minimal test app.
If fail: If the module fails in isolation but works in the full app (or vice versa), check for implicit dependencies on global variables or parent session state.
Validation
- Module UI function accepts
as first argument and usesidNS(id) - Every input/output ID in the UI is wrapped with
ns() - Module server uses
moduleServer(id, function(input, output, session) { ... }) - Dynamic UI in server uses
for IDssession$ns - Module can be instantiated multiple times without ID collisions
- Reactive return values are accessible to the parent app
- Module works in a minimal standalone test app
Pitfalls
- Forgetting
inns()
: Dynamic UI created inside the server must userenderUI()
— the outersession$ns
is not available insidens
.moduleServer() - Passing non-reactive data: Module arguments that change over time must be reactive expressions. Pass
notreactive(data)
.data - ID mismatch: The
string in the UI call must exactly match theid
in the server call.id - Not returning reactives: If the module computes something the parent needs, it must
a reactive. Forgetting this is a silent bug.return() - Namespace in nested modules: In UI:
. In server: justns("inner_id")
. Mixing these up causes namespace double-wrapping or missing prefixes."inner_id"
Related Skills
— set up the app structure before adding modulesscaffold-shiny-app
— test modules with testServer() unit teststest-shiny-app
— bslib layout and theming for module UIsdesign-shiny-ui
— cache and async patterns within modulesoptimize-shiny-performance