fix(graph): resolve instrument identity to stop wrong-company hallucination

Agents had no ground-truth ticker→company mapping, so the market analyst
could pattern-match a price chart to the wrong company (e.g. TOTDY read as
"TotalEnergies"), and every downstream agent inherited the bad framing.

Resolve identity once at run start via a cached, fail-open yfinance lookup
and inject company/sector/exchange into the shared instrument context that
all twelve agents consume, with an explicit do-not-substitute instruction.
Resolution runs on both the propagate() and CLI entry points.

Also replaces the bare "Continue" message-clear placeholder, which some
OpenAI-compatible providers interpreted as the user task, with a
context-anchored placeholder carrying the resolved identity and date.

#814 #888

tradingagents/agents/risk_mgmt/neutral_debator.py

@@ -1,4 +1,7 @@
-from tradingagents.agents.utils.agent_utils import get_language_instruction
+from tradingagents.agents.utils.agent_utils import (
+    get_instrument_context_from_state,
+    get_language_instruction,
+)
 
 
 def create_neutral_debator(llm):
@@ -14,6 +17,7 @@ def create_neutral_debator(llm):
         sentiment_report = state["sentiment_report"]
         news_report = state["news_report"]
         fundamentals_report = state["fundamentals_report"]
+        instrument_context = get_instrument_context_from_state(state)
 
         trader_decision = state["trader_investment_plan"]
 
@@ -23,6 +27,7 @@ def create_neutral_debator(llm):
 
 Your task is to challenge both the Aggressive and Conservative Analysts, pointing out where each perspective may be overly optimistic or overly cautious. Use insights from the following data sources to support a moderate, sustainable strategy to adjust the trader's decision:
 
+{instrument_context}
 Market Research Report: {market_research_report}
 Social Media Sentiment Report: {sentiment_report}
 Latest World Affairs Report: {news_report}