chore: update

Author: Lawhy

README.md

@@ -8,13 +8,15 @@ RL environment abstraction for [Strands Agents](https://github.com/strands-agent
 
 ## Features
 
-This package standardizes agent environments by treating each `env.step()` as a full agent loop (prompt → (tool_call, tool_response)* → response), not a single model call or tool call. Built on [strands](https://github.com/strands-agents/sdk-python) agent loop and [`strands-sglang`](https://github.com/horizon-rl/strands-sglang) for RL training.
+This package standardizes agent environments by treating each `env.step()` as a **full agent loop**, not a single model call or tool call. Built on [strands](https://github.com/strands-agents/sdk-python) agent loop and [`strands-sglang`](https://github.com/horizon-rl/strands-sglang) for RL training.
 
 - **Define environments easily** — subclass `Environment` and implement tools as `@tool` functions
 - **Capture token-level observations** — token-in/token-out trajectories for on-policy RL training (SGLang backend)
 - **Plug in reward functions** — evaluate agent outputs with custom `RewardFunction`
 - **Run benchmarks** — `Evaluator` with flexible environment setup, metric customization, and resume
 
+> An agent loop can be defined as `(prompt → (tool_call, tool_response+)* → response)`
+
 ## Install
 
 ```bash