feat: add analysis-only crypto asset mode

cli/main.py

@@ -505,6 +505,10 @@ def get_user_selections():
         )
     )
     selected_ticker = get_ticker()
+    asset_type = detect_asset_type(selected_ticker)
+    console.print(
+        f"[green]Detected asset type:[/green] {asset_type.value}"
+    )
 
     # Step 2: Analysis date
     default_date = datetime.datetime.now().strftime("%Y-%m-%d")
@@ -523,7 +527,7 @@ def get_user_selections():
             "Step 3: Analysts Team", "Select your LLM analyst agents for the analysis"
         )
     )
-    selected_analysts = select_analysts()
+    selected_analysts = select_analysts(asset_type)
     console.print(
         f"[green]Selected analysts:[/green] {', '.join(analyst.value for analyst in selected_analysts)}"
     )
@@ -577,6 +581,7 @@ def get_user_selections():
 
     return {
         "ticker": selected_ticker,
+        "asset_type": asset_type.value,
         "analysis_date": analysis_date,
         "analysts": selected_analysts,
         "research_depth": selected_research_depth,
@@ -989,6 +994,7 @@ def run_analysis():
 
         # Add initial messages
         message_buffer.add_message("System", f"Selected ticker: {selections['ticker']}")
+        message_buffer.add_message("System", f"Detected asset type: {selections['asset_type']}")
         message_buffer.add_message(
             "System", f"Analysis date: {selections['analysis_date']}"
         )
@@ -1011,7 +1017,9 @@ def run_analysis():
 
         # Initialize state and get graph args with callbacks
         init_agent_state = graph.propagator.create_initial_state(
-            selections["ticker"], selections["analysis_date"]
+            selections["ticker"],
+            selections["analysis_date"],
+            asset_type=selections["asset_type"],
         )
         # Pass callbacks to graph config for tool execution tracking
         # (LLM tracking is handled separately via LLM constructor)