fix(agents): stop debate openers from rebutting a nonexistent argument

- the first speaker in each debate round received an empty opponent response,
  yet the prompt demanded a rebuttal, so models fabricated the other side
- substitute an explicit opening marker when an opponent has not spoken, across
  all five debators (bull, bear, and the three risk analysts) #1176

tests/test_debate_opening.py

@@ -0,0 +1,111 @@
+"""The first speaker in each debate must not rebut a nonexistent argument (#1176).
+
+Each debate round's opening speaker receives an empty opponent response; the
+prompt used to interpolate it into a "refute the opponent" instruction, so models
+fabricated the other side's position. All five debators (bull, bear, and the
+three risk analysts) now substitute an explicit opening marker when the opponent
+has not spoken, and pass a real argument through unchanged.
+"""
+from __future__ import annotations
+
+from unittest.mock import MagicMock
+
+import pytest
+
+from tradingagents.agents.researchers.bear_researcher import create_bear_researcher
+from tradingagents.agents.researchers.bull_researcher import create_bull_researcher
+from tradingagents.agents.risk_mgmt.aggressive_debator import create_aggressive_debator
+from tradingagents.agents.risk_mgmt.conservative_debator import create_conservative_debator
+from tradingagents.agents.risk_mgmt.neutral_debator import create_neutral_debator
+from tradingagents.agents.utils.agent_utils import opponent_argument_or_opening
+
+_REPORTS = {
+    "company_of_interest": "AAPL", "asset_type": "stock",
+    "market_report": "m", "sentiment_report": "s",
+    "news_report": "n", "fundamentals_report": "f",
+}
+
+
+def _capturing_llm(captured: dict):
+    llm = MagicMock()
+    llm.invoke.side_effect = lambda prompt: (
+        captured.__setitem__("prompt", prompt) or MagicMock(content="argument")
+    )
+    return llm
+
+
+def _investment_state(current_response):
+    return {
+        **_REPORTS,
+        "count": 0,
+        "investment_debate_state": {
+            "history": "", "bull_history": "", "bear_history": "",
+            "current_response": current_response, "count": 0,
+        },
+    }
+
+
+def _risk_state(**responses):
+    base = {
+        "current_aggressive_response": "", "current_conservative_response": "",
+        "current_neutral_response": "", "history": "", "aggressive_history": "",
+        "conservative_history": "", "neutral_history": "", "count": 0,
+    }
+    base.update(responses)
+    return {**_REPORTS, "trader_investment_plan": "plan", "risk_debate_state": base}
+
+
+# --- shared helper ----------------------------------------------------------
+
+@pytest.mark.unit
+def test_helper_marks_empty_and_passes_through():
+    assert "has not spoken yet" in opponent_argument_or_opening("", "bear analyst")
+    assert opponent_argument_or_opening("  real point ", "bear") == "real point"
+
+
+# --- researchers ------------------------------------------------------------
+
+@pytest.mark.unit
+@pytest.mark.parametrize(
+    "factory,opponent",
+    [(create_bull_researcher, "bear"), (create_bear_researcher, "bull")],
+)
+def test_researcher_opening_has_no_phantom_opponent(factory, opponent):
+    captured = {}
+    factory(_capturing_llm(captured))(_investment_state(""))
+    assert "has not spoken yet" in captured["prompt"]
+
+
+@pytest.mark.unit
+def test_researcher_passes_real_opponent_argument():
+    captured = {}
+    state = _investment_state("Bear Analyst: valuation is stretched")
+    create_bull_researcher(_capturing_llm(captured))(state)
+    assert "valuation is stretched" in captured["prompt"]
+    assert "has not spoken yet" not in captured["prompt"]
+
+
+# --- risk debators ----------------------------------------------------------
+
+@pytest.mark.unit
+@pytest.mark.parametrize(
+    "factory", [create_aggressive_debator, create_conservative_debator, create_neutral_debator]
+)
+def test_risk_opening_has_no_phantom_opponent(factory):
+    captured = {}
+    factory(_capturing_llm(captured))(_risk_state())
+    # Both opponent slots were empty -> two opening markers, no fabricated args.
+    assert captured["prompt"].count("has not spoken yet") == 2
+
+
+@pytest.mark.unit
+def test_risk_passes_real_opponent_arguments():
+    captured = {}
+    state = _risk_state(
+        current_conservative_response="Conservative Analyst: trim risk",
+        current_neutral_response="Neutral Analyst: hold steady",
+    )
+    create_aggressive_debator(_capturing_llm(captured))(state)
+    assert "trim risk" in captured["prompt"]
+    assert "hold steady" in captured["prompt"]
+    assert "has not spoken yet" not in captured["prompt"]

tradingagents/agents/researchers/bear_researcher.py

@@ -1,6 +1,7 @@
 from tradingagents.agents.utils.agent_utils import (
     get_instrument_context_from_state,
     get_language_instruction,
+    opponent_argument_or_opening,
 )
 
