diff --git a/src/main.py b/src/main.py
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--- /dev/null
+++ b/src/main.py
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+"""
+Deep Agents from Scratch example.
+This script demonstrates a simple agent that searches the web and writes results to files.
+It uses the `deep-agents-from-scratch` package as required by the assignment.
+"""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+
+# Ensure dependencies are available
+try:
+    from deep_agents_from_scratch.research_tools import tavily_search, think_tool
+except Exception as e:  # pragma: no cover - defensive
+    raise RuntimeError("deep-agents-from-scratch not installed") from e
+
+from langchain.agents import create_agent
+from langchain.chat_models import init_chat_model
+from deep_agents_from_scratch.state import DeepAgentState
+from deep_agents_from_scratch.file_tools import ls, read_file, write_file
+
+# Simple prompt for the agent
+SYSTEM_PROMPT = """
+You are a research assistant. Use web search to gather information and store results in files.
+After each search, reflect on what you found.
+"""
+
+model = init_chat_model(model="anthropic:claude-sonnet-4-20250514", temperature=0)
+
+# Tools available to the agent
+TOOLS = [tavily_search, think_tool, ls, read_file, write_file]
+
+agent = create_agent(
+    model,
+    TOOLS,
+    system_prompt=SYSTEM_PROMPT,
+    state_schema=DeepAgentState,
+)
+
+def run_query(query: str) -> None:
+    """Run a single query and print the resulting messages."""
+    result = agent.invoke({"messages": [{"role": "user", "content": query}]})
+    for msg in result["messages"]:
+        print(msg.content)
+
+if __name__ == "__main__":  # pragma: no cover - entry point
+    import argparse
+
+    parser = argparse.ArgumentParser(description="Run deep agent example")
+    parser.add_argument("query", help="Query to search for")
+    args = parser.parse_args()
+    run_query(args.query)