diff --git a/R/geographic.R b/R/geographic.R
index 62dc481..0296791 100644
--- a/R/geographic.R
+++ b/R/geographic.R
@@ -42,8 +42,8 @@ get_geographic_country = function(url_root){
 #'
 #' @examples
 #' url_root = "https://webapi.aclimate.org/api/"
-#' country = "61e59d829d5d2486e18d2ea8"
-#' df = get_geographic(url_root,country)
+#' country_id = "61e59d829d5d2486e18d2ea8"
+#' df = get_geographic(url_root, country_id)
 #' print(head(df))
 #'
 #' @export
@@ -82,8 +82,8 @@ get_geographic = function(url_root, country_id){
 #'
 #' @examples
 #' url_root = "https://webapi.aclimate.org/api/"
-#' country = "61e59d829d5d2486e18d2ea8"
-#' df = get_geographic_crop(url_root,country)
+#' country_id = "61e59d829d5d2486e18d2ea8"
+#' df = get_geographic_crop(url_root, country_id)
 #' print(head(df))
 #'
 #' @export
@@ -126,8 +126,8 @@ get_geographic_crop = function(url_root, country_id){
 #'
 #' @examples
 #' url_root = "https://webapi.aclimate.org/api/"
-#' country = "61e59d829d5d2486e18d2ea8"
-#' ws_list = get_geographic_ws(url_root,country)
+#' country_id = "61e59d829d5d2486e18d2ea8"
+#' ws_list = get_geographic_ws(url_root, country_id)
 #' print(head(ws_list))
 #'
 #' @export
diff --git a/R/geoserver.R b/R/geoserver.R
index 9d2b57f..a7d46ca 100644
--- a/R/geoserver.R
+++ b/R/geoserver.R
@@ -106,8 +106,8 @@ get_geo_mosaic_name = function(url_root, workspace){
 #' year = 2014
 #' month = 5
 #' day = 1
-#' obj_f = get_geo_mosaics(url_root, workspace, mosaic_name, year, month, day)
-#' print(obj_f)
+#' raster = get_geo_mosaics(url_root, workspace, mosaic_name, year, month, day)
+#' print(raster)
 #'
 #' @export
 get_geo_mosaics = function(url_root, workspace, mosaic_name, year, month=1, day=1){
@@ -209,8 +209,8 @@ get_geo_polygon_name = function(url_root, workspace){
 #' url_root = "https://geo.aclimate.org/geoserver/"
 #' workspace = "administrative"
 #' polygon_name = "ao_adm1"
-#' obj_f = get_geo_polygons(url_root, workspace, polygon_name)
-#' print(obj_f)
+#' shapefile = get_geo_polygons(url_root, workspace, polygon_name)
+#' print(shapefile)
 #'
 #' @export
 get_geo_polygons = function(url_root, workspace, polygon_name){
diff --git a/README.md b/README.md
index 06776d6..e9a996f 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,3 @@
-
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
 # AClimate R API
@@ -7,19 +6,19 @@ The AClimate R API package is a comprehensive R interface for accessing the ACli
 This package seamlessly integrates with R, providing users with convenient access to a wide range of agro-climatic
 forecasts offered by the AClimate platform.
 
-* [Oficial website](https://www.aclimate.org).
-* Source code [source code](https://github.com/CIAT-DAPA/aclimaterapi/).
-* Documentation of Web API and Dictionary of variable [documentation](https://docs.aclimate.org/en/latest/08-webapi.html).
-* Depends **R (>= 4.2)**
-* Author [stevensotelo](https://github.com/stevensotelo)
+- [Oficial website](https://www.aclimate.org).
+- Source code [source code](https://github.com/CIAT-DAPA/aclimaterapi/).
+- Documentation of Web API and Dictionary of variable [documentation](https://docs.aclimate.org/en/latest/08-webapi.html).
+- Depends **R (>= 4.2)**
+- Author [stevensotelo](https://github.com/stevensotelo)
 
 ## Key Features
 
-* Data Access: Access all relevant information from the AClimate platform, including accurate and up-to-date seasonal climate forecasts.
+- Data Access: Access all relevant information from the AClimate platform, including accurate and up-to-date seasonal climate forecasts.
 
-* User-Friendly: The package is designed with ease of use in mind, ensuring that users can effortlessly retrieve the information they need.
+- User-Friendly: The package is designed with ease of use in mind, ensuring that users can effortlessly retrieve the information they need.
 
-* Seamless Integration: Integrate AClimate data directly into R workflows, making it simple for users to incorporate climate and agroclimatic forecasts into their existing data analysis and decision-making processes
+- Seamless Integration: Integrate AClimate data directly into R workflows, making it simple for users to incorporate climate and agroclimatic forecasts into their existing data analysis and decision-making processes
 
 ## Install
 
@@ -53,7 +52,7 @@ library("aclimaterapi")
 
 ### Url of the Web API
 
-The first thing that you have to identify is the url which is located the Web API. This parameter will be asked in all methods. 
+The first thing that you have to identify is the url which is located the Web API. This parameter will be asked in all methods.
 
