Add chart-pattern entry archetype (XAU_CP) — disabled by default

Third entry archetype: completion of classical chart patterns (double
bottom/top, H&S top / inverse H&S, bull/bear flag) — the tight canon
with the strongest documented stats. New chart_patterns.py detector
module (pure functions, ATR-unit geometry, closed-bar slices only,
first-close-beyond trigger discipline so a breakout fires exactly
once and never repaints).

Pipeline step 10 in analyze_from_dataframes: fills only empty setup
slots, allows weak-composite F grades (normal at reversal completion)
but inherits session/day blocks, mirrors MTF-opposition + SELL
vol/hour + M5 protections. Geometry: SL = pattern anchor -/+ 0.5 ATR
(min $8), TP1 = measured move, $9 spread gate, trailing exit does the
real work. Strategy tag XAU_CP.

cp_enabled defaults to False everywhere — per-TF adoption happens in
pair_signals/xauusd.py only after the standard validation rule passes.
Backtester: --cp / --cp-patterns flags to test the candidate, XAU_CP
tag recognition.

Suite: 183/183 (21 new tests: detectors, trigger discipline,
invalidation, gates, pipeline, default-off safety).

Claude-Session: https://claude.ai/code/session_015kby7M9JwpYi8NQT2yoxAi

config.py

@@ -274,6 +274,34 @@ class XauStrategyConfig:
     # Price must have touched EMA21/KC-mid within this many bars.
     m5_pullback_touch_bars: int = 3
 
+    # ── Chart-pattern entry (XAU_CP) ──────────────────────────────
+    # Third entry archetype: completion of a classical chart pattern
+    # (see chart_patterns.py for the pattern set and design contract).
+    # Defaults are textbook geometry, NOT tuned values. Disabled by
+    # default — per-TF adoption happens in pair_signals/xauusd.py only
+    # after the pattern book passes the standard validation rule
+    # (positive R both halves of ≥12mo, PF ≥ 1.3, $0.30 spread,
+    # trailing exits, next-open fills).
+    cp_enabled: bool = False
+    cp_patterns: List[str] = field(default_factory=lambda: [
+        "inv_hs", "hs_top", "double_bottom", "double_top",
+        "bull_flag", "bear_flag",
+    ])
+    cp_lookback: int = 72          # bars scanned for pattern structure
+    cp_swing_window: int = 3       # bars each side to confirm a swing
+    cp_recency_bars: int = 20      # last extreme must be this fresh
+    cp_min_sep_bars: int = 8       # min bars between double extremes
+    cp_tolerance_atr: float = 0.5  # double top/bottom level match tol
+    cp_min_height_atr: float = 1.5   # pattern height floor (noise gate)
+    cp_max_height_atr: float = 8.0   # pattern height ceiling
+    cp_hs_head_min_atr: float = 0.5  # head must exceed shoulders by this
+    cp_hs_shoulder_tol_atr: float = 1.0  # shoulder level match tol
+    cp_flag_pole_atr: float = 3.0    # min pole size
+    cp_flag_pole_bars: int = 12      # pole measured over ≤ this many bars
+    cp_flag_min_bars: int = 3        # flag consolidation length bounds
+    cp_flag_max_bars: int = 12
+    cp_flag_retrace: tuple = (0.1, 0.5)  # flag depth as fraction of pole
+
 
 @dataclass
 class FilterConfig: