diff --git a/R/annual.R b/R/annual.R
index 60d098b..3e9ad3a 100644
--- a/R/annual.R
+++ b/R/annual.R
@@ -1,16 +1,27 @@
-#' @title Calculate Annual Summaries
+#' @title Calculate Annual Timseries
+#'
+#' @description
+#' `annual()` aggregates the daily timeseries into an annual one.
+#' Aggregation is done differently for TMIN, TMAX, and PRCP.
+#'
+#' @details
+#' Aggregation is done as:
+#' \describe{
+#'  \item{TMAX}{Maximum temperature recorded in the year} 
+#'  \item{TMIN}{Minimum temperature recorded in the year}
+#'  \item{PRCP}{Total (cumulative) precipitation amount in the year}
+#' }
 #'
 #' @importFrom dplyr select mutate across distinct_all summarize group_by left_join
 #' @importFrom tidyselect contains everything all_of
 #' @importFrom tidyr drop_na
 #' @importFrom tibble tibble as_tibble
 #' @importFrom rlang .data
-#'
 #' @export
 #'
 #' @param x Object of class `ghcn_daily`. See [daily()] for details.
-#'
 #' @return A tibble with the annual timeseries at the stations.
+#'
 #' @examples
 #' annual(CA003076680)
 annual <- function(x) {
diff --git a/R/coverage.R b/R/coverage.R
index 1bfb62b..d0fbbf5 100644
--- a/R/coverage.R
+++ b/R/coverage.R
@@ -1,23 +1,33 @@
 #' @title Calculate Monthly Coverage
 #'
+#' @description
+#' `monthly_coverage()` calculates how many days have been recorded for 
+#' each month in the time period.
+#'
+#' @details
+#' To calculate the coverage, a full daily time range is full joined to the
+#' timeseries. Missing days are set to NA. Coverage is then calculated as
+#' the number of values that are not NAs over the number of NAs.
+#'
 #' @importFrom dplyr mutate group_by full_join
 #' @importFrom tidyr pivot_longer pivot_wider
 #' @importFrom tidyselect any_of
 #' @importFrom tibble tibble
 #' @importFrom rlang .data
-#'
 #' @export
 #'
 #' @param x Object of class `ghcn_daily`. See [daily()] for details.
+#' @return A table with mothly coverage.
 #'
-#' @details Calculates the monthly coverage of one station.
-#'
-#' @return A table with mothly coverages.
 #' @examples
 #' cleaned <- remove_flagged(CA003076680)
 #' cover <- monthly_coverage(cleaned)
 #' cover[cover$year == 2020, ]
 monthly_coverage <- function(x) {
+  stopifnot(inherits(x, "ghcn_daily"))
+  .check_flags(x)
+  x <- .drop_flags(x)
+
 	timespan <- seq.Date(min(x$date), max(x$date), by = "day")
 
 	x <- tibble(date = timespan) |> 
@@ -54,25 +64,35 @@ monthly_coverage <- function(x) {
 
 #' @title Calculate Annual Coverage
 #'
+#' @description
+#' `annual_coverage()` calculates how many days have been recorded for 
+#' each year in the time period.
+#'
+#' @details
+#' To calculate the coverage, a full daily time range is full joined to the
+#' timeseries. Missing days are set to NA. Coverage is then calculated as
+#' the number of values that are not NAs over the number of NAs.
+#'
 #' @importFrom dplyr mutate group_by full_join
 #' @importFrom tidyr pivot_longer pivot_wider
 #' @importFrom tidyselect any_of
 #' @importFrom tibble tibble
 #' @importFrom rlang .data
-#'
 #' @export
 #'
 #' @param x Object of class `ghcn_daily`. See [daily()] for details.
-#'
-#' @details Calculates the annual coverage of one station.
-#'
 #' @return A table with annual coverage.
+#'
 #' @examples
 #' cleaned <- remove_flagged(CA003076680)
 #' cover <- annual_coverage(cleaned)
 #' cover
 annual_coverage <- function(x) {
-	timespan <- seq.Date(min(x$date), max(x$date), by = "day")
+	stopifnot(inherits(x, "ghcn_daily"))
+  .check_flags(x)
+  x <- .drop_flags(x)
+
+  timespan <- seq.Date(min(x$date), max(x$date), by = "day")
 
 	x <- tibble(date = timespan) |> 
 		full_join(x, by = "date", multiple = "all") |> 
@@ -106,28 +126,39 @@ annual_coverage <- function(x) {
   return (ans)
 }
 
