diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 704a027..5a77a5d 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -83,45 +83,22 @@ make test
#### Code quality
-To run all quality checks together
+The CI will also run some sanity checks (header format, dependency consistency, etc.), which you can run as follows:
```shell
make quality
```
-##### Lint verification
+This will read `pyproject.toml` and run:
+- lint checking ([ruff](https://docs.astral.sh/ruff/))
+- type annotation checking ([mypy](https://github.com/python/mypy))
+- code formatting ([black](https://github.com/psf/black))
+- security checking ([bandit](https://github.com/PyCQA/bandit))
-To ensure that your incoming PR complies with the lint settings, you need to install [flake8](https://flake8.pycqa.org/en/latest/) and run the following command from the repository's root folder:
+You can apply automatic fix to most of those by running:
```shell
-flake8 ./
-```
-This will read the `.flake8` setting file and let you know whether your commits need some adjustments.
-
-##### Import order
-
-In order to ensure there is a common import order convention, run [isort](https://github.com/PyCQA/isort) as follows:
-
-```shell
-isort **/*.py
-```
-This will reorder the imports of your local files.
-
-##### Annotation typing
-
-Additionally, to catch type-related issues and have a cleaner codebase, annotation typing are expected. After installing [mypy](https://github.com/python/mypy), you can run the verifications as follows:
-
-```shell
-mypy
-```
-The `pyproject.toml` file will be read to check your typing.
-
-##### Code formatting
-
-Finally, code formatting is a good practice for shareable projects. After installing [black](https://github.com/psf/black), you can run the verifications as follows:
-
-```shell
-black .
+make style
```
### Submit your modifications
diff --git a/README.md b/README.md
index bc08359..6c1d101 100644
--- a/README.md
+++ b/README.md
@@ -1,28 +1,33 @@
-
-# TorchCAM: class activation explorer
+
+ TorchCAM: class activation explorer
+
-
- 
-
-
- 
+
+ 
-
- 
+
+ 
+
+ 
+
- 
+ 
+
+
+ 
+
+ 
+
+ 
- 
- 
- 
@@ -32,6 +37,11 @@
+
+
+ 
+
+
Simple way to leverage the class-specific activation of convolutional layers in PyTorch.