feat(bot): 5-phase strategy upgrade — edge neto, families, GNews priority, regimes

Phase 1 — Edge neto real (paper.py, bayesian.py, risk/manager.py, db.py):
- Trade records now store edge_gross, edge_net, prior_prob, final_prob,
  mid_price, spread_estimate, commission, family_key
- edge_net = edge_gross - SPREAD_ESTIMATE(0.02) - COMMISSION_RATE(0.02)
  NOTE: both constants are heuristics, not exact Polymarket exchange costs
- Execution gate changed from edge_gross > MIN_EDGE to edge_net > regime_min_edge

Phase 2 — Market families (polymarket.py):
- market_family_key(market) groups related markets:
    texas-republican-2026, fed-april-2026, openai-2026, etc.
- At most 1 trade per family per cycle; occupied_families propagated via main.py
- Family key logged on every TRADE and SKIP line

Phase 3 — GNews priority (news.py, bayesian.py, main.py):
- NewsClient.get_freshness() returns 1.0/0.75/0.40/0.10 by cache age
- gnews_priority(market, news) = uncertainty × volume_score × freshness
- Politics markets sorted by priority DESC before eval so best markets get
  the 5-query/cycle GNews budget first

Phase 4 — Regime min-edge by category/horizon (bayesian.py):
- politics >60d → 0.12, 30-60d → 0.10, <30d → 0.08
- tech / crypto/finance → 0.10
- All thresholds applied to edge_net (not edge_gross)

Phase 5 — Observability (bayesian.py, main.py):
- Structured skip labels: SKIP_UNSUPPORTED, SKIP_NO_SIGNALS,
  SKIP_PRIOR_EXTREME, SKIP_FAMILY, SKIP_GNEWS_PRIORITY, SKIP_EDGE_NET
- TRADE lines now include family_key, edge_gross, edge_net, regime_min, days
- schema.sql: 8 new cols on trades, 7 new cols on signals (via ALTER TABLE IF NOT EXISTS)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

bot/data/db.py

@@ -33,13 +33,21 @@ class Database:
             await conn.execute("""
                 INSERT INTO trades (
                     id, market_id, question, direction, size_usdc,
-                    entry_price, shares, fee_usdc, net_cost, timestamp, reasoning, paper
-                ) VALUES ($1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12)
+                    entry_price, shares, fee_usdc, net_cost, timestamp, reasoning, paper,
+                    edge_gross, edge_net, prior_prob, final_prob,
+                    mid_price, spread_estimate, commission, family_key
+                ) VALUES (
+                    $1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12,
+                    $13,$14,$15,$16,$17,$18,$19,$20
+                )
                 ON CONFLICT (id) DO NOTHING
             """,
                 trade.id, trade.market_id, trade.question, trade.direction,
                 trade.size_usdc, trade.entry_price, trade.shares, trade.fee_usdc,
                 trade.net_cost, trade.timestamp, trade.reasoning, trade.paper,
+                # Phase 1 fields
+                trade.edge_gross, trade.edge_net, trade.prior_prob, trade.final_prob,
+                trade.mid_price, trade.spread_estimate, trade.commission, trade.family_key,
             )
 
     async def save_daily_metrics(self, metrics: dict) -> None:
@@ -69,6 +77,18 @@ class Database:
             )
             return {r["market_id"]: float(r["total"]) for r in rows}
 
+    async def get_open_families(self) -> set[str]:
+        """Return the set of family_key values from all open positions.
+
+        Used at startup to rebuild occupied_families from DB state so the
+        family-deduplication logic survives pod restarts.
+        """
+        async with self._pool.acquire() as conn:
+            rows = await conn.fetch(
+                "SELECT DISTINCT family_key FROM trades WHERE family_key IS NOT NULL"
+            )
+            return {r["family_key"] for r in rows if r["family_key"]}
+
     async def get_recent_trades(self, limit: int = 100) -> list[dict]:
         async with self._pool.acquire() as conn:
             rows = await conn.fetch(