-
 #' @title Calculate Period Coverage
 #'
+#' @description
+#' `period_coverage()` calculates how many days have been recorded for 
+#' the whole time period.
+#'
+#' @details
+#' To calculate the coverage, a full daily time range is full joined to the
+#' timeseries. Missing days are set to NA. Coverage is then calculated as
+#' the number of values that are not NAs over the number of NAs.
+#' Period coverage is a constant value for each station in the `ghcn_daily`
+#' object.
+#'
 #' @importFrom dplyr mutate group_by full_join
 #' @importFrom tidyr pivot_longer pivot_wider
 #' @importFrom tidyselect any_of
 #' @importFrom tibble tibble
 #' @importFrom rlang .data
-#'
 #' @export
 #'
 #' @param x Object of class `ghcn_daily`. See [daily()] for details.
+#' @return A table with period coverage.
 #'
-#' @details Calculates the period coverage of one station.
-#'
-#' @return A table with coverage across the period.
 #' @examples
 #' cleaned <- remove_flagged(CA003076680)
 #' cover <- period_coverage(cleaned)
 #' cover
 period_coverage <- function(x) {
-	timespan <- seq.Date(min(x$date), max(x$date), by = "day")
+	stopifnot(inherits(x, "ghcn_daily"))
+  .check_flags(x)
+  x <- .drop_flags(x)
+
+  timespan <- seq.Date(min(x$date), max(x$date), by = "day")
 
 	x <- tibble(date = timespan) |> 
 		full_join(x, by = "date", multiple = "all") |> 
@@ -163,6 +194,18 @@ period_coverage <- function(x) {
 
 #' @title Calculate Coverage of Daily Summaries
 #'
+#' @description
+#' `coverage()` calculates the temporal coverage of the time series.
+#' See also [monthly_coverage()], [annual_coverage()], and [period_coverage()].
+#'
+#' @details 
+#' Returns a table with:
+#' \itemize{
+#'  \item mothly_coverage The proportion of the days with records in the month
+#'  \item annual_coverage The proportion of the days with records in the year
+#'  \item annual_coverage The proportion of the years with records in the reference period
+#' }
+#'
 #' @importFrom dplyr mutate group_by group_split select distinct_all left_join bind_cols bind_rows
 #' @importFrom tibble as_tibble
 #' @importFrom tidyr pivot_longer
@@ -170,22 +213,11 @@ period_coverage <- function(x) {
 #' @importFrom stats interaction.plot
 #' @importFrom graphics grid
 #' @importFrom rlang .data
-#'
 #' @export
 #'
 #' @param x Object of class `ghcn_daily`. See [daily()] for details.
 #' @param graph Logical, if to show a graph of annual coverage.
 #'
-#' @details This function calculates the temporal coverage of stations.
-#' It returns a table with:
-#' \itemize{
-#'  \item mothly_coverage The proportion of the days with records in the month
-#'  \item annual_coverage The proportion of the days with records in the year
-#'  \item annual_coverage The proportion of the years with records in the reference period
-#' }
-#' Important: 'annual_coverage = 1' does not mean that all years have 'annual_coverage = 1', 
-#' but rather that all years have at least one record.
-#'
 #' @return A table with coverage.
 #' @examples
 #' cleaned <- remove_flagged(CA003076680)
diff --git a/R/daily.R b/R/daily.R
index 317bdc5..d77dc6b 100644
--- a/R/daily.R
+++ b/R/daily.R
@@ -36,7 +36,7 @@
   }
 
   if (length(station_id) > 1) station_id <- paste(station_id, collapse = ",")
-  req <- paste0(
+  url <- paste0(
     "https://www.ncei.noaa.gov/access/services/data/v1?",
     "dataset=daily-summaries&",
     "stations=", station_id, "&",
@@ -47,7 +47,7 @@
     "includeAttributes=true&",
     "format=json"
   )
-  return(req)
+  return(url)
 }
 
 #' @title Request Daily Summaries
diff --git a/man/annual.Rd b/man/annual.Rd
index 39fc64f..fd31e73 100644
--- a/man/annual.Rd
+++ b/man/annual.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/annual.R
 \name{annual}
 \alias{annual}
-\title{Calculate Annual Summaries}
+\title{Calculate Annual Timseries}
 \usage{
 annual(x)
 }
@@ -13,7 +13,16 @@ annual(x)
 A tibble with the annual timeseries at the stations.
 }
 \description{
-Calculate Annual Summaries
+\code{annual()} aggregates the daily timeseries into an annual one.
+Aggregation is done differently for TMIN, TMAX, and PRCP.
+}
+\details{
+Aggregation is done as:
+\describe{
+\item{TMAX}{Maximum temperature recorded in the year}
+\item{TMIN}{Minimum temperature recorded in the year}
+\item{PRCP}{Total (cumulative) precipitation amount in the year}
+}
 }
 \examples{
 annual(CA003076680)