fix(agents): ground the Trader in the technical market report

- the Trader received only the digested investment plan, so its entry / stop /
  sizing levels were not anchored to real price structure (ATR, support and
  resistance, current price)
- inject the market report and instruct the Trader to take concrete price levels
  from it and direction/strategy from the plan; when the market analyst was not
  selected the report is empty, so the section and grounding note are omitted #1167

tests/test_structured_agent_prompts.py

@@ -52,6 +52,7 @@ def test_trader_prompt_states_constraint():
     create_trader(llm)({
         "company_of_interest": "NVDA",
         "investment_plan": "**Recommendation**: Buy",
+        "market_report": "Current price $189.5; ATR 4.2.",
     })
     assert NO_EXTERNAL_TOOLS in _prompt_text(captured["prompt"])
 

tests/test_structured_agents.py

@@ -131,6 +131,7 @@ def _make_trader_state():
     return {
         "company_of_interest": "NVDA",
         "investment_plan": "**Recommendation**: Buy\n**Rationale**: ...\n**Strategic Actions**: ...",
+        "market_report": "Current price $189.5; 14-day ATR 4.2; support $178, resistance $196.",
     }
 
 
@@ -200,6 +201,31 @@ class TestTraderAgent:
         prompt = captured["prompt"]
         assert any("Proposed Investment Plan" in m["content"] for m in prompt)
 
+    def test_prompt_includes_market_report_for_price_levels(self):
+        # #1167: the Trader must see the technical market report so entry/stop
+        # levels are grounded in real price structure, not just the digested plan.
+        captured = {}
+        trader = create_trader(_structured_trader_llm(captured))
+        trader(_make_trader_state())
+        user = " ".join(m["content"] for m in captured["prompt"] if m["role"] == "user")
+        system = " ".join(m["content"] for m in captured["prompt"] if m["role"] == "system")
+        assert "Technical Market Report:" in user
+        assert "14-day ATR 4.2" in user            # the actual report content reached the Trader
+        assert "support $178, resistance $196" in user
+        assert "Ground concrete price levels" in system
+
+    def test_empty_market_report_omits_the_section_and_grounding(self):
+        # #1167: when the market analyst wasn't selected the report is empty, so
+        # don't tell the Trader to ground levels in a report it doesn't have.
+        captured = {}
+        state = _make_trader_state()
+        state["market_report"] = ""
+        create_trader(_structured_trader_llm(captured))(state)
+        text = " ".join(m["content"] for m in captured["prompt"])
+        assert "Technical Market Report:" not in text
+        assert "Ground concrete price levels" not in text
+        assert "Proposed Investment Plan" in text  # still present
+
     def test_falls_back_to_freetext_when_structured_unavailable(self):
         plain_response = (
             "**Action**: Sell\n\nGuidance cut hits margins.\n\n"

tradingagents/agents/trader/trader.py

@@ -25,6 +25,23 @@ def create_trader(llm):
         company_name = state["company_of_interest"]
         instrument_context = get_instrument_context_from_state(state)
         investment_plan = state["investment_plan"]
+        # The research plan digests the debate but loses exact price structure;
+        # give the Trader the technical market report so entry/stop levels are
+        # grounded in real ATR / support-resistance / current price (#1167). The
+        # report is empty when the user did not select the market analyst, so
+        # only offer it (and the grounding instruction) when it has content.
+        market_report = (state["market_report"] or "").strip()
+
+        if market_report:
+            grounding = (
+                "Ground concrete price levels (entry, stop-loss, position sizing) in the technical "
+                "market report's price structure -- current price, support/resistance, ATR, and "
+                "volatility -- and use the research plan for direction and strategy. "
+            )
+            report_section = f"Technical Market Report:\n{market_report}\n\n"
+        else:
+            grounding = ""
+            report_section = ""
 
         messages = [
             {
@@ -32,7 +49,7 @@ def create_trader(llm):
                 "content": (
                     "You are a trading agent analyzing market data to make investment decisions. "
                     "Based on your analysis, provide a specific recommendation to buy, sell, or hold. "
-                    "Anchor your reasoning in the analysts' reports and the research plan. "
+                    + grounding
                     + NO_EXTERNAL_TOOLS
                     + get_language_instruction()
                 ),
@@ -40,12 +57,11 @@ def create_trader(llm):
             {
                 "role": "user",
                 "content": (
-                    f"Based on a comprehensive analysis by a team of analysts, here is an investment "
+                    f"Here is the research team's investment plan for {company_name}. "
-                    f"plan tailored for {company_name}. {instrument_context} This plan incorporates "
+                    f"{instrument_context}\n\n"
-                    f"insights from current technical market trends, macroeconomic indicators, and "
+                    f"{report_section}"
-                    f"social media sentiment. Use this plan as a foundation for evaluating your next "
+                    f"Proposed Investment Plan:\n{investment_plan}\n\n"
-                    f"trading decision.\n\nProposed Investment Plan: {investment_plan}\n\n"
+                    f"Make an informed, strategic trading decision."
-                    f"Leverage these insights to make an informed and strategic decision."
                 ),
             },
         ]