docs: add docs README landing/starting point

README.md

@@ -1,8 +1,11 @@
 # Brittle Star
 
+> What is the impact of different levels of controller-modularity on the learning-speed, coordination and tolerance for
+defects (e.g. amputations) in brittle-star-like robots trained with Reinforcement Learning?
+
 ## Usage
 
-### UV
+### Local setup
 
 To set up the UV module, you can run the following command:
 
@@ -16,6 +19,10 @@ example command:
 uv run src/train.py --model_name my_model --epochs 50 --batch_size 32
 ```
 
-## HPC
+### HPC setup
 
 See **[docs/HPC.md](docs/HPC.md)** for the full guide, including environment setup, cluster selection, interactive debugging, and job submission.
+
+## Documentation
+
+Please find all documentation and a starting point for more information in [corresponding README](./docs/README.md).

docs/README.md

@@ -0,0 +1,14 @@
+# Documentation
+
+## Design & architecture ([`/design`](./design/))
+
+- [Controllers](./design/controllers.md): Macroscopig brain toplogy, centralized, arm-level, segment-level.
+- [MLP architecture](./design/mlp_architecture.md): Module wiring, state/action spaces, and actor-critic pipeline.
+- [Communication](./design/communication.md): Message propagation, Nerve-Net style.
+- [Learning algorithm](./design/learning_algorithm.md): RL techniques, i.e. PPO.
+- [Reward function](./design/learning_algorithm.md): Goals, fitness tracking, and reward structures.
+
+## API reference ([`/api`](./api/))
+
+- [Environment](./api/environment.md): MuJoCo environment interaction, state retrieval, and configuration.
+- [Simulate](./api/simulate.md): Simulation rendering.