refactor: one name per decision in the state and its log

- the Research Manager's plan and the Portfolio Manager's decision live only in investment_plan and final_trade_decision; the debate states no longer copy them as judge_decision
- the saved state log writes the Trader's plan as trader_investment_plan, its state key
- the report tree, the final display and the live CLI read the decisions from those fields

cli/display.py

@@ -404,8 +404,8 @@ def display_complete_report(final_state):
             research.append(("Bull Researcher", debate["bull_history"]))
         if debate.get("bear_history"):
             research.append(("Bear Researcher", debate["bear_history"]))
-        if debate.get("judge_decision"):
+        if final_state.get("investment_plan"):
-            research.append(("Research Manager", debate["judge_decision"]))
+            research.append(("Research Manager", final_state["investment_plan"]))
         if research:
             console.print(Panel("[bold]II. Research Team Decision[/bold]", border_style="magenta"))
             for title, content in research:
@@ -431,10 +431,10 @@ def display_complete_report(final_state):
             for title, content in risk_reports:
                 console.print(Panel(Markdown(content), title=title, border_style="blue", padding=(1, 2)))
 
-        # V. Portfolio Manager Decision
+    # V. Portfolio Manager Decision
-        if risk.get("judge_decision"):
+    if final_state.get("final_trade_decision"):
-            console.print(Panel("[bold]V. Portfolio Manager Decision[/bold]", border_style="green"))
+        console.print(Panel("[bold]V. Portfolio Manager Decision[/bold]", border_style="green"))
-            console.print(Panel(Markdown(risk["judge_decision"]), title="Portfolio Manager", border_style="blue", padding=(1, 2)))
+        console.print(Panel(Markdown(final_state["final_trade_decision"]), title="Portfolio Manager", border_style="blue", padding=(1, 2)))
 
 
 def update_research_team_status(status):

cli/run.py

@@ -253,7 +253,7 @@ def run_analysis(checkpoint: bool | None = None, portfolio=None):
                     debate_state = chunk["investment_debate_state"]
                     bull_hist = debate_state.get("bull_history", "").strip()
                     bear_hist = debate_state.get("bear_history", "").strip()
-                    judge = debate_state.get("judge_decision", "").strip()
+                    judge = (chunk.get("investment_plan") or "").strip()
 
                     # Only update status when there's actual content
                     if bull_hist or bear_hist:
@@ -288,7 +288,7 @@ def run_analysis(checkpoint: bool | None = None, portfolio=None):
                     agg_hist = risk_state.get("aggressive_history", "").strip()
                     con_hist = risk_state.get("conservative_history", "").strip()
                     neu_hist = risk_state.get("neutral_history", "").strip()
-                    judge = risk_state.get("judge_decision", "").strip()
+                    judge = (chunk.get("final_trade_decision") or "").strip()
 
                     if agg_hist:
                         if message_buffer.agent_status.get("Aggressive Analyst") != "completed":

tests/test_cli_display.py

@@ -48,9 +48,9 @@ def _state(ticker, final="评级: 买入"):
         "fundamentals_report": "基本面", "investment_plan": "计划",
         "trader_investment_plan": "交易计划", "final_trade_decision": final, "final_rating": "REVIEW",
         "investment_debate_state": {"bull_history": "", "bear_history": "", "history": "",
-                                    "current_response": "", "judge_decision": "", "count": 0},
+                                    "current_response": "", "count": 0},
         "risk_debate_state": {"aggressive_history": "", "conservative_history": "",
-                              "neutral_history": "", "history": "", "judge_decision": "",
+                              "neutral_history": "", "history": "",
                               "latest_speaker": "", "current_aggressive_response": "",
                               "current_conservative_response": "", "current_neutral_response": "",
                               "count": 0},
@@ -76,6 +76,19 @@ def test_the_state_log_keeps_non_ascii_readable(tmp_path):
     assert json.loads(written)  # still valid JSON
 
 
+@pytest.mark.unit
+def test_the_state_log_names_each_field_as_the_state_does(tmp_path):
+    """One name per field: the Trader's plan under its state key, and no second
+    copy of the managers' decisions under the debate states."""
+    _bare_graph(tmp_path)._log_state("2026-09-01", _state("NVDA"))
+
+    logged = json.loads(next(tmp_path.rglob("full_states_log*.json")).read_text(encoding="utf-8"))
+    assert logged["trader_investment_plan"] == "交易计划"
+    assert logged["investment_plan"] == "计划"
+    assert "trader_investment_decision" not in logged
+    assert "judge_decision" not in json.dumps(logged)
+
+
 @pytest.mark.unit
 def test_the_live_display_does_not_scroll_the_terminal():
     """A layout taller than the window makes rich redraw by scrolling, which

