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+"""
+OpenAI Agents SDK — Forensic Reporting Example
+================================================
+
+Demonstrates how to add forensic reporting to an OpenAI Agents SDK agent
+using Agent Forensics. Records every decision, tool call, and LLM interaction,
+then generates a forensic report and auto-classifies failure patterns.
+
+Setup:
+    pip install openai-agents agent-forensics
+
+Usage:
+    python openai_agents_forensics_example.py
+
+Target repo: openai/openai-agents-python → examples/ or cookbook/
+PR title: "Add forensic reporting example with agent-forensics"
+"""
+
+import asyncio
+from agents import Agent, Runner, function_tool
+from agent_forensics import Forensics
+
+
+# --- Tools ---
+
+@function_tool
+def search_products(query: str) -> str:
+    """Search the product catalog for items matching the query."""
+    products = [
+        {"name": "Logitech M750", "price": 45.00, "in_stock": True},
+        {"name": "Apple Magic Mouse", "price": 99.00, "in_stock": True},
+        {"name": "Razer DeathAdder", "price": 69.00, "in_stock": False},
+    ]
+    results = [p for p in products if query.lower() in p["name"].lower()]
+    if not results:
+        results = products  # Return all if no match
+    return str(results)
+
+
+@function_tool
+def purchase(product_name: str, quantity: int = 1) -> str:
+    """Purchase a product by name."""
+    if "razer" in product_name.lower():
+        return '{"error": "Out of stock"}'
+    return f'{{"status": "confirmed", "product": "{product_name}", "qty": {quantity}, "order_id": "ORD-001"}}'
+
+
+# --- Main ---
+
+async def main():
+    # 1. Initialize forensics
+    f = Forensics(session="openai-agents-demo", agent="shopping-agent")
+
+    # 2. Create agent with forensics hooks (one line!)
+    agent = Agent(
+        name="shopping-agent",
+        instructions=(
+            "You help users buy products. Search for products first, "
+            "then purchase the one that best matches the user's request."
+        ),
+        tools=[search_products, purchase],
+        hooks=f.openai_agents(),  # ← This is all you need
+    )
+
+    # 3. Run the agent
+    print("Running agent...")
+    result = await Runner.run(agent, "Buy me a wireless mouse under $50")
+    print(f"Agent output: {result.final_output}\n")
+
+    # 4. Generate forensic report
+    print("=" * 60)
+    print("FORENSIC REPORT")
+    print("=" * 60)
+    print(f"Events recorded: {len(f.events())}")
+    print()
+
+    # 5. Auto-classify failures
+    failures = f.classify()
+    if failures:
+        print(f"Failures detected: {len(failures)}")
+        for fail in failures:
+            print(f"  [{fail['severity']}] {fail['type']}: {fail['description']}")
+    else:
+        print("No failures detected.")
+
+    print()
+
+    # 6. Save report
+    f.save_markdown(".")
+    print(f"Report saved: forensics-report-openai-agents-demo.md")
+
+    # 7. Extract replay config (for deterministic reproduction)
+    config = f.get_replay_config()
+    if config["model_config"]:
+        print(f"Model config: {config['model_config']}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())