diff --git a/apps/paper_trader/backtest_sim.py b/apps/paper_trader/backtest_sim.py
index 8be2dcd..5a0066c 100644
--- a/apps/paper_trader/backtest_sim.py
+++ b/apps/paper_trader/backtest_sim.py
@@ -351,310 +351,6 @@ async def _refresh_snapshot(
         raise
 
 
-# ── Overlay backtest support ──────────────────────────────────────────
-
-
-def _is_overlay_config(config_path: str) -> bool:
-    """Return True if config_path is an overlay spec (has 'books' key)."""
-    import json
-    try:
-        data = json.loads(Path(config_path).read_text())
-        return "books" in data and "allocations" in data
-    except Exception:
-        return False
-
-
-def _resolve_book_experiment_config(book: dict) -> str | None:
-    """Resolve the experiment config path for an overlay book entry."""
-    # Explicit field
-    explicit = book.get("experiment_config")
-    if explicit and Path(explicit).exists():
-        return explicit
-
-    # Infer from equity_csv filename
-    csv_path = book.get("equity_csv", "")
-    if csv_path:
-        name = Path(csv_path).stem  # e.g. "return_max_long_v6.221_equity"
-        # Strip common suffixes
-        for suffix in ("_equity", "_train", "_valid", "_test"):
-            if name.endswith(suffix):
-                name = name[: -len(suffix)]
-                break
-        candidate = f"configs/experiments/{name}.json"
-        if Path(candidate).exists():
-            return candidate
-
-    return None
-
-
-def _overlay_books_are_runnable(overlay_config_path: str) -> bool:
-    """Check if all books in an overlay config have resolvable experiment configs."""
-    import json
-    try:
-        spec = json.loads(Path(overlay_config_path).read_text())
-        for book in spec.get("books", []):
-            csv_path = book.get("equity_csv")
-            if csv_path and Path(csv_path).exists():
-                continue
-            if _resolve_book_experiment_config(book) is None:
-                return False
-        return True
-    except Exception:
-        return False
-
-
-def _rebase_equity_slice(
-    df,
-    *,
-    initial_equity: float,
-):
-    """Recompute equity within a requested window so the first kept day starts flat."""
-    df = df.sort_values("date").copy()
-    df["daily_return"] = df["equity"].astype(float).pct_change().fillna(0.0)
-    equity = float(initial_equity)
-    rebased: list[float] = []
-    for ret in df["daily_return"].astype(float):
-        equity *= 1.0 + float(ret)
-        rebased.append(equity)
-    df["equity"] = rebased
-    return df[["date", "equity", "daily_return"]]
-
-
-def _summarize_book_curve(df, *, initial_equity: float) -> dict[str, float]:
-    """Return a paper-backtest-like summary from a rebased equity curve."""
-    returns = df["daily_return"].astype(float)
-    final_equity = float(df["equity"].iloc[-1])
-    return_pct = (final_equity / float(initial_equity) - 1.0) * 100.0
-
-    peak = float(initial_equity)
-    max_dd_pct = 0.0
-    for equity in df["equity"].astype(float):
-        peak = max(peak, float(equity))
-        drawdown_pct = (peak - float(equity)) / peak * 100.0 if peak > 0 else 0.0
-        max_dd_pct = max(max_dd_pct, drawdown_pct)
-
-    if len(returns) >= 2 and float(returns.std()) > 0:
-        sharpe = float(returns.mean() / returns.std() * math.sqrt(252.0))
-    else:
-        sharpe = 0.0
-
-    return {
-        "return_pct": return_pct,
-        "final_equity": final_equity,
-        "max_dd_pct": max_dd_pct,
-        "trade_count": 0,
-        "win_rate": 0.0,
-        "sharpe": sharpe,
-    }
-
-
-def _load_overlay_book_curve_from_spec(
-    book: dict,
-    *,
-    capital: float,
-    start_date: dt.date,
-    end_date: dt.date,
-):
-    """Load a frozen overlay input curve from equity_csv and rebase it to the requested window."""
-    from libs.backtest.overlay import load_equity_curve_csv
-
-    csv_path = book.get("equity_csv")
-    if not csv_path or not Path(csv_path).exists():
-        return None
-
-    df = load_equity_curve_csv(csv_path)
-    df = df[(df["date"] >= start_date) & (df["date"] <= end_date)].copy()
-    if df.empty:
-        return None
-
-    rebased = _rebase_equity_slice(df, initial_equity=capital)
-    summary = _summarize_book_curve(rebased, initial_equity=capital)
-    return {
-        "curve": rebased,
-        "summary": summary,
-        "source": "equity_csv",
-    }
-
-
-def run_overlay_backtest_sync(
-    overlay_config_path: str,
-    capital: float,
-    start_date: dt.date,
-    end_date: dt.date,
-    console=None,
-) -> dict[str, Any]:
-    """Run an overlay backtest: execute each book strategy, then combine by regime."""
-    import json
-    import pandas as pd
-    from libs.backtest.overlay import build_overlay_curve, summarize_overlay_curve
-
-    spec = json.loads(Path(overlay_config_path).read_text())
-    overlay_name = spec.get("overlay_name", Path(overlay_config_path).stem)
-    allocations = spec["allocations"]
-
-    # ── Run each book strategy ────────────────────────────────────────
-    book_results: list[dict[str, Any]] = []
-    curves: dict[str, pd.DataFrame] = {}
-
-    replay_mode = "frozen_equity_csv"
-
-    for book in spec["books"]:
-        label = book["label"]
-        loaded = _load_overlay_book_curve_from_spec(
-            book,
-            capital=capital,
-            start_date=start_date,
-            end_date=end_date,
-        )
-        if loaded is not None:
-            if console:
-                source_name = Path(book["equity_csv"]).stem
-                console.print(f"  [dim]Book '{label}':[/] {source_name} [dim](frozen equity_csv)[/]")
-            curves[label] = loaded["curve"]
-            book_results.append(
-                {
-                    "label": label,
-                    "result": {
-                        "session_name": f"{overlay_name}__{label}",
-                        "summary": loaded["summary"],
-                        "equity_curve": [
-                            {"date": row.date, "equity": row.equity}
-                            for row in loaded["curve"].itertuples(index=False)
-                        ],
-                        "trades": [],
-                    },
-                    "source": loaded["source"],
-                }
-            )
-            continue
-
-        replay_mode = "rerun_books"
-        exp_config = _resolve_book_experiment_config(book)
-        if exp_config is None:
-            raise ValueError(
-                f"Overlay '{overlay_name}': book '{label}' has neither a usable equity_csv nor a resolvable experiment config. "
-                f"Add 'equity_csv' or 'experiment_config' to the book entry."
-            )
-
-        if console:
-            console.print(f"  [dim]Book '{label}':[/] {Path(exp_config).stem} [dim](rerun)[/]")
-
-        result = run_backtest_session_sync(
-            session_name=f"{overlay_name}__{label}",
-            config_path=exp_config,
-            initial_equity=capital,
-            start_date=start_date,
-            end_date=end_date,
-        )
-        book_results.append({"label": label, "result": result, "source": "rerun"})
-
-        eq = result.get("equity_curve", [])
-        if eq:
-            df = pd.DataFrame(eq)
-            df["date"] = pd.to_datetime(df["date"]).dt.date
-            df["equity"] = df["equity"].astype(float)
-            curves[label] = _rebase_equity_slice(df[["date", "equity"]], initial_equity=capital)
-
-    if not curves:
-        raise ValueError(f"Overlay '{overlay_name}': no book produced equity curves")
-
-    # ── Compute regime for each trading day ───────────────────────────
-    regimes = _compute_overlay_regimes(spec, start_date, end_date)
-
-    # ── Combine using overlay logic ───────────────────────────────────
-    overlay_curve = build_overlay_curve(
-        curves=curves,
-        allocations=allocations,
-        regimes_by_date=regimes,
-        initial_equity=capital,
-    )
-
-    summary = summarize_overlay_curve(overlay_curve, initial_equity=capital)
-
-    # Convert overlay equity curve to standard format
-    equity_curve = [
-        {"date": row.date, "equity": row.overlay_equity}
-        for row in overlay_curve.itertuples(index=False)
-    ]
-
-    # Aggregate trade count across books
-    total_trades = sum(
-        br["result"]["summary"]["trade_count"] for br in book_results
-    )
-
-    return {
-        "session_name": overlay_name,
-        "config_path": overlay_config_path,
-        "initial_equity": capital,
-        "is_overlay": True,
-        "overlay_replay_mode": replay_mode,
-        "equity_curve": equity_curve,
-        "trades": [],
-        "book_results": book_results,
-        "allocations": allocations,
-        "regime_day_counts": summary.get("regime_day_counts", {}),
-        "summary": {
-            "return_pct": summary["return_pct"],
-            "final_equity": summary["final_equity"],
-            "max_dd_pct": summary["max_dd_pct"],
-            "trade_count": total_trades,
-            "win_rate": 0.0,
-            "sharpe": summary["sharpe"],
-        },
-    }
-
-
-def _compute_overlay_regimes(
-    spec: dict,
-    start_date: dt.date,
-    end_date: dt.date,
-) -> dict[dt.date, str]:
-    """Compute macro regime for each trading day using the regime_source config.
-
-    Uses _build_merged_snapshot_store to get a full-period store with macro data,
-    covering the paper backtest date range (not just the original snapshot period).
-    """
-    from apps.backtester.run import _build_merged_snapshot_store, load_manifest, resolve_config
-    from libs.backtest.allocator import _macro_regime_state
-    from libs.backtest.overlay import load_merged_store_from_snapshot_dir
-    from libs.common.config import get_settings
-
-    regime_source = spec.get("regime_source", {})
-    config_path = regime_source.get("config_path")
-    if not config_path:
-        return {}
-
-    manifest = load_manifest(config_path)
-    config = resolve_config(manifest)
-
-    raw_snapshot_dir = regime_source.get("snapshot_dir")
-    if raw_snapshot_dir and (
-        (Path(raw_snapshot_dir) / "train.parquet").exists()
-        or (Path(raw_snapshot_dir) / "test.parquet").exists()
-    ):
-        settings = get_settings()
-        store = load_merged_store_from_snapshot_dir(
-            raw_snapshot_dir,
-            oracle_url=settings.stock_oracle_url,
-            db_dsn=settings.postgres_dsn,
-        )
-    else:
-        try:
-            store = _build_merged_snapshot_store(
-                manifest,
-                config,
-                snapshot_dir_override=raw_snapshot_dir,
-            )
-        except FileNotFoundError:
-            store = _build_merged_snapshot_store(manifest, config, snapshot_dir_override=None)
-    store = store.slice_by_date_range(start_date, end_date)
-
-    regimes: dict[dt.date, str] = {}
-    for date in store.all_trading_days():
-        regimes[date] = _macro_regime_state(config, store.get_macro_for_date(date))
-    return regimes
-
-
 def run_backtest(
     configs: list[str],
     capital: float,
@@ -691,8 +387,6 @@ def run_backtest(
 
     # Check if snapshots need refresh (async pipeline, run before sync backtest)
     for config_path in configs:
-        if _is_overlay_config(config_path):
-            continue  # overlay books handle their own snapshots
         from apps.backtester.run import load_manifest, resolve_config
         manifest = load_manifest(config_path)
         config = resolve_config(manifest)
@@ -723,27 +417,15 @@ def run_backtest(
     results = []
     for config_path in configs:
         session_name = Path(config_path).stem
-
-        if _is_overlay_config(config_path):
-            if console:
-                console.print(f"\n[bold magenta]Running overlay:[/] {session_name}")
-            result = run_overlay_backtest_sync(
-                overlay_config_path=config_path,
-                capital=capital,
-                start_date=start_date,
-                end_date=end_date,
-                console=console,
-            )
-        else:
-            if console:
-                console.print(f"\n[bold cyan]Running:[/] {session_name}")
-            result = run_backtest_session_sync(
-                session_name=session_name,
-                config_path=config_path,
-                initial_equity=capital,
-                start_date=start_date,
-                end_date=end_date,
-            )
+        if console:
+            console.print(f"\n[bold cyan]Running:[/] {session_name}")
+        result = run_backtest_session_sync(
+            session_name=session_name,
+            config_path=config_path,
+            initial_equity=capital,
+            start_date=start_date,
+            end_date=end_date,
+        )
 
         results.append(result)
 
diff --git a/apps/paper_trader/cli.py b/apps/paper_trader/cli.py
index 6d382c9..0acc69f 100644
--- a/apps/paper_trader/cli.py
+++ b/apps/paper_trader/cli.py
@@ -311,7 +311,6 @@ def _resolve_rank_configs(start: int, end: int) -> list[str]:
     """Load strategies ranked start..end from leaderboard by SQS score.
 
     start/end are 1-based inclusive. e.g. (1, 5) = top 5, (20, 40) = rank 20-40.
-    Overlays are excluded; use --overlay to run them explicitly.
     """
     import json
 
@@ -322,7 +321,6 @@ def _resolve_rank_configs(start: int, end: int) -> list[str]:
 
     registry = json.loads(registry_path.read_text())
     ranked: list[str] = []
-    skipped_overlays: list[str] = []
     entries = sorted(
         (
             e for e in registry.get("entries", [])
@@ -334,10 +332,6 @@ def _resolve_rank_configs(start: int, end: int) -> list[str]:
     )
 
     for e in entries:
-        is_overlay = e.get("strategy_family") == "overlay" or e.get("overlay_common_window_summary") is not None
-        if is_overlay:
-            skipped_overlays.append(e["experiment_name"])
-            continue
         if e.get("trade_count", 0) <= 0 or e.get("valid_trade_count", 0) <= 0:
             continue
         name = e["experiment_name"]
@@ -345,15 +339,6 @@ def _resolve_rank_configs(start: int, end: int) -> list[str]:
         if Path(cfg_path).exists():
             ranked.append(cfg_path)
 