tests/test_memory_log.py

@@ -74,7 +74,6 @@ def _make_pm_state(past_context=""):
             "aggressive_history": "",
             "conservative_history": "",
             "neutral_history": "",
-            "judge_decision": "",
             "current_aggressive_response": "",
             "current_conservative_response": "",
             "current_neutral_response": "",
@@ -906,13 +905,13 @@ class TestLegacyRemoval:
             "fundamentals_report": "",
             "investment_debate_state": {
                 "bull_history": "", "bear_history": "", "history": "",
-                "current_response": "", "judge_decision": "",
+                "current_response": "",
             },
             "investment_plan": "",
             "trader_investment_plan": "",
             "risk_debate_state": {
                 "aggressive_history": "", "conservative_history": "",
-                "neutral_history": "", "history": "", "judge_decision": "",
+                "neutral_history": "", "history": "",
                 "current_aggressive_response": "", "current_conservative_response": "",
                 "current_neutral_response": "", "count": 1, "latest_speaker": "",
             },

tests/test_portfolio_context.py

@@ -139,11 +139,11 @@ def test_decision_agents_see_the_portfolio(module, factory, monkeypatch):
         "news_report": "N", "fundamentals_report": "F", "investment_plan": "P",
         "trader_investment_plan": "T", "past_context": "",
         "portfolio_context": "PORTFOLIO_BLOCK_MARKER",
-        "investment_debate_state": {"history": "", "judge_decision": "", "count": 0},
+        "investment_debate_state": {"history": "", "count": 0},
         "risk_debate_state": {"history": "", "latest_speaker": "", "count": 0,
                               "aggressive_history": "", "conservative_history": "", "neutral_history": "",
                               "current_aggressive_response": "", "current_conservative_response": "",
-                              "current_neutral_response": "", "judge_decision": ""},
+                              "current_neutral_response": ""},
     }
     node = getattr(mod, factory)(_LLM())
     node(state)

tests/test_prompt_integrity.py

@@ -74,11 +74,11 @@ def test_a_report_that_was_never_produced_says_so(module, factory):
         "market_report": "RSI 61, price 178.", "sentiment_report": "", "news_report": "",
         "fundamentals_report": "", "investment_plan": "P", "trader_investment_plan": "T",
         "investment_debate_state": {"bull_history": "", "bear_history": "", "history": "",
-                                    "current_response": "", "judge_decision": "", "count": 0},
+                                    "current_response": "", "count": 0},
         "risk_debate_state": {"history": "", "latest_speaker": "", "count": 0,
                               "aggressive_history": "", "conservative_history": "", "neutral_history": "",
                               "current_aggressive_response": "", "current_conservative_response": "",
-                              "current_neutral_response": "", "judge_decision": ""},
+                              "current_neutral_response": ""},
     }
     getattr(mod, factory)(_LLM())(state)
 

tests/test_rating_integrity.py

@@ -194,11 +194,11 @@ def test_a_decision_prompt_states_the_shape_of_its_answer(module, factory, must_
         "news_report": "N", "fundamentals_report": "F", "investment_plan": "P",
         "trader_investment_plan": "T", "past_context": "", "portfolio_context": "",
         "investment_debate_state": {"bull_history": "b", "bear_history": "r", "history": "h",
-                                    "current_response": "", "judge_decision": "", "count": 2},
+                                    "current_response": "", "count": 2},
         "risk_debate_state": {"history": "h", "latest_speaker": "", "count": 3,
                               "aggressive_history": "", "conservative_history": "", "neutral_history": "",
                               "current_aggressive_response": "", "current_conservative_response": "",
-                              "current_neutral_response": "", "judge_decision": ""},
+                              "current_neutral_response": ""},
     }
     getattr(mod, factory)(_LLM())(state)
 

tests/test_reporting.py

@@ -13,9 +13,11 @@ def _state():
     return {
         "market_report": "MKT",
         "news_report": "NEWS",
-        "investment_debate_state": {"judge_decision": "RM PLAN"},
+        "investment_debate_state": {"bull_history": "BULL"},
+        "investment_plan": "RM PLAN",
         "trader_investment_plan": "TRADE",
-        "risk_debate_state": {"judge_decision": "PM DECISION"},
+        "risk_debate_state": {"neutral_history": "NEUTRAL"},
+        "final_trade_decision": "PM DECISION",
     }
 
 

tests/test_structured_agent_prompts.py

@@ -72,7 +72,7 @@ def test_research_manager_prompt_states_constraint():
         "company_of_interest": "NVDA",
         "investment_debate_state": {
             "history": "h", "bull_history": "b", "bear_history": "r",
-            "current_response": "", "judge_decision": "", "count": 1,
+            "current_response": "", "count": 1,
         },
     })
     assert NO_EXTERNAL_TOOLS in _prompt_text(captured["prompt"])

tests/test_structured_agents.py

@@ -292,7 +292,6 @@ def _make_rm_state():
             "bull_history": "Bull says...",
             "bear_history": "Bear says...",
             "current_response": "",
-            "judge_decision": "",
             "count": 1,
         },
     }

tradingagents/agents/managers/portfolio_manager.py

@@ -86,7 +86,6 @@ Write these sections, in this order, starting with the rating on its own line:
             final_rating = parse_rating(final_trade_decision)
 
