diff --git a/README.md b/README.md
index 657f2dc..dabc4eb 100644
--- a/README.md
+++ b/README.md
@@ -2,15 +2,36 @@
 
 *warning*: pystk2-gymnasium is in alpha stage - the environments might change abruptly!
 
+## Install
+
+The PySuperKart2 gymnasium wrapper is a Python package, so installing is fairly easy
+
+`pip install pystk2-gymnasium`
+
+Note that during the first run, SuperTuxKart assets are downloaded in the cache directory.
+
 ## Environments
 
+*Warning* only one SuperTuxKart environment can be created for now. Moreover, no graphics information
+is available for now.
+
 After importing `pystk2_gymnasium`, the following environments are available:
 
-- `supertuxkart-v0` is the main environment containing complete observations
-- `supertuxkart-simple-v0` is a simplified environment with fixed size observations
-- `supertuxkart-flattened-v0` has observation and action spaces simplified at the maximum (only `obs_discrete` and `obs_continuous` keys)
+- `supertuxkart-v0` is the main environment containing complete observations, with the following options:
+    - `render_mode` can be None or `human`
+    - `track` defines the SuperTuxKart track to use (None for random). The full list can be found in `STKRaceEnv.TRACKS` after initialization with `initialize.initialize(with_graphics: bool)` has been called.
+    - `num_kart` defines the number of karts on the track (3 by default)
+    - `rank_start` defines the starting position (None for random, which is the default)
+    - `use_ai` flag (False by default) to ignore actions and use a SuperTuxKart bot
+    - `max_paths` the maximum number of the (nearest) paths (a track is made of paths) to consider in the observation state
+    - `laps` is the number of laps (1 by default)
+    - `difficulty` is the difficulty of the other bots (0 to 2, default to 2)
+- `supertuxkart-simple-v0` is a simplified environment with fixed number of observations for paths (controlled by `state_paths`, default 5), items (`state_items`, default 5), karts (`state_karts`, default 5)
+- `supertuxkart-flattened-v0` has observation and action spaces simplified at the maximum (only `discrete` and `continuous` keys)
 - `supertuxkart-flattened-discrete-v0` is like the previous one, but with fully discretized actions
 
+The reward is the distance traveled.
+
 ## Example
 
 ```py3