-    if skipped_overlays:
-        labels = ", ".join(skipped_overlays[:5])
-        if len(skipped_overlays) > 5:
-            labels += ", ..."
-        _console.print(
-            "[yellow]Skipping overlay leaderboard entries for `--top/--rank` "
-            f"(use `--overlay` to run them explicitly): {labels}[/]"
-        )
-
     # 1-based inclusive slice
     return ranked[start - 1 : end]
 
@@ -363,8 +348,6 @@ def cmd_backtest(args: argparse.Namespace) -> None:
     import datetime as dt
 
     configs = args.configs or []
-    if args.overlays:
-        configs.extend(args.overlays)
     if args.top:
         configs = _resolve_rank_configs(1, args.top) + configs
     if args.rank:
@@ -378,7 +361,7 @@ def cmd_backtest(args: argparse.Namespace) -> None:
             _console.print("[red]ERROR: --rank format: N or START-END (e.g. 5 or 20-40)[/]")
             sys.exit(1)
     if not configs:
-        _console.print("[red]ERROR: Specify --config, --overlay, --top, or --rank[/]")
+        _console.print("[red]ERROR: Specify --config, --top, or --rank[/]")
         sys.exit(1)
 
     for cfg in configs:
@@ -590,8 +573,6 @@ def main() -> None:
     p.add_argument("--config", "-c", action="append",
                    dest="configs", metavar="PATH",
                    help="Config path (repeat for multiple strategies)")
-    p.add_argument("--overlay", action="append", dest="overlays", metavar="PATH",
-                   help="Overlay config path (repeat for multiple)")
     p.add_argument("--top", "-t", type=int, default=None, metavar="N",
                    help="Use top N strategies from leaderboard (by SQS score)")
     p.add_argument("--rank", default=None, metavar="START-END",
diff --git a/apps/paper_trader/reporter.py b/apps/paper_trader/reporter.py
index 121c6ef..a92c667 100644
--- a/apps/paper_trader/reporter.py
+++ b/apps/paper_trader/reporter.py
@@ -309,54 +309,6 @@ def print_sessions(sessions: list[SessionRow]) -> None:
 # Run summary
 # ------------------------------------------------------------------ #
 
-def _print_overlay_detail(r: dict) -> None:
-    """Print overlay regime allocation + per-book summary."""
-    name = r["session_name"]
-
-    # Regime day counts
-    regime_counts = r.get("regime_day_counts", {})
-    if regime_counts:
-        regime_tbl = Table(
-            box=box.SIMPLE_HEAD, show_header=True, header_style="bold yellow",
-            padding=(0, 1), title=f"[bold magenta]Regime Days — {name}[/]", title_justify="left",
-        )
-        regime_tbl.add_column("Regime", style="bold")
-        regime_tbl.add_column("Days", justify="right")
-        regime_tbl.add_column("Allocation", no_wrap=True)
-        allocations = r.get("allocations", {})
-        for regime, count in sorted(regime_counts.items()):
-            alloc = allocations.get(regime, {})
-            alloc_str = "  ".join(f"{k}={v:.0%}" for k, v in alloc.items())
-            regime_tbl.add_row(regime, str(count), alloc_str)
-        _console.print(regime_tbl)
-
-    # Per-book summary
-    book_results = r.get("book_results", [])
-    if book_results:
-        book_tbl = Table(
-            box=box.SIMPLE_HEAD, show_header=True, header_style="bold yellow",
-            padding=(0, 1), title=f"[bold magenta]Books — {name}[/]", title_justify="left",
-        )
-        book_tbl.add_column("Book", style="bold")
-        book_tbl.add_column("Return", justify="right")
-        book_tbl.add_column("MaxDD", justify="right")
-        book_tbl.add_column("Trades", justify="right")
-        book_tbl.add_column("WinRate", justify="right")
-        book_tbl.add_column("Sharpe", justify="right")
-        for br in book_results:
-            bs = br["result"]["summary"]
-            ret_color = "green" if bs["return_pct"] >= 0 else "red"
-            book_tbl.add_row(
-                br["label"],
-                f"[{ret_color}]{bs['return_pct']:+.2f}%[/{ret_color}]",
-                f"[red]-{bs['max_dd_pct']:.2f}%[/]",
-                str(bs["trade_count"]),
-                f"{bs['win_rate']:.0f}%",
-                f"{bs['sharpe']:+.2f}",
-            )
-        _console.print(book_tbl)
-
-
 def print_backtest_results(results: list[dict], output_dir: str | None = None, show_trades: bool = True) -> None:
     """Print equity curve comparison, summary table, and per-strategy trade logs."""
     import csv
@@ -386,8 +338,6 @@ def print_backtest_results(results: list[dict], output_dir: str | None = None, s
         s = r["summary"]
         ret_color = "green" if s["return_pct"] >= 0 else "red"
         name = r["session_name"]
-        if r.get("is_overlay"):
-            name = f"{name} [overlay]"
         sum_tbl.add_row(
             name,
             f"[{ret_color}]{s['return_pct']:+.2f}%[/{ret_color}]",
@@ -399,12 +349,6 @@ def print_backtest_results(results: list[dict], output_dir: str | None = None, s
 
     _console.print(sum_tbl)
 
-    # ── Overlay detail sections ───────────────────────────────────────────
-    for r in results:
-        if not r.get("is_overlay"):
-            continue
-        _print_overlay_detail(r)
-
     # ── Per-strategy trade logs ────────────────────────────────────────────
     if not show_trades:
         if output_dir:
@@ -520,8 +464,23 @@ def print_run_summary(summary: dict) -> None:
         _console.print(f"[dim]{date}: {status}[/]")
         return
 
+    if status == "kill_switch_active":
+        _console.print(f"[bold red]{date}: KILL SWITCH ACTIVE — all trading halted[/]")
+        return
+
     _console.print(f"\nProcessing [bold]{date}[/]...")
 
+    # Reconciliation report
+    recon = summary.get("reconciliation")
+    if recon and recon.has_issues:
+        _console.print("  [bold yellow]RECONCILIATION:[/]")
+        for sym in recon.orphaned_alpaca:
+            _console.print(f"    [yellow]ORPHANED[/] {sym} — on Alpaca but no local state")
+        for sym in recon.ghost_local:
+            _console.print(f"    [yellow]GHOST[/] {sym} — local state but no Alpaca position (auto-closed)")
+        if recon.stale_orders_cancelled:
+            _console.print(f"    [dim]Stale orders cancelled: {len(recon.stale_orders_cancelled)}[/]")
+
     exits = summary.get("exits", [])
     entries = summary.get("entries", [])
     rejected = summary.get("rejected", [])
diff --git a/apps/tools/evaluate_book_overlay.py b/apps/tools/evaluate_book_overlay.py
deleted file mode 100644
index d7c7909..0000000
--- a/apps/tools/evaluate_book_overlay.py
+++ /dev/null
@@ -1,125 +0,0 @@
-#!/usr/bin/env python3
-from __future__ import annotations
-
-import argparse
-import datetime as dt
-import json
-from pathlib import Path
-from typing import Any
-
-from apps.backtester.run import _build_merged_snapshot_store
-from libs.backtest.allocator import _macro_regime_state
-from libs.backtest.manifests import load_manifest, resolve_config
-from libs.backtest.overlay import (
-    build_overlay_curve,
-    load_equity_curve_csv,
-    load_merged_store_from_snapshot_dir,
-    summarize_overlay_curve,
-)
-from libs.common.config import get_settings
-
-
-def _parse_date(value: str | None) -> dt.date | None:
-    if not value:
-        return None
-    return dt.date.fromisoformat(value)
-
-
-def _compute_regimes(
-    *,
-    snapshot_dir: str | Path,
-    split: str,
-    config_path: str | Path,
-    start_date: dt.date | None,
-    end_date: dt.date | None,
-) -> dict[dt.date, str]:
-    del split  # overlay regimes should cover the full requested window, not a single split
-    manifest = load_manifest(config_path)
-    config = resolve_config(manifest, config_root=".")
-
-    raw_snapshot_dir = Path(snapshot_dir)
-    if (raw_snapshot_dir / "train.parquet").exists() or (raw_snapshot_dir / "test.parquet").exists():
-        settings = get_settings()
-        store = load_merged_store_from_snapshot_dir(
-            raw_snapshot_dir,
-            oracle_url=settings.stock_oracle_url,
-            db_dsn=settings.postgres_dsn,
-        )
-    else:
-        try:
-            store = _build_merged_snapshot_store(
-                manifest,
-                config,
-                snapshot_dir_override=str(raw_snapshot_dir),
-            )
-        except FileNotFoundError:
-            store = _build_merged_snapshot_store(
-                manifest,
-                config,
-                snapshot_dir_override=None,
-            )
-
-    if start_date or end_date:
-        lower = start_date or dt.date.min
-        upper = end_date or dt.date.max
-        store = store.slice_by_date_range(lower, upper)
-
-    regimes: dict[dt.date, str] = {}
-    for date in store.all_trading_days():
-        regimes[date] = _macro_regime_state(config, store.get_macro_for_date(date))
-    return regimes
-
-
-def _load_spec(path: str | Path) -> dict[str, Any]:
-    return json.loads(Path(path).read_text())
-
-
-def main() -> None:
-    parser = argparse.ArgumentParser(description="Evaluate a regime-switched overlay from book equity curves")
-    parser.add_argument("--spec", required=True, help="Path to overlay spec JSON")
-    parser.add_argument("--output-dir", required=True, help="Directory to write overlay outputs")
-    args = parser.parse_args()
-
-    spec = _load_spec(args.spec)
-    initial_equity = float(spec.get("initial_equity", 10_000.0))
-
-    curves = {
-        book["label"]: load_equity_curve_csv(book["equity_csv"])
-        for book in spec["books"]
-    }
-    regime_source = spec["regime_source"]
-    start_date = _parse_date(spec.get("start_date"))
-    end_date = _parse_date(spec.get("end_date"))
-    regimes = _compute_regimes(
-        snapshot_dir=regime_source["snapshot_dir"],
-        split=regime_source.get("split", "train"),
-        config_path=regime_source["config_path"],
-        start_date=start_date,
-        end_date=end_date,
-    )
-
-    curve = build_overlay_curve(
-        curves=curves,
-        allocations=spec["allocations"],
-        regimes_by_date=regimes,
-        initial_equity=initial_equity,
-    )
-    if start_date:
-        curve = curve[curve["date"] >= start_date]
-    if end_date:
-        curve = curve[curve["date"] <= end_date]
-
-    summary = summarize_overlay_curve(curve, initial_equity=initial_equity)
-    summary["overlay_name"] = spec.get("overlay_name", Path(args.spec).stem)
-    summary["books"] = [book["label"] for book in spec["books"]]
-    summary["allocations"] = spec["allocations"]
-
-    out_dir = Path(args.output_dir)
-    out_dir.mkdir(parents=True, exist_ok=True)
-    curve.assign(date=curve["date"].astype(str)).to_csv(out_dir / "overlay_equity.csv", index=False)
-    (out_dir / "overlay_summary.json").write_text(json.dumps(summary, indent=2) + "\n")
-    print(json.dumps(summary, indent=2))
-
-
-if __name__ == "__main__":
-    main()
diff --git a/apps/tracker/cli.py b/apps/tracker/cli.py
index a95d231..a5f41c1 100644
--- a/apps/tracker/cli.py
+++ b/apps/tracker/cli.py
@@ -2,8 +2,6 @@
 from __future__ import annotations
 
 import argparse
-import datetime as dt
-import json
 import sys
 from pathlib import Path
 
@@ -15,7 +13,6 @@ from rich.table import Table
 from libs.backtest.domain import (
     ConfigDelta,
     JournalEntry,
-    OverlayWindowSummary,
     RobustnessMatrixSummary,
     SplitResult,
     WalkForwardSummary,
@@ -33,8 +30,6 @@ from libs.backtest.tracker import (
     compute_public_sqs_v2,
     compute_promotion_score,
     compute_oot_robustness_gate,
-    compute_overlay_public_sqs,
-    compute_overlay_stress_sqs,
     compute_robustness_gate,
     compute_rqs,
     compute_sqs,
@@ -42,7 +37,6 @@ from libs.backtest.tracker import (
     compute_unified_score,
     compute_wfqs,
     compute_wfqs_v2,
-    filter_overlay_registry_entries,
     filter_registry_entries,
     get_next_entry_id,
     journal_lock,
@@ -117,43 +111,6 @@ def _load_optional_robustness_summary(path_str: str | None) -> RobustnessMatrixS
     return RobustnessMatrixSummary.model_validate_json(path.read_text())
 
