chore: remove dead functions and write-only state (no behaviour change)

Zero callers anywhere (tests included), verified by grep/AST:
- dashboard_publisher.DashboardPublisher.publish_all (run_cycle inlines both publishes)
- signal_log.SignalLogger.advance_with_bars (the backfill script uses
  backfill_seeds / resolve_from_store / reseed_unresolvable) and the never-read
  SignalLogger.path property plus its write-only self._path
- llm_client.reset_llm_client (tests reset the singleton by assignment)
- market_outlook._last_run_ts, residue of the old "now - last < 3600" dedup;
  _last_run_hour (the UTC hour bucket) is the live key
- news_engine FundamentalContext.event_impact_on_pairs: written once, read by
  nothing; its only feeder NewsEngine._get_affected_pairs and that helper's
  unit test go with it
- position_sizing.LIVE_DEPTH_BARS (referenced only by its own docstring, which
  now states the depths inline), the unused Iterable import and the unused
  atr_ok parameter of _fill_geometry
- analyze_signal_log: unused `field` import and the unused `rows` parameter of
  persona_scorecard / news_outcome_buckets (both read the DB directly)

The two backfill/label scripts' --db help text now names the config.json
setting it actually falls back to.

Suite: 463 passed, 0 failed (one test removed with its subject).

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0156YhogLytzj9P2iH1skGbL

analyze_signal_log.py

@@ -67,7 +67,7 @@ import math
 import os
 import sqlite3
 import sys
-from dataclasses import dataclass, field
+from dataclasses import dataclass
 from datetime import datetime, timedelta, timezone
 from typing import Dict, List, Optional, Sequence, Tuple
 
@@ -754,8 +754,7 @@ def _fmt_r(r: Optional[float]) -> str:
     return "  n/a " if r is None else f"{r:+.2f}R"
 
 
-def persona_scorecard(rows: Sequence[LogRow], events: Sequence[SignalEvent],
-                      db_path: str) -> List[dict]:
+def persona_scorecard(events: Sequence[SignalEvent], db_path: str) -> List[dict]:
     """Per persona × stance: n, mean R and win rate of the underlying
     event (needs panel_takes_json — read straight from the DB)."""
     by_row = _row_index(events)
@@ -921,8 +920,7 @@ def news_extremes(rows: Sequence[LogRow], streams: Dict[str, List[dict]],
     }
 
 
-def news_outcome_buckets(rows: Sequence[LogRow],
-                         events: Sequence[SignalEvent],
+def news_outcome_buckets(events: Sequence[SignalEvent],
                          db_path: str) -> List[dict]:
     """Resolved events bucketed by (direction, news bucket, macro stance).
 
@@ -1306,13 +1304,13 @@ def main(argv: Optional[Sequence[str]] = None) -> int:
         print_report(rows, events, panel, hit)
         print_stored_books(events)
         print("\n── Persona scorecard (stance × event outcome) " + "─" * 22)
-        for p in persona_scorecard(rows, events, args.db):
+        for p in persona_scorecard(events, args.db):
             print(f"  {p['persona']:11} {p['stance']:8} n={p['n']:3d} "
                   f"mean {p['mean_r']:+.3f}R  win {100 * p['win_rate']:.0f}%")
         if args.news:
             print_news(news_lead_lag(rows, streams),
                        news_extremes(rows, streams),
-                       news_outcome_buckets(rows, events, args.db))
+                       news_outcome_buckets(events, args.db))
         print_parity(parity_report(rows))
         if args.csv:
             export_csv(events, args.csv)