more docs

DOCS.md

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 # Welcome to OutRank's documentation!
 
 All functions/methods can be searched-for (search bar on the left).
 
 This tool enables fast screening of feature-feature interactions. Its purpose is to give the user fast insight into potential redundancies/anomalies in the data.
-It is implemented to operate in _mini batches_, it traverses the `raw data` incrementally, refining the rankings as it goes along.
-The interaction ranking outputs triplets which look as follows:
+It is implemented to operate in _mini batches_, it traverses the `raw data` incrementally, refining the rankings as it goes along. The core operation, interaction ranking, outputs triplets which look as follows:
 
 ```
 featureA	featureB	0.512
 featureA	featureC	0.125
 ```
 
 
-# Use and installation - CLI
+# Use and installation - first steps (OutRank as a CLI)
 ```bash
 pip install outrank
 ```
@@ -38,4 +28,8 @@ if this passes, you can be pretty certain OutRank will perform as intended. OutR
 outrank --help
 ```
 
-A minimal showcase of performing feature ranking on a generic CSV is demonstrated with [this example](../scripts/run_minimal.sh)
+
+# Example use cases
+* A minimal showcase of performing feature ranking on a generic CSV is demonstrated with [this example](../scripts/run_minimal.sh)
+
+* [More examples](../scripts/) demonstrating OutRank's capabilities are also available.