 
-def _build_overlay_window_summary(spec_path: str, summary_path: str) -> OverlayWindowSummary:
-    spec = json.loads(Path(spec_path).read_text())
-    summary = json.loads(Path(summary_path).read_text())
-
-    start_date = spec.get("start_date")
-    end_date = spec.get("end_date")
-    if not start_date or not end_date:
-        print("ERROR: overlay spec must include start_date and end_date")
-        sys.exit(1)
-
-    start = dt.date.fromisoformat(start_date)
-    end = dt.date.fromisoformat(end_date)
-    initial_equity = float(spec.get("initial_equity", 10_000.0))
-    final_equity = summary.get("final_equity")
-    annualized_return_pct = None
-    if final_equity is not None and initial_equity > 0:
-        calendar_days = max((end - start).days, 1)
-        annualized_return_pct = ((float(final_equity) / initial_equity) ** (365.25 / calendar_days) - 1.0) * 100.0
-
-    return OverlayWindowSummary(
-        window_name=summary.get("overlay_name", Path(spec_path).stem),
-        overlay_name=summary.get("overlay_name", Path(spec_path).stem),
-        start_date=start,
-        end_date=end,
-        initial_equity=initial_equity,
-        final_equity=summary.get("final_equity"),
-        return_pct=summary.get("return_pct"),
-        annualized_return_pct=annualized_return_pct,
-        max_drawdown_pct=summary.get("max_dd_pct"),
-        sharpe_ratio=summary.get("sharpe"),
-        day_count=int(summary.get("day_count") or 0),
-        books=list(summary.get("books") or []),
-        allocations=dict(summary.get("allocations") or {}),
-        regime_day_counts=dict(summary.get("regime_day_counts") or {}),
-    )
-
-
 def _score_sort_key(sort_by: str, entry) -> tuple:
     if sort_by == "promotion":
         return (
@@ -391,86 +348,12 @@ def cmd_record(args: argparse.Namespace) -> None:
     print(f"Leaderboard updated: {leaderboard_path}")
 
 
-def cmd_record_overlay(args: argparse.Namespace) -> None:
-    """Record an overlay evaluation to the official journal and leaderboard."""
-    journal_dir = Path(args.journal_dir)
-    journal_path = journal_dir / "improvement_journal.jsonl"
-    registry_path = journal_dir / "experiment_registry.json"
-    leaderboard_path = journal_dir / "LEADERBOARD.md"
-
-    overlay_summary = _build_overlay_window_summary(args.spec, args.summary)
-    overlay_stress_summary = _build_overlay_window_summary(args.stress_spec, args.stress_summary)
-    sqs_score, sqs_breakdown, source = compute_overlay_public_sqs(
-        overlay_summary,
-        overlay_stress_summary,
-    )
-    stress_sqs_score, stress_sqs_breakdown, _ = compute_overlay_stress_sqs(
-        overlay_summary,
-        overlay_stress_summary,
-    )
-    if sqs_score is None:
-        print(f"ERROR: overlay score unavailable ({source})")
-        sys.exit(1)
-
-    spec = json.loads(Path(args.spec).read_text())
-    experiment_name = spec.get("overlay_name") or Path(args.spec).stem
-    tags = ["overlay", *list(getattr(args, "tags", []) or [])]
-
-    with journal_lock(journal_path):
-        dupes = check_duplicate(journal_path, experiment_name)
-        if dupes and not args.force:
-            print(f"WARNING: overlay '{experiment_name}' already in journal ({len(dupes)} entries).")
-            print("Use --force to add anyway.")
-            sys.exit(1)
-
-        entry_id = get_next_entry_id(journal_path)
-        entry = JournalEntry(
-            entry_id=entry_id,
-            timestamp=utc_now().isoformat(),
-            experiment_name=experiment_name,
-            hypothesis=args.hypothesis or "",
-            overlay_common_window_summary=overlay_summary,
-            overlay_stress_window_summary=overlay_stress_summary,
-            sqs_score=sqs_score,
-            sqs_breakdown=sqs_breakdown,
-            sqs_v3_score=sqs_score,
-            sqs_v3_breakdown=sqs_breakdown,
-            stress_sqs_score=stress_sqs_score,
-            stress_sqs_breakdown=stress_sqs_breakdown,
-            verdict=args.verdict or "unknown",
-            verdict_reasoning=args.reasoning or "",
-            next_direction=args.next or "",
-            tags=tags,
-        )
-        append_journal_entry(journal_path, entry)
-        _sync_and_rebuild(journal_path, registry_path, leaderboard_path)
-
-    stress_label = f", stress={stress_sqs_score:.1f}" if stress_sqs_score is not None else ""
-    print(f"Recorded {entry_id}: {experiment_name} (SQS={sqs_score:.1f}{stress_label}, source={source})")
-    print(
-        "  common-window:"
-        f" Ret={overlay_summary.return_pct:+.2f}%"
-        f", Ann={overlay_summary.annualized_return_pct:+.2f}%"
-        f", DD={overlay_summary.max_drawdown_pct:.2f}%"
-        f", Sharpe={overlay_summary.sharpe_ratio:.2f}"
-    )
-    print(
-        "  stress-window:"
-        f" Ret={overlay_stress_summary.return_pct:+.2f}%"
-        f", Ann={overlay_stress_summary.annualized_return_pct:+.2f}%"
-        f", DD={overlay_stress_summary.max_drawdown_pct:.2f}%"
-        f", Sharpe={overlay_stress_summary.sharpe_ratio:.2f}"
-    )
-    print(f"Leaderboard updated: {leaderboard_path}")
-
-
 def cmd_leaderboard(args: argparse.Namespace) -> None:
     """Show or regenerate the leaderboard."""
     journal_dir = Path(args.journal_dir)
     journal_path = journal_dir / "improvement_journal.jsonl"
     registry_path = journal_dir / "experiment_registry.json"
     leaderboard_path = journal_dir / "LEADERBOARD.md"
-    overlay_leaderboard_path = journal_dir / "OVERLAY_LEADERBOARD.md"
 
     if not journal_path.exists():
         journal_path.parent.mkdir(parents=True, exist_ok=True)
@@ -478,31 +361,18 @@ def cmd_leaderboard(args: argparse.Namespace) -> None:
 
     with journal_lock(journal_path):
         registry = _sync_and_rebuild(journal_path, registry_path, leaderboard_path)
-    overlay_only = getattr(args, "overlay_only", False)
-    if overlay_only:
-        ranked_source = filter_overlay_registry_entries(
-            registry.entries,
-            include_retired=getattr(args, "include_retired", False),
-        )
-        displayed_leaderboard_path = overlay_leaderboard_path
-    else:
-        ranked_source = filter_registry_entries(
-            registry.entries,
-            include_retired=getattr(args, "include_retired", False),
-            include_overlays=False,
-        )
-        displayed_leaderboard_path = leaderboard_path
+    ranked_source = filter_registry_entries(
+        registry.entries,
+        include_retired=getattr(args, "include_retired", False),
+    )
+    displayed_leaderboard_path = leaderboard_path
 
     sort_by = getattr(args, "sort", "sqs")
     ranked_entries = sorted(ranked_source, key=lambda entry: _score_sort_key(sort_by, entry))
     total = len(ranked_entries)
     top_n = getattr(args, "top", 10)
-    diagnostics = (not overlay_only) and sort_by in {"deployment", "dep", "wfqs", "rqs", "promotion", "unified", "sqs2"}
-    title = (
-        f"[bold cyan]Top {top_n} / {total}[/]  [dim]· overlay official SQS · Common=full-window  Stress=OOT[/]"
-        if overlay_only
-        else f"[bold cyan]Top {top_n} / {total}[/]  [dim]· {_title_for_sort(sort_by)} · Tr=train  V=valid  T=test[/]"
-    )
+    diagnostics = sort_by in {"deployment", "dep", "wfqs", "rqs", "promotion", "unified", "sqs2"}
+    title = f"[bold cyan]Top {top_n} / {total}[/]  [dim]· {_title_for_sort(sort_by)} · Tr=train  V=valid  T=test[/]"
 
     tbl = Table(
         box=box.SIMPLE_HEAD,
@@ -537,7 +407,6 @@ def cmd_leaderboard(args: argparse.Namespace) -> None:
         name = entry.experiment_name
         if len(name) > _COL_NAME:
             name = name[: _COL_NAME - 1] + "…"
-        is_overlay = entry.strategy_family == "overlay" and entry.overlay_common_window_summary is not None
         row = [
             str(rank),
             name,
@@ -553,14 +422,14 @@ def cmd_leaderboard(args: argparse.Namespace) -> None:
                     _fmt(entry.rqs_score, ".1f"),
                 ])
         row.extend([
-            "-" if is_overlay else _fmt(entry.train_total_return_pct, "+.1f"),
-            "-" if is_overlay else _fmt(entry.valid_total_return_pct, "+.1f"),
+            _fmt(entry.train_total_return_pct, "+.1f"),
+            _fmt(entry.valid_total_return_pct, "+.1f"),
             _fmt(entry.total_return_pct, "+.1f"),
             _fmt(entry.annualized_return_pct, "+.1f"),
             _fmt(entry.max_drawdown_pct, ".1f"),
-            "-" if is_overlay else _fmt(entry.avg_gross_exposure_pct, ".1f"),
-            "-" if is_overlay else _fmt(entry.days_in_market_pct, ".1f"),
-            "-" if is_overlay else _fmt(_ratio(entry.total_return_pct, entry.avg_gross_exposure_pct), ".2f"),
+            _fmt(entry.avg_gross_exposure_pct, ".1f"),
+            _fmt(entry.days_in_market_pct, ".1f"),
+            _fmt(_ratio(entry.total_return_pct, entry.avg_gross_exposure_pct), ".2f"),
         ])
         tbl.add_row(*row)
 
@@ -1034,13 +903,6 @@ def main() -> None:
             action="store_true",
             help="Include retired legacy PEAD / short-core / exact-pocket families",
         )
-        subparser.add_argument(
-            "--overlay",
-            "--overlay-only",
-            dest="overlay_only",
-            action="store_true",
-            help="Show the separate overlay/book-of-books leaderboard instead of the default single-book leaderboard",
-        )
 
     for name in ("show", "s"):
         subparser = sub.add_parser(name, help="Show details of a journal entry")
@@ -1071,20 +933,6 @@ def main() -> None:
         subparser.add_argument("target", help="Entry ID or experiment name to update")
         subparser.add_argument("--summary", required=True, help="Path to robustness_matrix_summary.json")
 
