Fix scoring/recommendation correctness and calibration

Triggered by CNC showing "LONG (High Confidence)" with SHORT reasoning
and no long setup.

- A: recommendation action + reasoning are ticker-level and identical
  on both setups; reasoning always matches the shown action
- B: recommended_action only picks a direction with a tradeable setup;
  strong bias with no setup (e.g. price at ATH) → NEUTRAL with an
  explanatory reason instead of a fake LONG_HIGH
- C: confidence is a directional-agreement model — opposing signals push
  it below 50 (SHORT on a 92-technical/99-momentum stock ~0%, not 55%)
- D: fundamental score requires >=2 real metrics (market-cap-only no
  longer yields a high score)
- E: RSI score peaks at healthy momentum (~60) and penalizes
  overbought/oversold extremes instead of treating RSI 90 as maximal
- F: fundamentals chain merges fields across providers (FMP market cap
  + Finnhub P/E) instead of stopping at the first with any field
- NEUTRAL label: "No Clear Setup" (covers untradeable-bias case)

Scores recompute on next scan/scoring run; C and E shift score
distributions intentionally.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

app/services/rr_scanner_service.py

@@ -202,6 +202,7 @@ async def scan_ticker(
                     detected_at=now,
                 ))
 
+    available_directions = {s.direction for s in setups}
     enhanced_setups: list[TradeSetup] = []
     for setup in setups:
         try:
@@ -213,6 +214,7 @@ async def scan_ticker(
                 sr_levels=sr_levels,
                 sentiment_classification=sentiment_classification,
                 atr_value=atr_value,
+                available_directions=available_directions,
             )
             enhanced_setups.append(enhanced)
         except Exception: