diff --git a/README.md b/README.md
index 3a13357..f6baa58 100644
--- a/README.md
+++ b/README.md
@@ -1,33 +1,54 @@
 # LangGraph Code Review Agent
 
-This repository implements a LangGraph agent that performs a code review on a Python function.  The graph consists of three nodes:
+## Overview
 
-1. **draft_review** – generates an initial review.
-2. **reflect** – a critic that scores the review on four criteria (PEP8, type hints, edge cases, naming) and decides whether a rewrite is required.
-3. **rewrite** – rewrites the weakest part of the review.
+This repository contains a LangGraph agent that performs a code review on a given Python function. The agent:
 
-The graph runs for a maximum of `max_rounds` (default 2).  The demo can be executed with `python -m main`.
+1. Generates an initial draft review.
+2. Critiques the draft on four criteria (PEP8, type hints, edge cases, naming).
+3. If the review needs revision, rewrites the weakest part up to a maximum number of rounds.
 
 ## Requirements
 
 ```text
 langgraph>=0.2.0
 langchain-openai>=0.2.0
-python-dotenv>=1.0.0
+python-dotenv
 ```
 
+Install dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+## Running the Demo
+
+```bash
+python main.py
+```
+
+The demo uses a simple `sort_numbers` function. The output shows the final review, the scores, and the verdict.
+
 ## Usage
 
-```bash
-# Install dependencies
-pip install -r requirements.txt
+You can import the `run_demo` function or use the graph directly in your own code.
 
-# Run the demo
-python -m main
+```python
+from main import graph, CodeReviewState
+
+state = CodeReviewState(
+    code="def foo(x): return x+1",
+    draft_review="",
+    criteria_scores={},
+    weakest_criterion="",
+    verdict="",
+    round=0,
+    max_rounds=2,
+)
+result = await graph.ainvoke(state)
 ```
 
-The demo uses a simple `sort_numbers` function.  The output shows the final review, the scores for each criterion, the verdict, and the number of rounds performed.
-
 ## Environment Variables
 
-The agent uses OpenAI.  Set the `OPENAI_API_KEY` environment variable before running.
+The agent uses OpenAI. Set `OPENAI_API_KEY` in your environment or in a `.env` file.