-    for name in ("record-overlay", "rovl"):
-        subparser = sub.add_parser(name, help="Record an official overlay evaluation")
-        subparser.add_argument("--journal-dir", **journal_kwargs)
-        subparser.add_argument("--spec", required=True, help="Path to overlay spec JSON for the main window")
-        subparser.add_argument("--summary", required=True, help="Path to overlay_summary.json for the main window")
-        subparser.add_argument("--stress-spec", required=True, help="Path to overlay spec JSON for the stress window")
-        subparser.add_argument("--stress-summary", required=True, help="Path to overlay_summary.json for the stress window")
-        subparser.add_argument("--hypothesis", default="", help="Short hypothesis / notes")
-        subparser.add_argument("--verdict", help="Initial verdict label")
-        subparser.add_argument("--reasoning", help="Verdict reasoning")
-        subparser.add_argument("--next", help="Next direction")
-        subparser.add_argument("--force", action="store_true", help="Allow duplicate overlay names")
-        subparser.add_argument("--tags", nargs="*", default=[], help="Extra tags")
-
     for name in ("rescore-public", "rsp"):
         subparser = sub.add_parser(name, help="Recompute stored public scores for journal entries")
         subparser.add_argument("--journal-dir", **journal_kwargs)
@@ -1108,8 +956,6 @@ def main() -> None:
         "arb": cmd_attach_robustness,
         "attach-oot-robustness": cmd_attach_oot_robustness,
         "aoot": cmd_attach_oot_robustness,
-        "record-overlay": cmd_record_overlay,
-        "rovl": cmd_record_overlay,
         "rescore-public": cmd_rescore_public,
         "rsp": cmd_rescore_public,
     }
diff --git a/configs/overlays/return_book_overlay_v1.json b/configs/overlays/return_book_overlay_v1.json
deleted file mode 100644
index 7740a4e..0000000
--- a/configs/overlays/return_book_overlay_v1.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v1",
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6.221_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv"
-    }
-  ],
-  "allocations": {
-    "risk_on": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "neutral": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "risk_off": {
-      "core": 1.0,
-      "mom": 0.0
-    },
-    "unknown": {
-      "core": 1.0,
-      "mom": 0.0
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v1b.json b/configs/overlays/return_book_overlay_v1b.json
deleted file mode 100644
index 89c5779..0000000
--- a/configs/overlays/return_book_overlay_v1b.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v1b",
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6.221_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv"
-    }
-  ],
-  "allocations": {
-    "risk_on": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "neutral": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "risk_off": {
-      "core": 1.0,
-      "mom": 0.0
-    },
-    "unknown": {
-      "core": 0.0,
-      "mom": 1.0
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v1c.json b/configs/overlays/return_book_overlay_v1c.json
deleted file mode 100644
index 51d5df8..0000000
--- a/configs/overlays/return_book_overlay_v1c.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v1c",
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6.221_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv"
-    }
-  ],
-  "allocations": {
-    "risk_on": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "neutral": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "risk_off": {
-      "core": 1.0,
-      "mom": 0.0
-    },
-    "unknown": {
-      "core": 0.5,
-      "mom": 0.5
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v2.json b/configs/overlays/return_book_overlay_v2.json
deleted file mode 100644
index c1a0bca..0000000
--- a/configs/overlays/return_book_overlay_v2.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.114.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/fallback_book_compare/return_max_long_v6.114_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv"
-    }
-  ],
-  "overlay_name": "return_book_overlay_v2",
-  "allocations": {
-    "risk_on": {
-      "core": 0,
-      "mom": 1
-    },
-    "neutral": {
-      "core": 0,
-      "mom": 1
-    },
-    "risk_off": {
-      "core": 1,
-      "mom": 0
-    },
-    "unknown": {
-      "core": 1,
-      "mom": 0
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v2b.json b/configs/overlays/return_book_overlay_v2b.json
deleted file mode 100644
index d6137a9..0000000
--- a/configs/overlays/return_book_overlay_v2b.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.114.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/fallback_book_compare/return_max_long_v6.114_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv"
-    }
-  ],
-  "overlay_name": "return_book_overlay_v2b",
-  "allocations": {
-    "risk_on": {
-      "core": 0,
-      "mom": 1
-    },
-    "neutral": {
-      "core": 0,
-      "mom": 1
-    },
-    "risk_off": {
-      "core": 1,
-      "mom": 0
-    },
-    "unknown": {
-      "core": 0,
-      "mom": 1
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v3.json b/configs/overlays/return_book_overlay_v3.json
deleted file mode 100644
index fb30189..0000000
--- a/configs/overlays/return_book_overlay_v3.json
+++ /dev/null
@@ -1,29 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v3",
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6.221_equity.csv",
-      "experiment_config": "configs/experiments/return_max_long_v6.221.json"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv",
-      "experiment_config": "configs/experiments/return_max_long_v6new.54.json"
-    }
-  ],
-  "allocations": {
-    "risk_on": {"core": 0.5, "mom": 0.5},
-    "neutral": {"core": 0.0, "mom": 1.0},
-    "risk_off": {"core": 1.0, "mom": 0.0},
-    "unknown": {"core": 1.0, "mom": 0.0}
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v3_oot.json b/configs/overlays/return_book_overlay_v3_oot.json
deleted file mode 100644
index 0b5fd0d..0000000
--- a/configs/overlays/return_book_overlay_v3_oot.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v3_oot",
-  "initial_equity": 10000,
-  "start_date": "2020-01-02",
-  "end_date": "2021-12-31",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/datasets/snapshots/midlarge-liquid-long-v1-oot-2020-2021",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_oot_inputs/csv/core_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_oot_inputs/csv/mom_equity.csv"
-    }
-  ],
-  "allocations": {
-    "risk_on": {
-      "core": 0.5,
-      "mom": 0.5
-    },
-    "neutral": {
-      "core": 0.0,
-      "mom": 1.0
-    },
-    "risk_off": {
-      "core": 1.0,
-      "mom": 0.0
-    },
-    "unknown": {
-      "core": 1.0,
-      "mom": 0.0
-    }
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v3b.json b/configs/overlays/return_book_overlay_v3b.json
deleted file mode 100644
index d3b33b2..0000000
--- a/configs/overlays/return_book_overlay_v3b.json
+++ /dev/null
@@ -1,29 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v3b",
-  "initial_equity": 10000,
-  "start_date": "2022-03-03",
-  "end_date": "2026-03-13",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/parquet/midlarge-liquid-long-v1_bucketfix_full_audit_mom_v2",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6.221_equity.csv",
-      "experiment_config": "configs/experiments/return_max_long_v6.221.json"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_v1_inputs/return_max_long_v6new.54_equity.csv",
-      "experiment_config": "configs/experiments/return_max_long_v6new.54.json"
-    }
-  ],
-  "allocations": {
-    "risk_on": {"core": 0.5, "mom": 0.5},
-    "neutral": {"core": 0.5, "mom": 0.5},
-    "risk_off": {"core": 1.0, "mom": 0.0},
-    "unknown": {"core": 1.0, "mom": 0.0}
-  }
-}
diff --git a/configs/overlays/return_book_overlay_v3b_oot.json b/configs/overlays/return_book_overlay_v3b_oot.json
deleted file mode 100644
index a731073..0000000
--- a/configs/overlays/return_book_overlay_v3b_oot.json
+++ /dev/null
@@ -1,39 +0,0 @@
-{
-  "overlay_name": "return_book_overlay_v3b_oot",
-  "initial_equity": 10000,
-  "start_date": "2020-01-02",
-  "end_date": "2021-12-31",
-  "regime_source": {
-    "config_path": "configs/experiments/return_max_long_v6.221.json",
-    "snapshot_dir": "data/datasets/snapshots/midlarge-liquid-long-v1-oot-2020-2021",
-    "split": "train"
-  },
-  "books": [
-    {
-      "label": "core",
-      "equity_csv": "runs/book_overlay_oot_inputs/csv/core_equity.csv"
-    },
-    {
-      "label": "mom",
-      "equity_csv": "runs/book_overlay_oot_inputs/csv/mom_equity.csv"
-    }
-  ],
-  "allocations": {
-    "risk_on": {
-      "core": 0.5,
-      "mom": 0.5
-    },
-    "neutral": {
-      "core": 0.5,
-      "mom": 0.5
-    },
-    "risk_off": {
-      "core": 1.0,
-      "mom": 0.0
-    },
-    "unknown": {
-      "core": 1.0,
-      "mom": 0.0
-    }
-  }
-}
diff --git a/docs/public_sqs_calculation.md b/docs/public_sqs_calculation.md
index b903340..42a0cb1 100644
--- a/docs/public_sqs_calculation.md
+++ b/docs/public_sqs_calculation.md
@@ -8,7 +8,6 @@ split-only 점수와 final leaderboard 점수가 다를 수 있는지를 정리
 - `SQS v4`: `SQS v3` + common-window capital-growth blend
 - `sqs_v3_score`: deployment/WFV-first primary rank
 - `stress_sqs_score`: 예전 public score. stress OOT quality를 추가 패널티로 곱한 legacy score
-- overlay entry는 split/WFV 기반 `SQS v4` 대신 **overlay 전용 official score**를 쓴다.
 
 핵심 결론부터 말하면:
 
@@ -44,42 +43,13 @@ public leaderboard / registry rebuild도 같은 함수를 쓴다:
 
 즉, 수동 계산과 leaderboard 계산은 같은 코드 경로를 따라야 한다.
 
-## 1.5 Overlay는 어떻게 공식 점수화되나
+## 1.5 Overlay 경로는 retired 상태다
 
-overlay는 train/valid/test/WFV 구조가 없으므로 single-book `SQS v4`를 그대로 쓸 수 없다.
+overlay/book-of-books 평가는 코드베이스에서 제거됐다.
 
-대신 아래 두 summary를 붙여서 공식 점수를 계산한다.
-
-- `overlay_common_window_summary`
-- `overlay_stress_window_summary`
-
-계산 함수는:
-
-- [`compute_overlay_public_sqs`](/Users/yirugi/mycloud/personal/workspace/fithia2/libs/backtest/tracker.py#L1356)
-- [`compute_overlay_stress_sqs`](/Users/yirugi/mycloud/personal/workspace/fithia2/libs/backtest/tracker.py#L1381)
-
-공식 overlay 점수는:
-
-```text
-overlay_window_score * overlay_stress_gate
-```
-
-legacy overlay stress 점수는:
-
-```text
-overlay_window_score * overlay_stress_gate * overlay_quality_factor
-```
-
-즉 overlay도 stress window는 ranking 보조가 아니라 **공식 통과 게이트**에 가깝게 다룬다.
-
-추가 원칙:
-
-- overlay official score는 spec의 `books[].equity_csv`를 **frozen input**으로 본다.
-- [`fithia2 paper backtest --overlay`](/Users/yirugi/mycloud/personal/workspace/fithia2/apps/paper_trader/cli.py)도 같은 frozen `equity_csv`를 우선 replay해야 한다.
-- 그래서 overlay leaderboard 숫자와 paper overlay 숫자가 다르면 먼저
-  `equity_csv`, `regime_source`, `start_date`, `end_date`가 같은지 확인한다.
-- stress OOT overlay는 full-window csv를 재사용하면 안 된다.
-  OOT 전용 `equity_csv`와 OOT snapshot `regime_source.snapshot_dir`를 같이 고정해야 한다.
+- 기본 leaderboard는 single-book 전략만 포함한다.
+- journal에 남아 있는 과거 overlay entry는 historical record로만 취급한다.
+- registry rebuild와 `fithia2 lb`는 overlay entry를 건너뛴다.
 