 You can create a global variable with this url:
 
@@ -81,6 +80,26 @@ df = get_geographic(url_root)
 print(head(df))
 ```
 
+### Get weather stations with crop information
+
+The method **get_geographic** allows to users get a list of the states of the selected country with each of their municipalities and meteorological stations and for each meteorological station their productive ranges for each crop.
+
+```r
+country_id = "61e59d829d5d2486e18d2ea8"
+df = get_geographic_crop(url_root, country_id)
+print(head(df))
+```
+
+### Get weather stations information
+
+The method **get_geographic** allows to users get a list of detailed information weather stations, and crop-related details for a selected country.
+
+```r
+country_id = "61e59d829d5d2486e18d2ea8"
+ws_list = get_geographic_ws(url_root, country)
+print(head(ws_list))
+```
+
 ### Get agronomy setup
 
 The method **get_agronomy** allows to users get a list of cultivars and soils available into the AClimate platform.
@@ -116,34 +135,215 @@ df = get_forecast_crop(url_root, stations)
 print(head(df))
 ```
 
-## Developer
+### Get forecast id
+
+The method **get_forecast_information**, function which gets access primary forecast data for each month within a desired year.
+
+```r
+year= 2023
+forecasts = get_forecast_information(url_root, year)
+print(forecasts)
+```
+
+### Get subseasonal forecast
+
+The method **get_forecast_subseasonal**, function which gets information from the subseasonal forecast process, including probabilities and climatic scenarios.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations = c("63a3744005732d2a14260392","63a374ce05732d2a14260499")
+subseasonal_data = get_forecast_subseasonal(url_root, stations)
+print(subseasonal_data)
+```
+
+### Get previous climate forecast
+
+The method **get_forecast_climate_previous**, function which gets the information obtained through the forecast process that is desired by means of the Id, the seasonal and subseasonal probabilities and the climatic scenarios.
+
+You can find the ids of the weather stations in the method **get_geographic**
+You can find the forecast id in the method **get_forecast_information**
+
+```r
+forecast = "657006544afb9646da8c6b78"
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+obj_fp = get_forecast_climate_previous(url_root, forecast, stations)
+print(obj_fp)
+```
+
+### Get previous crop forecast
+
+The method **get_forecast_crop_previous**, function which gets the crop forecast information for a specific forecast indicated in the parameters.
+
+You can find the ids of the weather stations in the method **get_geographic**
+You can find the forecast id in the method **get_forecast_information**
+
+```r
+forecast = "657006544afb9646da8c6b78"
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+df = get_forecast_crop_previous(url_root, forecast, stations)
+print(head(df))
+```
+
+### Get forecast crop exceedance
+
+The method **get_forecast_crop_exc**, function which gets the information obtained through of all forecast in the crop model process, yield data.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+df = get_forecast_crop_exc(url_root, stations)
+print(head(df))
+```
+
+### Get historical climatology
+
+The method **get_historical_climatology**, function which gets the climatology of a selected weather station.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+df = get_historical_climatology(url_root, stations)
+print(df)
+```
+
+### Get historical climate information
+
+The method **get_historical_historicalclimatic**, function which gets the weather history of a selected weather station.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+df = get_historical_historicalclimatic(url_root, stations)
+print(df)
+```
+
+### Get years with historical crop performance data
+
+The method **get_historical_historicalyieldyears**, function which gets the years that contain historical crop performance data of the selected weather station.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+df = get_historical_historicalyieldyears(url_root, stations)
+print(df)
+```
+
+### Get historical crop performance
+
+The method **get_historical_historicalyield**, function which gets the yield data obtained through the crop model process.
+
+You can find the ids of the weather stations in the method **get_geographic**
+
+```r
+stations=c("58504f1a006cb93ed40eebe2","58504f1a006cb93ed40eebe3")
+years=c("2022","2023")
+df = get_historical_historicalyield(url_root, stations, years)
+print(head(df))
+```
+
+### Get geoserver workspace
+
+The method **get_geo_workspaces**, function which gets all the workspaces of the GeoServer.
+
+```r
+obj_f = get_geo_workspaces(url_root)
+print(obj_f)
+```
+
+### Get geoserver mosaic stores
+
+The method **get_geo_mosaic_name**, function which gets all the mosaic stores of a specific workspace.
 
+You can find the workspace in the method **get_geo_workspaces**
+
+```r
+workspace = "climate_indices_pe"
+obj_f = get_geo_mosaic_name(url_root, workspace)
+print(obj_f)
+```
+
+### Get geoserver mosaics
+
+The method **get_geo_mosaics**, function which gets the desired mosaic from the GeoServer.
+
+You can find the workspace in the method **get_geo_workspaces**
+You can find the mosaic_name in the method **get_geo_mosaic_name**
+
+```r
+workspace = "climate_indices_pe"
+mosaic_name = "freq_rh80_t_20_25"
+year = 2014
+month = 5
+day = 1
+raster = get_geo_mosaics(url_root, workspace, mosaic_name, year, month, day)
+print(raster)
+```
+
+### Get geoserver polygon stores
+
+The method **get_geo_polygon_name**, function which gets all the polygon stores of a specific workspace.
+
+You can find the workspace in the method **get_geo_workspaces**
+
+```r
+workspace = "administrative"
+obj_f = get_geo_polygon_name(url_root, workspace)
+print(obj_f)
+```
+
+### Get geoserver shapefiles
+
+The method **get_geo_polygons**, function which gets the desired shapefile from the GeoServer.
+
+You can find the workspace in the method **get_geo_workspaces**
+You can find the polygon_name in the method **get_geo_polygon_name**
+
+```r
+workspace = "administrative"
+polygon_name = "ao_adm1"
+shapefile = get_geo_polygons(url_root, workspace, polygon_name)
+print(shapefile)
+```
+
+## Developer
 
 ### Configure dev environment
 
 Install the following packages
+
 ```r
 install.packages("devtools")
 install.packages("roxygen2")
 ```
 
 ### Build package
+
 Import libraries
+
 ```r
 library(devtools)
 library(roxygen2)
 ```
+
 Call the packages
+
 ```r
 setwd("/path/source_code/")
 ```
 
 Build documentation
+
 ```r
 devtools::document()
 ```
 
 Build package
+
 ```r
 devtools::build()
-```
\ No newline at end of file
+```