diff --git a/docs/index.md b/docs/index.md
index 4df154f9c0..eb116d95ce 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -40,6 +40,6 @@ In tinygrad, you can do [`x.conv2d(w, b)`](tensor.md/#tinygrad.Tensor.conv2d) or
 
 When you do `a+b` in tinygrad, nothing happens. It's not until you [`realize`](tensor.md/#tinygrad.Tensor.realize) the Tensor that the computation actually runs.
 
-### tinygrad requires @TinyJIT to be fast
+### tinygrad requires @TinyJit to be fast
 
 PyTorch spends a lot of development effort to make dispatch very fast. tinygrad doesn't. We have a simple decorator that will replay the kernels used in the decorated function.
diff --git a/mkdocs.yml b/mkdocs.yml
index d7f12b73e0..c79f9e1af9 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,16 +1,18 @@
 # pip install mkdocs mkdocs-material mkdocstrings[python]
 site_name: tinygrad docs
 site_url: https://docs.tinygrad.org/
+repo_url: https://github.com/tinygrad/tinygrad/
 nav:
 - Home: index.md
-- Tensor: tensor.md
-- dtypes: dtypes.md
-- Neural Networks: nn.md
-- MNIST Tutorial: mnist.md
 - Quickstart: quickstart.md
+- MNIST Tutorial: mnist.md
+- API:
+  - Tensor: tensor.md
+  - Function: function.md
+  - dtypes: dtypes.md
+  - nn (Neural Networks): nn.md
 - Showcase: showcase.md
 - Developer: developer.md
-- Function: function.md
 - Environment: env_vars.md
 #- tinygrad: reference/