 ## 2. 흔한 오해
 
diff --git a/docs/research_workflow_and_handoff.md b/docs/research_workflow_and_handoff.md
index 2dbdaba..465ae25 100644
--- a/docs/research_workflow_and_handoff.md
+++ b/docs/research_workflow_and_handoff.md
@@ -224,52 +224,13 @@ python apps/tracker/cli.py attach-oot-robustness \
   --summary runs/<experiment>_oot_rm/robustness_matrix/robustness_matrix_summary.json
 ```
 
-### Book Overlay Evaluation
+### Retired Overlay Path
 
-single-book manifest를 억지로 섞지 말고, 별도 book을 각각 먼저 고정 기간으로 돌린 뒤
-overlay를 따로 평가한다.
+book-of-books overlay 실험은 코드베이스에서 제거됐다.
 
-1. 같은 기간, 같은 초기 자본으로 각 book의 equity curve를 만든다.
-2. [`configs/overlays`](/Users/yirugi/mycloud/personal/workspace/fithia2/configs/overlays) 아래 spec에
-   regime별 자본 배분을 적는다.
-3. [`apps/tools/evaluate_book_overlay.py`](/Users/yirugi/mycloud/personal/workspace/fithia2/apps/tools/evaluate_book_overlay.py)로
-   overlay equity와 summary를 만든다.
-4. full-window spec/summary와 stress-window spec/summary를 모두 만든 뒤
-   [`apps/tracker/cli.py`](/Users/yirugi/mycloud/personal/workspace/fithia2/apps/tracker/cli.py)
-   `record-overlay`로 공식 journal/leaderboard에 등록한다.
-
-주의:
-
-- overlay spec의 `books[].equity_csv`는 **재현 기준 입력**이다.
-- 공식 평가와 [`fithia2 paper backtest --overlay`](/Users/yirugi/mycloud/personal/workspace/fithia2/apps/paper_trader/cli.py)는
-  둘 다 이 frozen curve를 우선 replay해야 한다.
-- OOT overlay는 full-window csv를 재사용하면 안 된다.
-  `runs/book_overlay_oot_inputs/...`처럼 OOT 전용 book curve를 따로 만든다.
-- `regime_source.snapshot_dir`가 explicit snapshot directory라면 evaluator는 그 디렉터리를 그대로 merged load해야 한다.
-
-예시:
-
-```bash
-fithia2 paper backtest \
-  --config configs/experiments/return_max_long_v6.221.json \
-  --config configs/experiments/return_max_long_v6new.54.json \
-  --capital 10000 \
-  --start 2022-03-03 \
-  --end 2026-03-13 \
-  --output runs/book_overlay_v1_inputs \
-  --no-trades
-
-python apps/tools/evaluate_book_overlay.py \
-  --spec configs/overlays/return_book_overlay_v1.json \
-  --output-dir runs/return_book_overlay_v1_eval
-
-python apps/tracker/cli.py record-overlay \
-  --spec configs/overlays/return_book_overlay_v3.json \
-  --summary runs/return_book_overlay_v3_eval/overlay_summary.json \
-  --stress-spec configs/overlays/return_book_overlay_v3_oot.json \
-  --stress-summary runs/return_book_overlay_v3_oot_eval/overlay_summary.json \
-  --hypothesis "Official overlay candidate"
-```
+- 공식 leaderboard와 paper backtest는 이제 single-book 전략만 지원한다.
+- 과거 overlay journal entry는 재현성 기록으로만 남고, registry/leaderboard 재빌드에는 포함되지 않는다.
+- 새 연구는 [`configs/experiments`](/Users/yirugi/mycloud/personal/workspace/fithia2/configs/experiments) 아래 single-book manifest 기준으로 진행한다.
 
 ## 8. 빠른 무결성 점검
 
diff --git a/journal/LEADERBOARD.md b/journal/LEADERBOARD.md
index 9e3d6f1..5448921 100644
--- a/journal/LEADERBOARD.md
+++ b/journal/LEADERBOARD.md
@@ -1,7 +1,7 @@
 # Strategy Improvement Leaderboard
-_Updated: 2026-03-27T03:43:33.985346+00:00_
+_Updated: 2026-03-27T04:05:32.124207+00:00_
 
-_Default view excludes overlay/book-of-books rows, retired legacy PEAD / short-core / exact-pocket families, and incomplete train-only scans. Use `fithia2 lb --overlay` for overlays or `fithia2 lb --include-retired` to inspect archived research._
+_Default view excludes retired legacy PEAD / short-core / exact-pocket families and incomplete train-only scans. Use `fithia2 lb --include-retired` to inspect archived research._
 
 _`SQS` below is public SQS v4: v3 deployment/WFV-first ranking plus a modest common-window capital-growth term when available. Stress OOT remains an eligibility gate. Prior v3 values remain in `experiment_registry.json` as `sqs_v3_score`._
 
diff --git a/journal/OVERLAY_LEADERBOARD.md b/journal/OVERLAY_LEADERBOARD.md
deleted file mode 100644
index 972e622..0000000
--- a/journal/OVERLAY_LEADERBOARD.md
+++ /dev/null
@@ -1,36 +0,0 @@
-# Overlay Strategy Leaderboard
-_Updated: 2026-03-27T03:43:33.985346+00:00_
-
-_This board is separate from the default single-book leaderboard. Overlay rows are book-of-books evaluations and are not directly comparable to single-book `SQS` rows._
-
-_`SQS` here is overlay official SQS: common-window overlay score with a stress OOT gate. `T.*` columns are common-window overlay metrics._
-
-| # | Overlay | SQS | [T]Ret% | [T]Ann% | [T]DD% | Stress Ret% | Stress DD% | Stress Sharpe | Date |
-|---|---------|-----|----------|----------|--------|-------------|------------|---------------|------|
-| 1 | return_book_overlay_v4 | 91.4 | +185.3 | +29.7 | 5.0 | +7.4 | 5.8 | +0.80 | 2026-03-27 |
-| 2 | return_book_overlay_v4b | 91.4 | +187.2 | +30.0 | 5.0 | +7.4 | 5.8 | +0.80 | 2026-03-27 |
-| 3 | return_book_overlay_v3 | 90.2 | +175.6 | +28.6 | 4.5 | +6.0 | 5.4 | +0.67 | 2026-03-26 |
-| 4 | return_book_overlay_v3b | 87.7 | +169.5 | +27.9 | 5.0 | +7.4 | 5.8 | +0.80 | 2026-03-26 |
-| 5 | return_book_overlay_v4c | 60.7 | +232.5 | +34.8 | 5.2 | +3.1 | 3.3 | +0.43 | 2026-03-27 |
-
-## Recent Overlay Entries
-### IMP-0794 (2026-03-27) — return_book_overlay_v4b
-Hypothesis: Core v6.221 plus higher-ranked v6new.207 momentum book with balanced 50/50 neutral allocation.
-Verdict: **UNKNOWN** (SQS 91.4)
-
-### IMP-0793 (2026-03-27) — return_book_overlay_v4c
-Hypothesis: Core v6.221 plus top-return v6new.275 momentum book with aggressive 75/25 risk-on and full-neutral momentum allocation.
-Verdict: **UNKNOWN** (SQS 60.7)
-
-### IMP-0792 (2026-03-27) — return_book_overlay_v4
-Hypothesis: Core v6.221 plus higher-ranked v6new.196 momentum book with balanced 50/50 neutral allocation.
-Verdict: **UNKNOWN** (SQS 91.4)
-
-### IMP-0738 (2026-03-26) — return_book_overlay_v3b
-Hypothesis: Balanced overlay variant with 50/50 neutral allocation between v6.221 and v6new.54.
-Verdict: **UNKNOWN** (SQS 87.7)
-
-### IMP-0737 (2026-03-26) — return_book_overlay_v3
-Hypothesis: Book-of-books overlay using v6.221 as stress fallback and v6new.54 as normal-regime book.
-Verdict: **UNKNOWN** (SQS 90.2)
-
diff --git a/journal/experiment_registry.json b/journal/experiment_registry.json
index b888403..f5da44c 100644
--- a/journal/experiment_registry.json
+++ b/journal/experiment_registry.json
@@ -1,505 +1,5 @@
 {
   "entries": [
-    {
-      "entry_id": "IMP-0792",
-      "experiment_name": "return_book_overlay_v4",
-      "strategy_family": "overlay",
-      "is_retired": false,
-      "sqs_score": 91.4,
-      "sqs_v3_score": 91.4,
-      "stress_sqs_score": 58.9,
-      "sqs_v2_score": null,
-      "promotion_score": null,
-      "unified_score": null,
-      "rqs_score": null,
-      "wfqs_score": null,
-      "wfqs_v2_score": null,
-      "deployment_score": null,
-      "common_window_score": null,
-      "common_window_summary": null,
-      "overlay_common_window_summary": {
-        "window_name": "return_book_overlay_v4",
-        "overlay_name": "return_book_overlay_v4",
-        "start_date": "2022-03-03",
-        "end_date": "2026-03-13",
-        "initial_equity": 10000.0,
-        "final_equity": 28533.769396343927,
-        "return_pct": 185.33769396343928,
-        "annualized_return_pct": 29.737609916187125,
-        "max_drawdown_pct": 4.952503311051353,
-        "sharpe_ratio": 2.698541363816893,
-        "day_count": 1014,
-        "books": [
-          "core",
-          "mom"
-        ],
-        "allocations": {
-          "risk_on": {
-            "core": 0.5,
-            "mom": 0.5
-          },
-          "neutral": {
-            "core": 0.5,
-            "mom": 0.5
-          },
-          "risk_off": {
-            "core": 1.0,
-            "mom": 0.0
-          },
-          "unknown": {
-            "core": 1.0,
-            "mom": 0.0
-          }
-        },
-        "regime_day_counts": {
-          "neutral": 83,
-          "risk_off": 312,
-          "risk_on": 619
-        }
-      },
-      "overlay_stress_window_summary": {
-        "window_name": "return_book_overlay_v4_oot",
-        "overlay_name": "return_book_overlay_v4_oot",
-        "start_date": "2020-01-02",
-        "end_date": "2021-12-31",
-        "initial_equity": 10000.0,
-        "final_equity": 10742.597083222194,
-        "return_pct": 7.42597083222194,
-        "annualized_return_pct": 3.654139119591049,
-        "max_drawdown_pct": 5.758756741288944,
-        "sharpe_ratio": 0.7998468196254072,
-        "day_count": 508,
-        "books": [
-          "core",
-          "mom"
-        ],
-        "allocations": {
-          "risk_on": {
-            "core": 0.5,
-            "mom": 0.5
-          },
-          "neutral": {
-            "core": 0.5,
-            "mom": 0.5
-          },
-          "risk_off": {
-            "core": 1.0,
-            "mom": 0.0
-          },
-          "unknown": {
-            "core": 1.0,
-            "mom": 0.0
-          }
-        },
-        "regime_day_counts": {
-          "neutral": 54,
-          "risk_off": 98,
-          "risk_on": 352,
-          "unknown": 4
-        }
-      },
-      "walk_forward_summary": null,
-      "robustness_matrix_summary": null,
-      "out_of_time_robustness_summary": null,
-      "train_total_return_pct": null,
-      "train_annualized_return_pct": null,
-      "profit_factor": null,
-      "total_return_pct": 185.33769396343928,
-      "annualized_return_pct": 29.737609916187125,
-      "win_rate": null,
-      "sharpe_ratio": 2.698541363816893,
-      "max_drawdown_pct": 4.952503311051353,
-      "trade_count": 0,
-      "avg_gross_exposure_pct": null,
-      "avg_net_exposure_pct": null,
-      "days_in_market_pct": null,
-      "valid_profit_factor": null,
-      "valid_total_return_pct": null,
-      "valid_annualized_return_pct": null,
-      "valid_win_rate": null,
-      "valid_sharpe_ratio": null,
-      "valid_max_drawdown_pct": null,
-      "valid_trade_count": 0,
-      "valid_avg_gross_exposure_pct": null,
-      "valid_avg_net_exposure_pct": null,
-      "valid_days_in_market_pct": null,
-      "timestamp": "2026-03-27T03:34:12.994662+00:00"
-    },
-    {
-      "entry_id": "IMP-0794",
-      "experiment_name": "return_book_overlay_v4b",
-      "strategy_family": "overlay",
-      "is_retired": false,
-      "sqs_score": 91.4,
-      "sqs_v3_score": 91.4,
-      "stress_sqs_score": 58.9,
-      "sqs_v2_score": null,
-      "promotion_score": null,
-      "unified_score": null,
-      "rqs_score": null,
-      "wfqs_score": null,
-      "wfqs_v2_score": null,
-      "deployment_score": null,
-      "common_window_score": null,
-      "common_window_summary": null,
-      "overlay_common_window_summary": {
-        "window_name": "return_book_overlay_v4b",
-        "overlay_name": "return_book_overlay_v4b",
-        "start_date": "2022-03-03",
-        "end_date": "2026-03-13",
-        "initial_equity": 10000.0,
-        "final_equity": 28724.75896020887,
-        "return_pct": 187.24758960208868,
-        "annualized_return_pct": 29.95269200710682,
-        "max_drawdown_pct": 4.952503311051353,
-        "sharpe_ratio": 2.692136311757153,
-        "day_count": 1014,
-        "books": [
-          "core",
-          "mom"
-        ],
-        "allocations": {
-          "risk_on": {
-            "core": 0.5,
-            "mom": 0.5
-          },
-          "neutral": {
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       "out_of_time_robustness_summary": null,
@@ -194963,8 +192812,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195009,8 +192856,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195055,8 +192900,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195101,8 +192944,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195147,8 +192988,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195193,8 +193032,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195239,8 +193076,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195285,8 +193120,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195331,8 +193164,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195377,8 +193208,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195423,8 +193252,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195469,8 +193296,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195515,8 +193340,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195561,8 +193384,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195607,8 +193428,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195653,8 +193472,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195699,8 +193516,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195745,8 +193560,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195791,8 +193604,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195837,8 +193648,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -195883,8 +193692,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": {
         "window_mode": "rolling_fixed",
         "train_days": 252,
@@ -196531,8 +194338,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -196577,8 +194382,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -196623,8 +194426,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -196737,8 +194538,6 @@
           }
         }
       },
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": {
         "window_mode": "rolling_fixed",
         "train_days": 252,
@@ -197405,8 +195204,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -197451,8 +195248,6 @@
       "deployment_score": null,
       "common_window_score": null,
       "common_window_summary": null,
-      "overlay_common_window_summary": null,
-      "overlay_stress_window_summary": null,
       "walk_forward_summary": null,
       "robustness_matrix_summary": null,
       "out_of_time_robustness_summary": null,
@@ -197481,5 +195276,5 @@
       "timestamp": "2026-03-26T14:56:24.543029+00:00"
     }
   ],
-  "updated_at": "2026-03-27T03:43:33.985346+00:00"
+  "updated_at": "2026-03-27T04:05:32.124207+00:00"
 }
\ No newline at end of file
diff --git a/libs/backtest/domain.py b/libs/backtest/domain.py
index 4df31c1..6035051 100644
--- a/libs/backtest/domain.py
+++ b/libs/backtest/domain.py
@@ -797,25 +797,6 @@ class CommonWindowSummary(BaseModel):
     metrics: MetricsBundle
 
 
-class OverlayWindowSummary(BaseModel):
