Add SkyRL optimization example

README.md

@@ -39,3 +39,4 @@ harbor run -p harbor_cookbook/recipes/<name> -a claude-code -m anthropic/claude-
 |:--|:--|
 | [gepa](harbor_cookbook/gepa/) | Agent harness optimization for MedAgentBench using Harbor+GEPA. |
 | [tinker&#8209;rl](harbor_cookbook/tinker_rl/) | RL training on Harbor tasks using the Tinker SDK. |
+| [sky&#8209;rl](harbor_cookbook/sky_rl/) | RL training on Harbor tasks using SkyRL. |

harbor_cookbook/sky_rl/README.md

@@ -0,0 +1,31 @@
+# sky_rl
+
+RL training on Harbor tasks using [SkyRL](https://github.com/NovaSky-AI/SkyRL).
+
+This directory is a pointer. The full integration lives in the SkyRL repo:
+
+**[SkyRL/examples/train_integrations/harbor](https://github.com/NovaSky-AI/SkyRL/tree/main/examples/train_integrations/harbor)**
+
+## Quick start
+
+Set credentials:
+
+```bash
+export WANDB_API_KEY=your_wandb_api_key
+export DAYTONA_API_KEY=your_daytona_api_key
+```
+
+Prepare datasets (run from the SkyRL root):
+
+```bash
+uv run examples/train_integrations/harbor/prepare_harbor_dataset.py \
+    --dataset open-thoughts/CodeContests
+```
+
+Launch training:
+
+```bash
+bash examples/train_integrations/harbor/run_codecontest.sh
+```
+
+See the [SkyRL README](https://github.com/NovaSky-AI/SkyRL) for full setup instructions.