Update agent.md

docs/design_pattern/agent.md

@@ -9,12 +9,6 @@ nav_order: 6
 
 Agent is a powerful design pattern in which nodes can take dynamic actions based on the context.
 
-The core of building **high-performance** and **reliable** agents boils down to:
-
-1. **Input Context:** Provide *relevant, minimal context.* For example, rather than including an entire chat history, retrieve the most relevant via [RAG](./rag.md). Even with larger context windows, LLMs still fall victim to ["lost in the middle"](https://arxiv.org/abs/2307.03172), overlooking mid-prompt content.
-
-2. **Action Space:** Provide *a well-structured and unambiguous* set of actions—avoiding overlap like separate `read_databases` or  `read_csvs`. Instead, import CSVs into the database and then use one parameterized (e.g., table name) or programmable action (e.g., via SQL) to query data.
-
 <div align="center">
   <img src="https://github.com/the-pocket/PocketFlow/raw/main/assets/agent.png?raw=true" width="350"/>
 </div>
@@ -49,6 +43,13 @@ parameters:
 ```"""
 ```
 
+The core of building **high-performance** and **reliable** agents boils down to:
+
+1. **Input Context:** Provide *relevant, minimal context.* For example, rather than including an entire chat history, retrieve the most relevant via [RAG](./rag.md). Even with larger context windows, LLMs still fall victim to ["lost in the middle"](https://arxiv.org/abs/2307.03172), overlooking mid-prompt content.
+
+2. **Action Space:** Provide *a well-structured and unambiguous* set of actions—avoiding overlap like separate `read_databases` or  `read_csvs`. Instead, import CSVs into the database and then use one parameterized (e.g., table name) or programmable action (e.g., via SQL) to query data.
+
+
 ### Example: Search Agent
 
 This agent:
@@ -130,4 +131,4 @@ search - "decide" >> decide  # Loop back
 
 flow = Flow(start=decide)
 flow.run({"query": "Who won the Nobel Prize in Physics 2024?"})
-```
+```