-    """Compact overlay run summary for full-window / stress-window evaluation."""
-
-    window_name: str = "overlay_window"
-    overlay_name: str = ""
-    start_date: dt.date
-    end_date: dt.date
-    initial_equity: float = 10_000.0
-    final_equity: float | None = None
-    return_pct: float | None = None
-    annualized_return_pct: float | None = None
-    max_drawdown_pct: float | None = None
-    sharpe_ratio: float | None = None
-    day_count: int = 0
-    books: list[str] = Field(default_factory=list)
-    allocations: dict[str, dict[str, float]] = Field(default_factory=dict)
-    regime_day_counts: dict[str, int] = Field(default_factory=dict)
-
-
 class ConfigDelta(BaseModel):
     """Records what changed from a baseline experiment."""
 
@@ -836,8 +817,6 @@ class JournalEntry(BaseModel):
     robustness_matrix_summary: RobustnessMatrixSummary | None = None
     out_of_time_robustness_summary: RobustnessMatrixSummary | None = None
     common_window_summary: CommonWindowSummary | None = None
-    overlay_common_window_summary: OverlayWindowSummary | None = None
-    overlay_stress_window_summary: OverlayWindowSummary | None = None
     sqs_score: float | None = None
     sqs_breakdown: dict[str, float] = Field(default_factory=dict)
     sqs_v3_score: float | None = None
@@ -885,8 +864,6 @@ class RegistryEntry(BaseModel):
     deployment_score: float | None = None
     common_window_score: float | None = None
     common_window_summary: CommonWindowSummary | None = None
-    overlay_common_window_summary: OverlayWindowSummary | None = None
-    overlay_stress_window_summary: OverlayWindowSummary | None = None
     walk_forward_summary: WalkForwardSummary | None = None
     robustness_matrix_summary: RobustnessMatrixSummary | None = None
     out_of_time_robustness_summary: RobustnessMatrixSummary | None = None
diff --git a/libs/backtest/overlay.py b/libs/backtest/overlay.py
deleted file mode 100644
index 830003f..0000000
--- a/libs/backtest/overlay.py
+++ /dev/null
@@ -1,193 +0,0 @@
-"""Evaluate deterministic book overlays from daily equity curves."""
-from __future__ import annotations
-
-import datetime as dt
-import math
-from pathlib import Path
-from typing import Any
-
-import pandas as pd
-
-
-def load_merged_store_from_snapshot_dir(
-    snapshot_dir: str | Path,
-    *,
-    oracle_url: str,
-    db_dsn: str,
-):
-    """Load and merge train/valid/test splits from an explicit snapshot directory."""
-    from libs.backtest.snapshot_store import SnapshotStore
-
-    base = Path(snapshot_dir)
-    stores = []
-    for split in ("train", "valid", "test"):
-        if not (base / f"{split}.parquet").exists():
-            continue
-        stores.append(
-            SnapshotStore.load(
-                snapshot_dir=base,
-                split_name=split,
-                oracle_url=oracle_url,
-                db_dsn=db_dsn,
-            )
-        )
-
-    if not stores:
-        raise FileNotFoundError(f"No snapshot splits found under {base}")
-
-    merged_candidates: dict[dt.date, dict[tuple[Any, ...], dict[str, Any]]] = {}
-    merged_bars: dict[str, dict[dt.date, dict[str, Any]]] = {}
-    merged_macro: dict[dt.date, dict[str, Any]] = {}
-
-    for store in stores:
-        for exec_date in store.all_execution_dates():
-            bucket = merged_candidates.setdefault(exec_date, {})
-            for candidate in store.get_candidates_for_date(exec_date):
-                dedupe_key = (
-                    candidate.get("event_id"),
-                    candidate.get("symbol"),
-                    candidate.get("execution_date"),
-                    candidate.get("reaction_date"),
-                )
-                bucket.setdefault(dedupe_key, candidate)
-        for symbol, bars in store._bars.items():
-            merged_bars.setdefault(symbol, {}).update(bars)
-        for macro_date, macro_values in store._macro.items():
-            merged_macro.setdefault(macro_date, {}).update(macro_values)
-
-    from libs.backtest.snapshot_store import SnapshotStore
-
-    return SnapshotStore(
-        candidates_by_exec_date={
-            date: list(rows.values())
-            for date, rows in merged_candidates.items()
-        },
-        bars_by_symbol_date=merged_bars,
-        macro_by_date=merged_macro,
-    )
-
-
-def load_equity_curve_csv(path: str | Path) -> pd.DataFrame:
-    """Load a paper backtest equity CSV into a normalized daily returns frame."""
-    csv_path = Path(path)
-    df = pd.read_csv(csv_path, parse_dates=["date"])
-    required = {"date", "equity"}
-    missing = required.difference(df.columns)
-    if missing:
-        raise ValueError(f"Missing columns in {csv_path}: {sorted(missing)}")
-    if df.empty:
-        raise ValueError(f"Equity CSV has no rows: {csv_path}")
-
-    df = df.sort_values("date").copy()
-    df["date"] = pd.to_datetime(df["date"]).dt.date
-    df["equity"] = df["equity"].astype(float)
-    df["daily_return"] = df["equity"].pct_change().fillna(0.0)
-    return df[["date", "equity", "daily_return"]]
-
-
-def validate_allocations(
-    allocations: dict[str, dict[str, float]],
-    labels: set[str],
-    *,
-    tolerance: float = 1e-6,
-) -> None:
-    """Ensure each regime allocation references known labels and sums to 1."""
-    if not allocations:
-        raise ValueError("allocations must not be empty")
-    if "unknown" not in allocations:
-        raise ValueError("allocations must include an 'unknown' regime")
-
-    for regime, weights in allocations.items():
-        unknown = set(weights).difference(labels)
-        if unknown:
-            raise ValueError(
-                f"Allocation for regime '{regime}' references unknown labels: {sorted(unknown)}"
-            )
-        total = sum(float(weight) for weight in weights.values())
-        if abs(total - 1.0) > tolerance:
-            raise ValueError(
-                f"Allocation for regime '{regime}' must sum to 1.0, got {total:.6f}"
-            )
-
-
-def build_overlay_curve(
-    *,
-    curves: dict[str, pd.DataFrame],
-    allocations: dict[str, dict[str, float]],
-    regimes_by_date: dict[dt.date, str],
-    initial_equity: float = 10_000.0,
-) -> pd.DataFrame:
-    """Combine per-book daily returns into a single overlay equity curve."""
-    labels = set(curves)
-    if not labels:
-        raise ValueError("curves must not be empty")
-    validate_allocations(allocations, labels)
-
-    merged: pd.DataFrame | None = None
-    for label, df in curves.items():
-        renamed = df.rename(
-            columns={
-                "equity": f"equity_{label}",
-                "daily_return": f"daily_return_{label}",
-            }
-        )
-        frame = renamed[["date", f"daily_return_{label}"]]
-        merged = frame if merged is None else merged.merge(frame, on="date", how="inner")
-
-    if merged is None or merged.empty:
-        raise ValueError("No overlapping dates across curves")
-
-    merged = merged.sort_values("date").copy()
-    merged["regime"] = merged["date"].map(regimes_by_date).fillna("unknown")
-
-    overlay_returns: list[float] = []
-    for row in merged.itertuples(index=False):
-        weights = allocations.get(row.regime, allocations["unknown"])
-        ret = 0.0
-        for label in labels:
-            ret += float(weights.get(label, 0.0)) * float(getattr(row, f"daily_return_{label}"))
-        overlay_returns.append(ret)
-
-    merged["overlay_return"] = overlay_returns
-    equity = initial_equity
-    overlay_equity: list[float] = []
-    for ret in overlay_returns:
-        equity *= 1.0 + float(ret)
-        overlay_equity.append(equity)
-    merged["overlay_equity"] = overlay_equity
-    return merged[["date", "regime", "overlay_return", "overlay_equity"]]
-
-
-def summarize_overlay_curve(curve: pd.DataFrame, *, initial_equity: float) -> dict[str, Any]:
-    """Return total return, drawdown, Sharpe, and regime counts for an overlay."""
-    if curve.empty:
-        raise ValueError("curve must not be empty")
-
-    final_equity = float(curve["overlay_equity"].iloc[-1])
-    total_return_pct = (final_equity / float(initial_equity) - 1.0) * 100.0
-
-    peak = float(initial_equity)
-    max_drawdown_pct = 0.0
-    for equity in curve["overlay_equity"]:
-        peak = max(peak, float(equity))
-        drawdown_pct = (peak - float(equity)) / peak * 100.0 if peak > 0 else 0.0
-        max_drawdown_pct = max(max_drawdown_pct, drawdown_pct)
-
-    rets = curve["overlay_return"].astype(float)
-    if len(rets) >= 2 and float(rets.std()) > 0:
-        sharpe = float(rets.mean() / rets.std() * math.sqrt(252.0))
-    else:
-        sharpe = 0.0
-
-    regime_counts = {
-        str(regime): int(count)
-        for regime, count in curve["regime"].value_counts().sort_index().items()
-    }
-    return {
-        "return_pct": total_return_pct,
-        "max_dd_pct": max_drawdown_pct,
-        "sharpe": sharpe,
-        "final_equity": final_equity,
-        "day_count": int(len(curve)),
-        "regime_day_counts": regime_counts,
-    }
diff --git a/libs/backtest/tracker.py b/libs/backtest/tracker.py
index c06d0c7..fc019c8 100644
--- a/libs/backtest/tracker.py
+++ b/libs/backtest/tracker.py
@@ -22,7 +22,6 @@ from libs.backtest.domain import (
     ReturnScoreWeights,
     PromotionScoreWeights,
     RegistryEntry,
-    OverlayWindowSummary,
     SplitResult,
     SQSWeights,
     SQSv2Weights,
@@ -1316,134 +1315,6 @@ def compute_common_window_score(
     return round(score, 1), breakdown
 
 
-def compute_overlay_window_score(
-    overlay_summary: OverlayWindowSummary | None,
-) -> tuple[float | None, dict[str, float]]:
-    """Score an overlay on full-window capital growth and risk efficiency."""
-    if overlay_summary is None:
-        return None, {}
-
-    return_score = _normalize(overlay_summary.return_pct, low=0.0, high=180.0)
-    ann_score = _normalize(overlay_summary.annualized_return_pct, low=0.0, high=35.0)
-    sharpe_score = _normalize(overlay_summary.sharpe_ratio, low=0.0, high=3.0)
-    drawdown_score = _normalize_inverse(overlay_summary.max_drawdown_pct, low=12.0, high=2.5)
-    activity_score = _normalize(float(overlay_summary.day_count), low=250.0, high=1000.0)
-
-    score = (
-        return_score * 0.40
-        + ann_score * 0.15
-        + sharpe_score * 0.25
-        + drawdown_score * 0.15
-        + activity_score * 0.05
-    )
-    breakdown = {
-        "overlay_return": round(return_score, 1),
-        "overlay_annualized_return": round(ann_score, 1),
-        "overlay_sharpe": round(sharpe_score, 1),
-        "overlay_drawdown": round(drawdown_score, 1),
-        "overlay_activity": round(activity_score, 1),
-        "overlay_day_count": float(overlay_summary.day_count),
-    }
-    return round(score, 1), breakdown
-
-
-def compute_overlay_stress_gate(
-    overlay_stress_summary: OverlayWindowSummary | None,
-) -> tuple[float, dict[str, float]]:
-    """Gate overlay scores using a stress-period overlay run."""
-    if overlay_stress_summary is None:
-        return 0.0, {"requires_overlay_stress_window": 1.0}
-
-    pass_return = (overlay_stress_summary.return_pct or 0.0) >= 5.0
-    pass_sharpe = (overlay_stress_summary.sharpe_ratio or 0.0) >= 0.50
-    pass_drawdown = (overlay_stress_summary.max_drawdown_pct or 999.0) <= 10.0
-    pass_count = sum([pass_return, pass_sharpe, pass_drawdown])
-    gate_factor = {
-        3: 1.00,
-        2: 0.85,
-        1: 0.65,
-        0: 0.40,
-    }[pass_count]
-    return gate_factor, {
-        "overlay_gate_return": 1.0 if pass_return else 0.0,
-        "overlay_gate_sharpe": 1.0 if pass_sharpe else 0.0,
-        "overlay_gate_drawdown": 1.0 if pass_drawdown else 0.0,
-    }
-
-
-def compute_overlay_stress_quality(
-    overlay_stress_summary: OverlayWindowSummary | None,
-) -> tuple[float | None, dict[str, float]]:
-    """Diagnostic stress quality for overlay entries."""
-    if overlay_stress_summary is None:
-        return None, {}
-
-    return_score = _normalize(overlay_stress_summary.return_pct, low=0.0, high=20.0)
-    sharpe_score = _normalize(overlay_stress_summary.sharpe_ratio, low=0.0, high=1.5)
-    drawdown_score = _normalize_inverse(overlay_stress_summary.max_drawdown_pct, low=12.0, high=3.0)
-    quality = return_score * 0.45 + sharpe_score * 0.35 + drawdown_score * 0.20
-    breakdown = {
-        "overlay_stress_return": round(return_score, 1),
-        "overlay_stress_sharpe": round(sharpe_score, 1),
-        "overlay_stress_drawdown": round(drawdown_score, 1),
-    }
-    return round(quality, 1), breakdown
-
-
-def compute_overlay_public_sqs(
-    overlay_common_window_summary: OverlayWindowSummary | None,
-    overlay_stress_window_summary: OverlayWindowSummary | None,
-) -> tuple[float | None, dict[str, float], str | None]:
-    """Return the official overlay score."""
-    base_score, base_breakdown = compute_overlay_window_score(overlay_common_window_summary)
-    if base_score is None:
-        return None, {"requires_overlay_common_window": 1.0}, "pending_overlay_common_window"
-    gate_factor, gate_breakdown = compute_overlay_stress_gate(overlay_stress_window_summary)
-    if overlay_stress_window_summary is None:
-        return None, gate_breakdown, "pending_overlay_stress_window"
-    stress_quality, stress_breakdown = compute_overlay_stress_quality(overlay_stress_window_summary)
-    final_score = base_score * gate_factor
-    breakdown = {
-        "overlay_base_score": round(base_score, 1),
-        "overlay_gate_factor": round(gate_factor, 2),
-        **base_breakdown,
-        **gate_breakdown,
-        **stress_breakdown,
-    }
-    if stress_quality is not None:
-        breakdown["overlay_stress_quality"] = round(stress_quality, 1)
-    return round(final_score, 1), breakdown, "overlay_v1_common_window+stress_gate"
-
-
-def compute_overlay_stress_sqs(
-    overlay_common_window_summary: OverlayWindowSummary | None,
-    overlay_stress_window_summary: OverlayWindowSummary | None,
-) -> tuple[float | None, dict[str, float], str | None]:
-    """Legacy overlay score with an extra stress-quality penalty."""
-    base_score, base_breakdown = compute_overlay_window_score(overlay_common_window_summary)