 
@@ -10,7 +11,9 @@ def create_bear_researcher(llm):
         history = investment_debate_state.get("history", "")
         bear_history = investment_debate_state.get("bear_history", "")
 
-        current_response = investment_debate_state.get("current_response", "")
+        current_response = opponent_argument_or_opening(
+            investment_debate_state.get("current_response", ""), "bull analyst"
+        )
         market_research_report = state["market_report"]
         sentiment_report = state["sentiment_report"]
         news_report = state["news_report"]

tradingagents/agents/researchers/bull_researcher.py

@@ -1,6 +1,7 @@
 from tradingagents.agents.utils.agent_utils import (
     get_instrument_context_from_state,
     get_language_instruction,
+    opponent_argument_or_opening,
 )
 
 
@@ -10,7 +11,9 @@ def create_bull_researcher(llm):
         history = investment_debate_state.get("history", "")
         bull_history = investment_debate_state.get("bull_history", "")
 
-        current_response = investment_debate_state.get("current_response", "")
+        current_response = opponent_argument_or_opening(
+            investment_debate_state.get("current_response", ""), "bear analyst"
+        )
         market_research_report = state["market_report"]
         sentiment_report = state["sentiment_report"]
         news_report = state["news_report"]

tradingagents/agents/risk_mgmt/aggressive_debator.py

@@ -1,6 +1,7 @@
 from tradingagents.agents.utils.agent_utils import (
     get_instrument_context_from_state,
     get_language_instruction,
+    opponent_argument_or_opening,
 )
 
 
@@ -10,8 +11,12 @@ def create_aggressive_debator(llm):
         history = risk_debate_state.get("history", "")
         aggressive_history = risk_debate_state.get("aggressive_history", "")
 
-        current_conservative_response = risk_debate_state.get("current_conservative_response", "")
-        current_neutral_response = risk_debate_state.get("current_neutral_response", "")
+        current_conservative_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_conservative_response", ""), "conservative analyst"
+        )
+        current_neutral_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_neutral_response", ""), "neutral analyst"
+        )
 
         market_research_report = state["market_report"]
         sentiment_report = state["sentiment_report"]

tradingagents/agents/risk_mgmt/conservative_debator.py

@@ -1,6 +1,7 @@
 from tradingagents.agents.utils.agent_utils import (
     get_instrument_context_from_state,
     get_language_instruction,
+    opponent_argument_or_opening,
 )
 
 
@@ -10,8 +11,12 @@ def create_conservative_debator(llm):
         history = risk_debate_state.get("history", "")
         conservative_history = risk_debate_state.get("conservative_history", "")
 
-        current_aggressive_response = risk_debate_state.get("current_aggressive_response", "")
-        current_neutral_response = risk_debate_state.get("current_neutral_response", "")
+        current_aggressive_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_aggressive_response", ""), "aggressive analyst"
+        )
+        current_neutral_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_neutral_response", ""), "neutral analyst"
+        )
 
         market_research_report = state["market_report"]
         sentiment_report = state["sentiment_report"]

tradingagents/agents/risk_mgmt/neutral_debator.py

@@ -1,6 +1,7 @@
 from tradingagents.agents.utils.agent_utils import (
     get_instrument_context_from_state,
     get_language_instruction,
+    opponent_argument_or_opening,
 )
 
 
@@ -10,8 +11,12 @@ def create_neutral_debator(llm):
         history = risk_debate_state.get("history", "")
         neutral_history = risk_debate_state.get("neutral_history", "")
 
-        current_aggressive_response = risk_debate_state.get("current_aggressive_response", "")
-        current_conservative_response = risk_debate_state.get("current_conservative_response", "")
+        current_aggressive_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_aggressive_response", ""), "aggressive analyst"
+        )
+        current_conservative_response = opponent_argument_or_opening(
+            risk_debate_state.get("current_conservative_response", ""), "conservative analyst"
+        )
 
         market_research_report = state["market_report"]
         sentiment_report = state["sentiment_report"]

tradingagents/agents/utils/agent_utils.py

@@ -65,6 +65,20 @@ def get_language_instruction() -> str:
     return f" Write your entire response in {lang}."
 
 
+def opponent_argument_or_opening(text: str, opponent: str) -> str:
+    """Opponent's latest argument, or an explicit opening marker when empty.
+
+    The first speaker in each debate round receives an empty opponent response;
+    interpolating it into a "refute the opponent" prompt makes the model
+    fabricate the other side's position. Returning a clear "has not spoken yet"
+    marker instead lets it open with its own case (#1176).
+    """
+    text = (text or "").strip()
+    if text:
+        return text
+    return f"(The {opponent} has not spoken yet — open the debate with your own case.)"
+
+
 def _clean_identity_value(value: Any) -> str | None:
     """Return a trimmed string, or None for empty / placeholder-ish values."""
     if not isinstance(value, str):