test_that("rob_summary returns a ggplot for ROB2", {
  p <- rob_summary(data_rob2, tool = "ROB2", quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary works with overall = TRUE", {
  p <- rob_summary(data_rob2, tool = "ROB2", overall = TRUE, quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary works with colourblind palette", {
  p <- rob_summary(data_rob2, tool = "ROB2", colour = "colourblind", quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary works unweighted", {
  d <- data_rob2[, !names(data_rob2) %in% "Weight"]
  p <- rob_summary(d, tool = "ROB2", weighted = FALSE, quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary handles >8 domains without truncation (issue #131)", {
  # Build a dataset with 10 domain columns
  d <- data.frame(
    Study = paste0("S", 1:5),
    stringsAsFactors = FALSE
  )
  for (i in 1:10) d[[paste0("Domain", i)]] <- rep("Low", 5)
  p <- rob_summary(d, tool = "Generic", quiet = TRUE)
  pb <- ggplot2::ggplot_build(p)
  # All 10 domains should appear in y axis
  y_vals <- unique(pb$layout$panel_params[[1]]$y$limits)
  expect_gte(length(y_vals), 9L)
})

test_that("rob_summary handles single study (issue #164)", {
  d <- data_rob2[1, ]
  expect_no_error(rob_summary(d, tool = "ROB2", quiet = TRUE))
})

test_that("rob_summary works for ROBINS-I", {
  p <- rob_summary(data_robins_i, tool = "ROBINS-I", quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary works for NOS-Cohort (star counts → qualitative)", {
  p <- rob_summary(data_nos_cohort, tool = "NOS-Cohort", quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary works for GRADE", {
  p <- rob_summary(data_grade, tool = "GRADE", quiet = TRUE)
  expect_s3_class(p, "gg")
})

test_that("rob_summary errors on bad colour vector length", {
  expect_error(
    rob_summary(data_rob2, tool = "ROB2", colour = c("#aabbcc"), quiet = TRUE),
    "Colour vector length mismatch"
  )
})