-    if base_score is None:
-        return None, {"requires_overlay_common_window": 1.0}, "pending_overlay_common_window"
-    gate_factor, gate_breakdown = compute_overlay_stress_gate(overlay_stress_window_summary)
-    if overlay_stress_window_summary is None:
-        return None, gate_breakdown, "pending_overlay_stress_window"
-    stress_quality, stress_breakdown = compute_overlay_stress_quality(overlay_stress_window_summary)
-    quality_factor = 1.0
-    if stress_quality is not None:
-        quality_factor = 0.30 + 0.70 * (stress_quality / 100.0)
-    final_score = base_score * gate_factor * quality_factor
-    breakdown = {
-        "overlay_base_score": round(base_score, 1),
-        "overlay_gate_factor": round(gate_factor, 2),
-        "overlay_quality_factor": round(quality_factor, 2),
-        **base_breakdown,
-        **gate_breakdown,
-        **stress_breakdown,
-    }
-    if stress_quality is not None:
-        breakdown["overlay_stress_quality"] = round(stress_quality, 1)
-    return round(final_score, 1), breakdown, "overlay_v1_common_window+stress_quality"
-
-
 def _get_robustness_horizon_summary(
     summary: RobustnessMatrixSummary | None,
     horizon_days: int,
@@ -1745,32 +1616,6 @@ def refresh_public_scores(
             updated_entries.append(entry)
             continue
 
-        if entry.overlay_common_window_summary is not None:
-            overlay_sqs, overlay_breakdown, _ = compute_overlay_public_sqs(
-                entry.overlay_common_window_summary,
-                entry.overlay_stress_window_summary,
-            )
-            overlay_stress_sqs, overlay_stress_breakdown, _ = compute_overlay_stress_sqs(
-                entry.overlay_common_window_summary,
-                entry.overlay_stress_window_summary,
-            )
-            refreshed = entry.model_copy(
-                update={
-                    "sqs_score": overlay_sqs,
-                    "sqs_breakdown": overlay_breakdown,
-                    "sqs_v3_score": overlay_sqs,
-                    "sqs_v3_breakdown": overlay_breakdown,
-                    "stress_sqs_score": overlay_stress_sqs,
-                    "stress_sqs_breakdown": overlay_stress_breakdown,
-                    "common_window_score": None,
-                    "common_window_breakdown": {},
-                }
-            )
-            if refreshed.model_dump() != entry.model_dump():
-                updated_count += 1
-            updated_entries.append(refreshed)
-            continue
-
         test_result = _hydrate_split_result(entry.results.get("test"))
         valid_result = _hydrate_split_result(entry.results.get("valid"))
         train_result = _hydrate_split_result(entry.results.get("train"))
@@ -2036,7 +1881,6 @@ def filter_registry_entries(
     entries: list[RegistryEntry],
     *,
     include_retired: bool = False,
-    include_overlays: bool = False,
 ) -> list[RegistryEntry]:
     """Filter registry entries for the default surfaced leaderboard."""
     filtered = list(entries) if include_retired else [entry for entry in entries if not entry.is_retired]
@@ -2045,32 +1889,9 @@ def filter_registry_entries(
         for entry in filtered
         if (
             entry.sqs_score is not None
-            and (
-                (include_overlays and entry.strategy_family == "overlay")
-                or (
-                    entry.strategy_family != "overlay"
-                    and entry.trade_count > 0
-                    and entry.valid_trade_count > 0
-                )
-            )
-        )
-    ]
-
-
-def filter_overlay_registry_entries(
-    entries: list[RegistryEntry],
-    *,
-    include_retired: bool = False,
-) -> list[RegistryEntry]:
-    """Filter registry entries for the dedicated overlay leaderboard."""
-    filtered = list(entries) if include_retired else [entry for entry in entries if not entry.is_retired]
-    return [
-        entry
-        for entry in filtered
-        if (
-            entry.sqs_score is not None
-            and entry.strategy_family == "overlay"
-            and entry.overlay_common_window_summary is not None
+            and entry.strategy_family != "overlay"
+            and entry.trade_count > 0
+            and entry.valid_trade_count > 0
         )
     ]
 
@@ -2080,8 +1901,6 @@ def _is_retired_journal_entry(entry: JournalEntry) -> bool:
 
 
 def _is_complete_journal_entry(entry: JournalEntry) -> bool:
-    if entry.overlay_common_window_summary is not None:
-        return entry.sqs_score is not None
     test_result = entry.results.get("test")
     valid_result = entry.results.get("valid")
     return (
@@ -2365,37 +2184,7 @@ def rebuild_registry(
     for je in entries:
         strategy_family = classify_strategy_family(je.experiment_name, je.tags)
         is_retired = is_retired_strategy_family(strategy_family)
-
-        if je.overlay_common_window_summary is not None:
-            computed_overlay_sqs, _, _ = compute_overlay_public_sqs(
-                je.overlay_common_window_summary,
-                je.overlay_stress_window_summary,
-            )
-            computed_overlay_stress_sqs, _, _ = compute_overlay_stress_sqs(
-                je.overlay_common_window_summary,
-                je.overlay_stress_window_summary,
-            )
-            overlay = je.overlay_common_window_summary
-            registry_entries.append(
-                RegistryEntry(
-                    entry_id=je.entry_id,
-                    experiment_name=je.experiment_name,
-                    strategy_family=strategy_family,
-                    is_retired=is_retired,
-                    sqs_score=computed_overlay_sqs,
-                    sqs_v3_score=computed_overlay_sqs,
-                    stress_sqs_score=computed_overlay_stress_sqs,
-                    common_window_score=None,
-                    overlay_common_window_summary=je.overlay_common_window_summary,
-                    overlay_stress_window_summary=je.overlay_stress_window_summary,
-                    total_return_pct=overlay.return_pct,
-                    annualized_return_pct=overlay.annualized_return_pct,
-                    sharpe_ratio=overlay.sharpe_ratio,
-                    max_drawdown_pct=overlay.max_drawdown_pct,
-                    trade_count=0,
-                    timestamp=je.timestamp,
-                )
-            )
+        if strategy_family == "overlay":
             continue
 
         test_result = _hydrate_split_result(je.results.get("test"))
@@ -2540,9 +2329,8 @@ def rebuild_registry(
     registry_path.parent.mkdir(parents=True, exist_ok=True)
     registry_path.write_text(registry.model_dump_json(indent=2))
 
-    # Write LEADERBOARD.md and OVERLAY_LEADERBOARD.md
+    # Write LEADERBOARD.md
     _write_leaderboard_md(leaderboard_path, registry, entries)
-    _write_overlay_leaderboard_md(leaderboard_path.parent / "OVERLAY_LEADERBOARD.md", registry, entries)
 
     logger.info("registry_rebuilt", count=len(registry_entries))
     return registry
@@ -2556,7 +2344,6 @@ def _write_leaderboard_md(
     visible_entries = filter_registry_entries(
         registry.entries,
         include_retired=False,
-        include_overlays=False,
     )
     visible_recent = [
         entry
@@ -2570,7 +2357,7 @@ def _write_leaderboard_md(
     lines: list[str] = []
     lines.append("# Strategy Improvement Leaderboard")
     lines.append(f"_Updated: {registry.updated_at}_\n")
-    lines.append("_Default view excludes overlay/book-of-books rows, retired legacy PEAD / short-core / exact-pocket families, and incomplete train-only scans. Use `fithia2 lb --overlay` for overlays or `fithia2 lb --include-retired` to inspect archived research._\n")
+    lines.append("_Default view excludes retired legacy PEAD / short-core / exact-pocket families and incomplete train-only scans. Use `fithia2 lb --include-retired` to inspect archived research._\n")
     lines.append("_`SQS` below is public SQS v4: v3 deployment/WFV-first ranking plus a modest common-window capital-growth term when available. Stress OOT remains an eligibility gate. Prior v3 values remain in `experiment_registry.json` as `sqs_v3_score`._\n")
     lines.append("| # | Experiment | SQS | [Tr]Ret% | [V]Ret% | [T]Ret% | [T]Ann% | [T]DD% | [T]Gross% | [T]DIM% | [T]R/G | Date |")
     lines.append("|---|-----------|-----|----------|----------|----------|----------|--------|------------|----------|---------|------|")
@@ -2621,62 +2408,6 @@ def _write_leaderboard_md(
     path.write_text("\n".join(lines) + "\n")
 
 
-def _write_overlay_leaderboard_md(
-    path: Path,
-    registry: ExperimentRegistry,
-    journal_entries: list[JournalEntry],
-) -> None:
-    visible_entries = filter_overlay_registry_entries(registry.entries, include_retired=False)
-    visible_recent = [
-        entry
-        for entry in reversed(journal_entries)
-        if (
-            not _is_retired_journal_entry(entry)
-            and _is_complete_journal_entry(entry)
-            and classify_strategy_family(entry.experiment_name, entry.tags) == "overlay"
-        )
-    ][:5]
-    lines: list[str] = []
-    lines.append("# Overlay Strategy Leaderboard")
-    lines.append(f"_Updated: {registry.updated_at}_\n")
-    lines.append("_This board is separate from the default single-book leaderboard. Overlay rows are book-of-books evaluations and are not directly comparable to single-book `SQS` rows._\n")
-    lines.append("_`SQS` here is overlay official SQS: common-window overlay score with a stress OOT gate. `T.*` columns are common-window overlay metrics._\n")
-    lines.append("| # | Overlay | SQS | [T]Ret% | [T]Ann% | [T]DD% | Stress Ret% | Stress DD% | Stress Sharpe | Date |")
-    lines.append("|---|---------|-----|----------|----------|--------|-------------|------------|---------------|------|")
-
-    for rank, e in enumerate(visible_entries, 1):
-        stress = e.overlay_stress_window_summary
-        ts = e.timestamp[:10] if e.timestamp else "-"
-        stress_ret = f"{stress.return_pct:+.1f}" if stress and stress.return_pct is not None else "-"
-        stress_dd = f"{stress.max_drawdown_pct:.1f}" if stress and stress.max_drawdown_pct is not None else "-"
-        stress_sharpe = f"{stress.sharpe_ratio:+.2f}" if stress and stress.sharpe_ratio is not None else "-"
-        lines.append(
-            f"| {rank} | {e.experiment_name} | {e.sqs_score:.1f}"
-            f" | {e.total_return_pct:+.1f} | {e.annualized_return_pct:+.1f} | {e.max_drawdown_pct:.1f}"
-            f" | {stress_ret}"
-            f" | {stress_dd}"
-            f" | {stress_sharpe}"
-            f" | {ts} |"
-        )
-
-    if visible_recent:
-        lines.append("\n## Recent Overlay Entries")
-        registry_by_id = {entry.entry_id: entry for entry in registry.entries}
-        for je in visible_recent:
-            canonical_sqs = registry_by_id.get(je.entry_id).sqs_score if je.entry_id in registry_by_id else je.sqs_score
-            lines.append(f"### {je.entry_id} ({je.timestamp[:10]}) — {je.experiment_name}")
-            lines.append(f"Hypothesis: {je.hypothesis}")
-            lines.append(f"Verdict: **{je.verdict.upper()}** (SQS {canonical_sqs})")
-            if je.verdict_reasoning:
-                lines.append(f"Reasoning: {je.verdict_reasoning}")
-            if je.next_direction:
-                lines.append(f"Next: {je.next_direction}")
-            lines.append("")
-
-    path.parent.mkdir(parents=True, exist_ok=True)
-    path.write_text("\n".join(lines) + "\n")
-
-
 # ---------------------------------------------------------------------------
 # Run scanning helpers (for CLI record command)
 # ---------------------------------------------------------------------------
diff --git a/tests/unit/backtest/test_overlay.py b/tests/unit/backtest/test_overlay.py
deleted file mode 100644
index 22d0b91..0000000
--- a/tests/unit/backtest/test_overlay.py
+++ /dev/null
@@ -1,76 +0,0 @@
-from __future__ import annotations
-
-import datetime as dt
-
-import pandas as pd
-
-from libs.backtest.overlay import build_overlay_curve, summarize_overlay_curve, validate_allocations
-
-
-def test_validate_allocations_requires_unknown_and_unit_sum() -> None:
-    try:
-        validate_allocations({"risk_on": {"core": 1.0}}, {"core"})
-    except ValueError as exc:
-        assert "unknown" in str(exc)
-    else:
-        raise AssertionError("expected ValueError")
-
-    try:
-        validate_allocations({"unknown": {"core": 0.8}}, {"core"})
-    except ValueError as exc:
-        assert "sum to 1.0" in str(exc)
-    else:
-        raise AssertionError("expected ValueError")
-
-
-def test_build_overlay_curve_switches_by_regime() -> None:
-    dates = [dt.date(2024, 1, 2), dt.date(2024, 1, 3), dt.date(2024, 1, 4)]
-    core = pd.DataFrame(
-        {
-            "date": dates,
-            "equity": [100.0, 110.0, 104.5],
-            "daily_return": [0.0, 0.10, -0.05],
-        }
-    )
-    mom = pd.DataFrame(
-        {
-            "date": dates,
-            "equity": [100.0, 105.0, 110.25],
-            "daily_return": [0.0, 0.05, 0.05],
-        }
-    )
-    regimes = {
-        dates[0]: "risk_on",
-        dates[1]: "risk_off",
-        dates[2]: "risk_on",
-    }
-    allocations = {
-        "risk_on": {"core": 0.0, "mom": 1.0},
-        "risk_off": {"core": 1.0, "mom": 0.0},
-        "unknown": {"core": 1.0, "mom": 0.0},
-    }
-
-    curve = build_overlay_curve(
-        curves={"core": core, "mom": mom},
-        allocations=allocations,
-        regimes_by_date=regimes,
-        initial_equity=100.0,
-    )
-
-    assert curve["overlay_return"].round(6).tolist() == [0.0, 0.10, 0.05]
-    assert round(float(curve["overlay_equity"].iloc[-1]), 4) == 115.5
-
-
-def test_summarize_overlay_curve_reports_return_drawdown_and_regimes() -> None:
-    curve = pd.DataFrame(
-        {
-            "date": [dt.date(2024, 1, 2), dt.date(2024, 1, 3), dt.date(2024, 1, 4)],
-            "regime": ["risk_on", "risk_off", "risk_on"],
-            "overlay_return": [0.0, -0.10, 0.05],
-            "overlay_equity": [100.0, 90.0, 94.5],
-        }
-    )
