diff --git a/docs/source/en/guided_tour.md b/docs/source/en/guided_tour.md
index 5a0d13d..2da7095 100644
--- a/docs/source/en/guided_tour.md
+++ b/docs/source/en/guided_tour.md
@@ -23,15 +23,12 @@ In this guided visit, you will learn how to build an agent, how to run it, and h
 
 To initialize a minimal agent, you need at least these two arguments:
 
-- An text-generation model to power your agent - because the agent is different from a simple LLM, it is a system that uses a LLM as its engine.
-- A list of tools from which the agent pick tools to execute
+- `model`, a text-generation model to power your agent - because the agent is different from a simple LLM, it is a system that uses a LLM as its engine. You can use any of these options:
+    - [`TransformersModel`] takes a pre-initialized `transformers` pipeline to run inference on your local machine using `transformers`.
+    - [`HfApiModel`] leverages a `huggingface_hub.InferenceClient` under the hood.
+    - [`LiteLLMModel`] lets you call 100+ different models through [LiteLLM](https://docs.litellm.ai/)!
 
-For your model, you can use any of these options:
-- [`TransformersModel`] takes a pre-initialized `transformers` pipeline to run inference on your local machine using `transformers`.
-- [`HfApiModel`] leverages a `huggingface_hub.InferenceClient` under the hood.
-- We also provide [`LiteLLMModel`], which lets you call 100+ different models through [LiteLLM](https://docs.litellm.ai/)!
-
-You will also need a `tools` argument which accepts a list of `Tools` - it can be an empty list. You can also add the default toolbox on top of your `tools` list by defining the optional argument `add_base_tools=True`.
+- `tools`, A list of `Tools` that the agent can use to solve the task. It can be an empty list. You can also add the default toolbox on top of your `tools` list by defining the optional argument `add_base_tools=True`.
 
 Once you have these two arguments, `tools` and `model`,  you can create an agent and run it. 
 
@@ -69,7 +66,7 @@ This gives you at the end of the agent run:
 ```text
 'Hugging Face – Blog'
 ```
-The execution will stop at any code trying to perform an illegal operation or if there is a regular Python error with the code generated by the agent. You can also use E2B code executor instead of a local Python interpreter by passing `use_e2b_executor=True` upon agent initialization.
+The execution will stop at any code trying to perform an illegal operation or if there is a regular Python error with the code generated by the agent. You can also use [E2B code executor](https://e2b.dev/docs#what-is-e2-b) instead of a local Python interpreter by first [setting the `E2B_API_KEY` environment variable](https://e2b.dev/dashboard?tab=keys) and then passing `use_e2b_executor=True` upon agent initialization.
 
 > [!WARNING]
 > The LLM can generate arbitrary code that will then be executed: do not add any unsafe imports!
@@ -336,4 +333,4 @@ You can also use this `reset=False` argument to keep the conversation going in a
 For more in-depth usage, you will then want to check out our tutorials:
 - [the explanation of how our code agents work](./tutorials/secure_code_execution)
 - [this guide on how to build good agents](./tutorials/building_good_agents).
-- [the in-depth guide for tool usage](./tutorials/building_good_agents).
\ No newline at end of file
+- [the in-depth guide for tool usage](./tutorials/building_good_agents).