         new_risk_debate_state = {
-            "judge_decision": final_trade_decision,
             "history": risk_debate_state["history"],
             "aggressive_history": risk_debate_state["aggressive_history"],
             "conservative_history": risk_debate_state["conservative_history"],

tradingagents/agents/managers/research_manager.py

@@ -59,7 +59,6 @@ Write these sections, in this order, starting with the recommendation on its own
         )
 
         new_investment_debate_state = {
-            "judge_decision": investment_plan,
             "history": investment_debate_state.get("history", ""),
             "bear_history": investment_debate_state.get("bear_history", ""),
             "bull_history": investment_debate_state.get("bull_history", ""),

tradingagents/agents/state.py

@@ -14,7 +14,6 @@ class InvestDebateState(TypedDict):
     ]
     history: Annotated[str, "Conversation history"]
     current_response: Annotated[str, "Latest response"]
-    judge_decision: Annotated[str, "Final judge decision"]
     count: Annotated[int, "Length of the current conversation"]
 
 
@@ -40,7 +39,6 @@ class RiskDebateState(TypedDict):
     current_neutral_response: Annotated[
         str, "Latest response by the neutral analyst"
     ]
-    judge_decision: Annotated[str, "Judge's decision"]
     count: Annotated[int, "Length of the current conversation"]
 
 

tradingagents/graph/propagation.py

@@ -41,7 +41,6 @@ class Propagator:
                     "bear_history": "",
                     "history": "",
                     "current_response": "",
-                    "judge_decision": "",
                     "count": 0,
                 }
             ),
@@ -55,7 +54,6 @@ class Propagator:
                     "current_aggressive_response": "",
                     "current_conservative_response": "",
                     "current_neutral_response": "",
-                    "judge_decision": "",
                     "count": 0,
                 }
             ),

tradingagents/graph/trading_graph.py

@@ -359,17 +359,13 @@ class TradingAgentsGraph:
                 "current_response": final_state["investment_debate_state"][
                     "current_response"
                 ],
-                "judge_decision": final_state["investment_debate_state"][
-                    "judge_decision"
-                ],
             },
-            "trader_investment_decision": final_state["trader_investment_plan"],
+            "trader_investment_plan": final_state["trader_investment_plan"],
             "risk_debate_state": {
                 "aggressive_history": final_state["risk_debate_state"]["aggressive_history"],
                 "conservative_history": final_state["risk_debate_state"]["conservative_history"],
                 "neutral_history": final_state["risk_debate_state"]["neutral_history"],
                 "history": final_state["risk_debate_state"]["history"],
-                "judge_decision": final_state["risk_debate_state"]["judge_decision"],
             },
             "investment_plan": final_state["investment_plan"],
             "final_trade_decision": final_state["final_trade_decision"],

tradingagents/reporting.py

@@ -52,10 +52,10 @@ def write_report_tree(final_state: dict, ticker: str, save_path) -> Path:
             research_dir.mkdir(exist_ok=True)
             (research_dir / "bear.md").write_text(debate["bear_history"], encoding="utf-8")
             research_parts.append(("Bear Researcher", debate["bear_history"]))
-        if debate.get("judge_decision"):
+        if final_state.get("investment_plan"):
             research_dir.mkdir(exist_ok=True)
-            (research_dir / "manager.md").write_text(debate["judge_decision"], encoding="utf-8")
+            (research_dir / "manager.md").write_text(final_state["investment_plan"], encoding="utf-8")
-            research_parts.append(("Research Manager", debate["judge_decision"]))
+            research_parts.append(("Research Manager", final_state["investment_plan"]))
         if research_parts:
             content = "\n\n".join(f"### {name}\n{text}" for name, text in research_parts)
             sections.append(f"## II. Research Team Decision\n\n{content}")
@@ -88,12 +88,12 @@ def write_report_tree(final_state: dict, ticker: str, save_path) -> Path:
             content = "\n\n".join(f"### {name}\n{text}" for name, text in risk_parts)
             sections.append(f"## IV. Risk Management Team Decision\n\n{content}")
 
-        # 5. Portfolio Manager
+    # 5. Portfolio Manager
-        if risk.get("judge_decision"):
+    if final_state.get("final_trade_decision"):
-            portfolio_dir = save_path / "5_portfolio"
+        portfolio_dir = save_path / "5_portfolio"
-            portfolio_dir.mkdir(exist_ok=True)
+        portfolio_dir.mkdir(exist_ok=True)
-            (portfolio_dir / "decision.md").write_text(risk["judge_decision"], encoding="utf-8")
+        (portfolio_dir / "decision.md").write_text(final_state["final_trade_decision"], encoding="utf-8")
-            sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{risk['judge_decision']}")
+        sections.append(f"## V. Portfolio Manager Decision\n\n### Portfolio Manager\n{final_state['final_trade_decision']}")
 
     # Write consolidated report
     header = f"# Trading Analysis Report: {ticker}\n\nGenerated: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"