-    summary = summarize_overlay_curve(curve, initial_equity=100.0)
-    assert round(summary["return_pct"], 4) == -5.5
-    assert round(summary["max_dd_pct"], 4) == 10.0
-    assert summary["regime_day_counts"] == {"risk_off": 1, "risk_on": 2}
diff --git a/tests/unit/backtest/test_tracker.py b/tests/unit/backtest/test_tracker.py
index cb11fcf..1e9bf6d 100644
--- a/tests/unit/backtest/test_tracker.py
+++ b/tests/unit/backtest/test_tracker.py
@@ -13,7 +13,6 @@ from libs.backtest.domain import (
     CommonWindowSummary,
     JournalEntry,
     MetricsBundle,
-    OverlayWindowSummary,
     RobustnessHorizonSummary,
     RobustnessMatrixSummary,
     SplitResult,
@@ -44,8 +43,6 @@ from libs.backtest.tracker import (
     compute_public_sqs_v3,
     compute_public_sqs_v4,
     compute_common_window_score,
-    compute_overlay_public_sqs,
-    compute_overlay_stress_sqs,
     compute_promotion_score,
     _compute_oot_positive_rate_63plus,
     compute_oot_robustness_gate,
@@ -58,7 +55,6 @@ from libs.backtest.tracker import (
     compute_unified_split_quality,
     compute_wfqs,
     compute_wfqs_v2,
-    filter_overlay_registry_entries,
     filter_registry_entries,
     get_next_entry_id,
     journal_lock,
@@ -900,61 +896,6 @@ class TestCommonWindowScore:
         assert v4_strong > v4_weak
 
 
-class TestOverlayPublicScore:
-    def test_rewards_strong_overlay_with_positive_stress_window(self):
-        overlay = OverlayWindowSummary(
-            overlay_name="return_book_overlay_v3",
-            start_date=dt.date(2022, 3, 3),
-            end_date=dt.date(2026, 3, 13),
-            return_pct=145.0,
-            annualized_return_pct=26.0,
-            max_drawdown_pct=4.5,
-            sharpe_ratio=2.62,
-            day_count=1014,
-        )
-        stress = OverlayWindowSummary(
-            overlay_name="return_book_overlay_v3",
-            start_date=dt.date(2020, 1, 2),
-            end_date=dt.date(2021, 12, 31),
-            return_pct=5.95,
-            annualized_return_pct=2.9,
-            max_drawdown_pct=5.37,
-            sharpe_ratio=0.67,
-            day_count=508,
-        )
-        public_score, breakdown, source = compute_overlay_public_sqs(overlay, stress)
-        stress_score, _, _ = compute_overlay_stress_sqs(overlay, stress)
-        assert source == "overlay_v1_common_window+stress_gate"
-        assert public_score is not None and public_score > 0
-        assert stress_score is not None and stress_score <= public_score
-        assert breakdown["overlay_gate_factor"] == 1.0
-
-    def test_penalizes_overlay_with_flat_negative_stress_window(self):
-        overlay = OverlayWindowSummary(
-            overlay_name="return_book_overlay_v1",
-            start_date=dt.date(2022, 3, 3),
-            end_date=dt.date(2026, 3, 13),
-            return_pct=153.89,
-            annualized_return_pct=27.0,
-            max_drawdown_pct=4.52,
-            sharpe_ratio=2.72,
-            day_count=1014,
-        )
-        weak_stress = OverlayWindowSummary(
-            overlay_name="return_book_overlay_v1",
-            start_date=dt.date(2020, 1, 2),
-            end_date=dt.date(2021, 12, 31),
-            return_pct=-1.26,
-            annualized_return_pct=-0.6,
-            max_drawdown_pct=3.15,
-            sharpe_ratio=-0.16,
-            day_count=508,
-        )
-        public_score, breakdown, _ = compute_overlay_public_sqs(overlay, weak_stress)
-        assert public_score is not None
-        assert breakdown["overlay_gate_factor"] == 0.65
-
-
 class TestComputeRQS:
     def test_requires_valid_and_test(self):
         score, breakdown = compute_rqs(None, None, None)
@@ -1934,56 +1875,27 @@ class TestRebuildRegistry:
         assert "| # |" in lb_text
         assert "| # | Experiment | SQS | [Tr]Ret% | [V]Ret% | [T]Ret% | [T]Ann% | [T]DD% | [T]Gross% | [T]DIM% | [T]R/G | Date |" in lb_text
 
-    def test_registry_and_leaderboard_split_overlay_entry(self, tmp_path):
+    def test_registry_skips_legacy_overlay_entries(self, tmp_path):
         journal_path = tmp_path / "journal.jsonl"
         registry_path = tmp_path / "registry.json"
         leaderboard_path = tmp_path / "LEADERBOARD.md"
-        overlay_leaderboard_path = tmp_path / "OVERLAY_LEADERBOARD.md"
 
         entry = JournalEntry(
             entry_id="IMP-0001",
             timestamp="2026-03-25T22:00:00+00:00",
             experiment_name="return_book_overlay_v3",
             hypothesis="overlay",
-            overlay_common_window_summary=OverlayWindowSummary(
-                overlay_name="return_book_overlay_v3",
-                start_date=dt.date(2022, 3, 3),
-                end_date=dt.date(2026, 3, 13),
-                return_pct=145.0,
-                annualized_return_pct=26.0,
-                max_drawdown_pct=4.5,
-                sharpe_ratio=2.62,
-                day_count=1014,
-            ),
-            overlay_stress_window_summary=OverlayWindowSummary(
-                overlay_name="return_book_overlay_v3",
-                start_date=dt.date(2020, 1, 2),
-                end_date=dt.date(2021, 12, 31),
-                return_pct=5.95,
-                annualized_return_pct=2.9,
-                max_drawdown_pct=5.37,
-                sharpe_ratio=0.67,
-                day_count=508,
-            ),
             tags=["overlay"],
         )
         append_journal_entry(journal_path, entry)
 
         registry = rebuild_registry(journal_path, registry_path, leaderboard_path)
         visible = filter_registry_entries(registry.entries)
-        overlay_visible = filter_overlay_registry_entries(registry.entries)
         assert len(visible) == 0
-        assert len(overlay_visible) == 1
-        assert overlay_visible[0].strategy_family == "overlay"
-        assert overlay_visible[0].sqs_score is not None
-        assert overlay_visible[0].total_return_pct == 145.0
-        assert overlay_visible[0].annualized_return_pct == 26.0
+        assert registry.entries == []
         lb_text = leaderboard_path.read_text()
-        overlay_lb_text = overlay_leaderboard_path.read_text()
         assert "return_book_overlay_v3" not in lb_text
-        assert "Default view excludes overlay/book-of-books rows" in lb_text
-        assert "return_book_overlay_v3" in overlay_lb_text
-        assert "Overlay Strategy Leaderboard" in overlay_lb_text
+        assert "Default view excludes retired legacy PEAD" in lb_text
 
     def test_registry_preserves_walk_forward_summary(self, tmp_path):
         journal_path = tmp_path / "journal.jsonl"
diff --git a/tests/unit/paper_trader/test_cli.py b/tests/unit/paper_trader/test_cli.py
index cccabd0..1babcc7 100644
--- a/tests/unit/paper_trader/test_cli.py
+++ b/tests/unit/paper_trader/test_cli.py
@@ -8,7 +8,7 @@ from rich.console import Console
 from apps.paper_trader import cli
 
 
-def test_resolve_rank_configs_skips_overlay_rows_and_warns(tmp_path: Path, monkeypatch) -> None:
+def test_resolve_rank_configs_selects_runnable_single_book_rows(tmp_path: Path, monkeypatch) -> None:
     monkeypatch.chdir(tmp_path)
     journal_dir = tmp_path / "journal"
     journal_dir.mkdir(parents=True)
@@ -19,17 +19,16 @@ def test_resolve_rank_configs_skips_overlay_rows_and_warns(tmp_path: Path, monke
     registry = {
         "entries": [
             {
-                "experiment_name": "return_book_overlay_v3",
-                "strategy_family": "overlay",
+                "experiment_name": "return_max_long_missing",
+                "strategy_family": "return_max_long",
                 "sqs_score": 81.6,
-                "trade_count": 0,
-                "valid_trade_count": 0,
-                "overlay_common_window_summary": {"return_pct": 145.0},
+                "trade_count": 10,
+                "valid_trade_count": 3,
                 "is_retired": False,
             },
             {
                 "experiment_name": "return_max_long_demo",
-                "strategy_family": "pead",
+                "strategy_family": "return_max_long",
                 "sqs_score": 70.0,
                 "trade_count": 10,
                 "valid_trade_count": 3,
@@ -46,6 +45,4 @@ def test_resolve_rank_configs_skips_overlay_rows_and_warns(tmp_path: Path, monke
     configs = cli._resolve_rank_configs(1, 1)
 
     assert configs == ["configs/experiments/return_max_long_demo.json"]
-    output = console.export_text()
-    assert "Skipping overlay leaderboard entries for `--top/--rank`" in output
-    assert "return_book_overlay_v3" in output
+    assert console.export_text() == ""
diff --git a/tests/unit/paper_trader/test_overlay_backtest.py b/tests/unit/paper_trader/test_overlay_backtest.py
deleted file mode 100644
index 80d9428..0000000
--- a/tests/unit/paper_trader/test_overlay_backtest.py
+++ /dev/null
@@ -1,75 +0,0 @@
-from __future__ import annotations
-
-import datetime as dt
-import json
-from pathlib import Path
-
-import pandas as pd
-
-from apps.paper_trader.backtest_sim import run_overlay_backtest_sync
-
-
-def _write_equity_csv(path: Path, rows: list[tuple[str, float]]) -> None:
-    df = pd.DataFrame(rows, columns=["date", "equity"])
-    path.parent.mkdir(parents=True, exist_ok=True)
-    df.to_csv(path, index=False)
-
-
-def test_run_overlay_backtest_sync_replays_frozen_equity_csv(tmp_path: Path) -> None:
-    core_csv = tmp_path / "core.csv"
-    mom_csv = tmp_path / "mom.csv"
-    _write_equity_csv(core_csv, [("2025-01-02", 100.0), ("2025-01-03", 110.0), ("2025-01-06", 121.0)])
-    _write_equity_csv(mom_csv, [("2025-01-02", 100.0), ("2025-01-03", 90.0), ("2025-01-06", 81.0)])
-
-    spec = {
-        "overlay_name": "overlay_demo",
-        "books": [
-            {"label": "core", "equity_csv": str(core_csv)},
-            {"label": "mom", "equity_csv": str(mom_csv)},
-        ],
-        "allocations": {
-            "unknown": {"core": 0.5, "mom": 0.5},
-        },
-    }
-    spec_path = tmp_path / "overlay.json"
-    spec_path.write_text(json.dumps(spec))
-
-    result = run_overlay_backtest_sync(
-        overlay_config_path=str(spec_path),
-        capital=100.0,
-        start_date=dt.date(2025, 1, 2),
-        end_date=dt.date(2025, 1, 6),
-    )
-
-    assert result["is_overlay"] is True
-    assert result["overlay_replay_mode"] == "frozen_equity_csv"
-    assert round(result["summary"]["return_pct"], 4) == 0.0
-    assert result["summary"]["trade_count"] == 0
-
-
-def test_run_overlay_backtest_sync_rebases_window_from_frozen_curves(tmp_path: Path) -> None:
-    core_csv = tmp_path / "core.csv"
-    _write_equity_csv(core_csv, [("2025-01-02", 100.0), ("2025-01-03", 200.0), ("2025-01-06", 400.0)])
-
-    spec = {
-        "overlay_name": "overlay_demo",
-        "books": [
-            {"label": "core", "equity_csv": str(core_csv)},
-        ],
-        "allocations": {
-            "unknown": {"core": 1.0},
-        },
-    }
-    spec_path = tmp_path / "overlay.json"
-    spec_path.write_text(json.dumps(spec))
-
-    result = run_overlay_backtest_sync(
-        overlay_config_path=str(spec_path),
-        capital=100.0,
-        start_date=dt.date(2025, 1, 3),
-        end_date=dt.date(2025, 1, 6),
-    )
-
-    assert result["overlay_replay_mode"] == "frozen_equity_csv"
-    assert round(result["summary"]["return_pct"], 4) == 100.0
-    assert round(result["summary"]["final_equity"], 4) == 200.0
diff --git a/tests/unit/tools/test_evaluate_book_overlay.py b/tests/unit/tools/test_evaluate_book_overlay.py
deleted file mode 100644
index 8d390ac..0000000
--- a/tests/unit/tools/test_evaluate_book_overlay.py
+++ /dev/null
@@ -1,69 +0,0 @@
-from __future__ import annotations
-
-import datetime as dt
-
-from apps.tools import evaluate_book_overlay as mod
-
-
-class _FakeStore:
-    def __init__(self) -> None:
-        self._dates = [dt.date(2025, 1, 2), dt.date(2025, 1, 3)]
-
-    def slice_by_date_range(self, start: dt.date, end: dt.date):
-        self._dates = [d for d in self._dates if start <= d <= end]
-        return self
-
-    def all_trading_days(self):
-        return list(self._dates)
-
-    def get_macro_for_date(self, date: dt.date):
-        return {"state": f"regime-{date.isoformat()}"}
-
-
-def test_compute_regimes_uses_merged_store(monkeypatch) -> None:
-    fake_store = _FakeStore()
-
-    monkeypatch.setattr(mod, "load_manifest", lambda path: object())
-    monkeypatch.setattr(mod, "resolve_config", lambda manifest, config_root=".": object())
-    monkeypatch.setattr(mod, "_build_merged_snapshot_store", lambda manifest, config, snapshot_dir_override=None: fake_store)
-    monkeypatch.setattr(mod, "_macro_regime_state", lambda config, macro: macro["state"])
-
-    regimes = mod._compute_regimes(
-        snapshot_dir="data/parquet/example_snapshot",
-        split="train",
-        config_path="configs/experiments/example.json",
-        start_date=dt.date(2025, 1, 2),
-        end_date=dt.date(2025, 1, 3),
-    )
-
-    assert regimes == {
-        dt.date(2025, 1, 2): "regime-2025-01-02",
-        dt.date(2025, 1, 3): "regime-2025-01-03",
-    }
-
-
-def test_compute_regimes_prefers_explicit_snapshot_dir(monkeypatch, tmp_path) -> None:
-    snapshot_dir = tmp_path / "snap"
-    snapshot_dir.mkdir()
-    (snapshot_dir / "train.parquet").write_text("stub")
-
-    fake_store = _FakeStore()
-
-    monkeypatch.setattr(mod, "load_manifest", lambda path: object())
-    monkeypatch.setattr(mod, "resolve_config", lambda manifest, config_root=".": object())
-    monkeypatch.setattr(mod, "load_merged_store_from_snapshot_dir", lambda snapshot_dir, oracle_url, db_dsn: fake_store)
-    monkeypatch.setattr(mod, "_build_merged_snapshot_store", lambda *args, **kwargs: (_ for _ in ()).throw(AssertionError("should not be called")))
-    monkeypatch.setattr(mod, "_macro_regime_state", lambda config, macro: macro["state"])
-
-    regimes = mod._compute_regimes(
-        snapshot_dir=snapshot_dir,
-        split="train",
-        config_path="configs/experiments/example.json",
-        start_date=dt.date(2025, 1, 2),
-        end_date=dt.date(2025, 1, 3),
-    )
-
-    assert regimes == {
-        dt.date(2025, 1, 2): "regime-2025-01-02",
-        dt.date(2025, 1, 3): "regime-2025-01-03",
-    }