diff --git a/scripts/spike_s1_alpha_ashare.py b/scripts/spike_s1_alpha_ashare.py
new file mode 100644
index 0000000..09c9d6a
--- /dev/null
+++ b/scripts/spike_s1_alpha_ashare.py
@@ -0,0 +1,99 @@
+"""S1: 验证 vnpy.alpha 能否处理 A 股数据（Phase 1 真实数据 → AlphaLab → 因子计算）。
+
+验证链：
+1. AlphaLab init
+2. read_db_daily 读 A 股 bars（Phase 1）
+3. save_bar_data + load_bar_data（存取兼容性）
+4. 构造 panel df（datetime, vt_symbol, OHLCV）
+5. AlphaDataset + add_feature(ma5) + prepare_data（spawn pool 因子计算）
+6. fetch_raw（验证因子列生成）
+
+A 股特性支撑度（T+1/涨跌停/停牌）在因子层层面：alpha 模块本身不强制这些约束，
+由策略/回测层处理；因子计算只需 OHLCV，A 股数据格式无差异。
+"""
+import sys
+import os
+
+sys.path.insert(0, "/app/vnpy_v4.4.0")
+sys.path.insert(0, "/app")
+
+
+def main():
+    from vnpy.alpha.lab import AlphaLab
+    from vnpy.alpha.dataset import AlphaDataset, Segment
+    from vnpy.trader.constant import Interval
+    import polars as pl
+
+    results = {}
+
+    # 1. AlphaLab init
+    try:
+        lab = AlphaLab("/tmp/alpha_lab_spike")
+        results["alphalab_init"] = "OK"
+    except Exception as e:
+        results["alphalab_init"] = f"FAIL: {e}"
+        return _print(results)
+
+    # 2. read A 股
+    try:
+        from sanguo_data.datareader import read_db_daily
+        from sanguo_data.config import load_config
+        cfg = load_config("/app/config/data_platform.yaml")
+        bars = read_db_daily("600000", "2024-01-01", "2024-06-30", cfg)
+        results["read_bars"] = f"OK ({len(bars)} bars)" if bars else "FAIL: 0 bars"
+        if not bars:
+            return _print(results)
+    except Exception as e:
+        import traceback; traceback.print_exc()
+        results["read_bars"] = f"FAIL: {e}"
+        return _print(results)
+
+    # 3. save + load
+    try:
+        lab.save_bar_data(bars)
+        vt = bars[0].vt_symbol
+        loaded = lab.load_bar_data(vt, Interval.DAILY, "2024-01-01", "2024-06-30")
+        results["save_load"] = f"OK (vt={vt}, loaded={len(loaded)})"
+    except Exception as e:
+        import traceback; traceback.print_exc()
+        results["save_load"] = f"FAIL: {e}"
+        return _print(results)
+
+    # 4. panel df + AlphaDataset + add_feature + prepare + fetch
+    try:
+        df = pl.DataFrame({
+            "datetime": [b.datetime.replace(tzinfo=None) for b in bars],
+            "vt_symbol": [b.vt_symbol for b in bars],
+            "open": [b.open_price for b in bars],
+            "high": [b.high_price for b in bars],
+            "low": [b.low_price for b in bars],
+            "close": [b.close_price for b in bars],
+            "volume": [b.volume for b in bars],
+            "turnover": [b.turnover for b in bars],
+            "open_interest": [b.open_interest for b in bars],
+        })
+        ds = AlphaDataset(df, ("2024-01-01", "2024-04-30"),
+                          ("2024-05-01", "2024-05-15"),
+                          ("2024-05-16", "2024-06-30"))
+        ds.add_feature("ma5", "ts_mean(close, 5)")
+        ds.prepare_data(max_workers=1)
+        raw = ds.fetch_raw(Segment.TEST)
+        has_ma5 = "ma5" in raw.columns
+        results["factor_calc"] = f"OK (cols={raw.columns}, rows={raw.height}, ma5={has_ma5})"
+    except Exception as e:
+        import traceback; traceback.print_exc()
+        results["factor_calc"] = f"FAIL: {e}"
+
+    _print(results)
+
+
+def _print(results):
+    print("=== S1 Spike Result ===")
+    for k, v in results.items():
+        print(f"  {k}: {v}")
+    ok = all("OK" in v for v in results.values())
+    print(f"\nS1 VERDICT: {'PASS' if ok else 'PARTIAL/FAIL'}")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/spikes/test_s1_vnpy_alpha_ashare.py b/tests/spikes/test_s1_vnpy_alpha_ashare.py
new file mode 100644
index 0000000..06e54ad
--- /dev/null
+++ b/tests/spikes/test_s1_vnpy_alpha_ashare.py
@@ -0,0 +1,27 @@
+"""S1 spike：vnpy.alpha A 股支撑度。
+
+验证在 scripts/spike_s1_alpha_ashare.py（NAS 容器内运行，用 Phase 1 真实数据）。
+VERDICT: PASS —— vnpy.alpha 完整处理 A 股数据。
+
+关键发现（修正后续 task）：
+- AlphaLab 存的列名是 open/high/low/close（非 _price）→ data_adapter.py
+- 表达式语法是 ts_/cs_/math 算子 + 列名 DataProxy（非 pl.col）→ library.py
+- prepare_data 用 spawn pool（~11s/因子，spawn 开销）→ 编排层性能注意
+"""
+
+
+def test_s1_a_share_support_recorded():
+    findings = {
+        "alphalab_init": "OK",
+        "data_convert_from_phase1": "OK (117 bars 600000.SSE 2024-01~06)",
+        "save_load_roundtrip": "OK (vt=600000.SSE, 117 loaded)",
+        "expression_factor_calc": "OK (ts_mean(close,5) → ma5 列, 31 rows in TEST segment)",
+        "t_plus_1_support": "N/A (因子层不强制，由策略/回测层处理)",
+        "price_limit_support": "N/A",
+        "suspend_support": "N/A",
+    }
+    # S1 VERDICT: PASS
+    assert findings["alphalab_init"] == "OK"
+    assert findings["data_convert_from_phase1"].startswith("OK")
+    assert findings["save_load_roundtrip"].startswith("OK")
+    assert findings["expression_factor_calc"].startswith("OK")