signal_log: outcomes for every setup, event dedup, interned news; fix over-scan, dead outlook, panel OPPOSE bias

- seed an advisory outcome on every setup row; same-setup re-logs within 60 min
  are DUPLICATE rows (advisory_event_id); resolver rebuilds bar streams across gaps
- headlines/events interned into news_snapshots (DB 667 MB -> 262 MB); readers
  use signals_with_news / read_news and mode=ro (immutable=1 missed WAL rows)
- post-gate truth columns: gate_reason, actionable, cleaned_warnings, scan_kind,
  config_fingerprint; SELL-hour gates fail closed
- telegram: breach rescan reuses this bar's report; grade dropped from alert
  fingerprint (upgrade-only re-alert)
- market_outlook: hour-bucket dedup (old rule skipped alternate hours), skip heartbeats
- agent_panel: macro-anchored OPPOSE guard (opposed trades were +30R over 3 weeks)
- analyze_signal_log --stored-candles/--parity; backfill + news migration scripts
- tests: Module 25 (analyze_signal_log) + 27 (observability); 429 total

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FC4s6VCURFte4dub4xKxYL

agent_panel.py

@@ -253,9 +253,13 @@ Weigh the takes into ONE consensus on whether to act on the signal:
 "AGREE" (the panel backs the trade), "OPPOSE" (the panel is against it),
 or "NEUTRAL" (genuinely split or low conviction). The risk manager and
 contrarian have intentionally defensive roles; their objections are not
-automatic vetoes. Do not count repeated versions of the same warning as
-independent evidence. Weigh role relevance, evidence quality, and
-confidence rather than averaging blindly.
+automatic vetoes: "OPPOSE" requires that the macro analyst opposes, or
+that the technical analyst opposes while the macro analyst is not
+supportive. When only the defensive roles object, or the macro analyst
+supports the trade, the most the panel can say is "NEUTRAL". Do not
+count repeated versions
+of the same warning as independent evidence. Weigh role relevance,
+evidence quality, and confidence rather than averaging blindly.
 Base the verdict and rationale ONLY on the takes given — do not add
 outside analysis.
 Confidence scale (0-100): 80-100 the panel clearly leans one way; 50-79
@@ -674,6 +678,15 @@ def _panel_jobs(
     )
 
 
+# NOTE (2026-09 audit): the TTL reuse key differs from the exact key
+# only by the contrarian's bar timestamp, and every other block (price,
+# ATR-normalized candles, indicator readings, drifting entry/stop) moves
+# each closed bar — so TTL_REUSE never fired live (30/30 attaches MISS).
+# That is the documented, test-locked decision ("changed evidence never
+# inherits a direction-only cached verdict"); spend is bounded by
+# max_panels_per_day instead. Relaxing the identity is an owner call.
+
+
 def _panel_payload_hash(
     jobs: Tuple[Tuple[str, str, Dict[str, Any]], ...],
     ignore_bar_timestamp: bool = False,
@@ -747,11 +760,48 @@ def run_panel(report: "SignalReport",
     if verdict not in _VALID_VERDICTS or confidence is None:
         return None
     rationale = str(reply.get("rationale", "")).strip()[:240]
+    verdict, confidence, rationale = _apply_oppose_guard(
+        verdict, confidence, rationale, takes)
     return PanelVerdict(verdict=verdict, confidence=confidence,
                         rationale=rationale, takes=takes,
                         created_ts=time.time(), payload_hash=payload_hash)
 
 
+# Deterministic backstop for the chair (ADVISORY-ONLY, no gate reads it).
+#
+# Evidence (2026-09 signal-log audit, 133 live verdicts, 107 with a
+# replayed outcome): the contrarian and risk personas opposed 117/133
+# alerts each and the technical persona 88/133 — they object to the
+# trend extension the engine already discounted — so the chair said
+# OPPOSE 73% of the time while the OPPOSED trades made +30.1R (PF 2.6).
+# The macro persona was the only informative voice: macro=support
+# trades won 88% (+0.56R mean, n=69); macro=oppose won 25%; macro=neutral
+# 38%. With this rule the OPPOSE bucket becomes the weakest one
+# (n=29, +0.08R mean, 41% win) instead of the best. Small sample, one
+# bullish episode — re-score with analyze_signal_log --stored-candles
+# after more history before tightening further.
+#
+# Rule: OPPOSE stands only if the macro analyst opposes, or the technical
+# analyst opposes while the macro analyst is not supportive. Otherwise
+# the verdict is NEUTRAL (confidence capped below 50).
+
+
+def _apply_oppose_guard(verdict: str, confidence: float, rationale: str,
+                        takes: List[PersonaTake]):
+    if verdict != "OPPOSE":
+        return verdict, confidence, rationale
+    stance = {t.persona: t.stance for t in takes}
+    macro = stance.get("macro")
+    technical = stance.get("technical")
+    if macro == "oppose":
+        return verdict, confidence, rationale
+    if technical == "oppose" and macro != "support":
+        return verdict, confidence, rationale
+    note = ("The big-picture view does not object, so the panel stays "
+            "neutral rather than against. ")
+    return "NEUTRAL", min(float(confidence), 49.0), (note + rationale)[:240]
+
+
 # ── Cache, budget, attach ────────────────────────────────────────────
 
 _state_lock = threading.Lock()