refactor: rename stock-lab → stock (graduation)

- git mv stock-lab/ → stock/
- docker-compose.yml: 서비스 키 + container_name + build.context +
  frontend.depends_on + agent-office STOCK_LAB_URL → STOCK_URL
- agent-office/app: config.py, service_proxy.py, agents/stock.py, tests/
  STOCK_LAB_URL → STOCK_URL
- nginx/default.conf: proxy_pass http://stock-lab → http://stock (3 lines)
- CLAUDE.md / README.md / STATUS.md / scripts/ 문구 갱신
- stock/ 내부 자기 참조 갱신

lab 네이밍 정책 (feedback_lab_naming.md) graduation.
API URL / Python import / DB 파일명 변경 없음.

stock/app/screener/nodes/vcp_lite.py

@@ -0,0 +1,40 @@
+"""VCP-lite — 단기/장기 일중 변동성 비율 기반 수축률."""
+
+import pandas as pd
+
+from .base import ScoreNode, percentile_rank
+
+
+class VcpLite(ScoreNode):
+    name  = "vcp_lite"
+    label = "VCP-lite (변동성 수축)"
+    default_params = {"short_window": 40, "long_window": 252}
+    param_schema = {
+        "type": "object",
+        "properties": {
+            "short_window": {"type": "integer", "minimum": 10, "maximum": 120, "default": 40},
+            "long_window":  {"type": "integer", "minimum": 60, "maximum": 504, "default": 252},
+        },
+    }
+
+    def compute(self, ctx, params: dict) -> pd.Series:
+        short_w = int(params.get("short_window", 40))
+        long_w  = int(params.get("long_window", 252))
+        prices = ctx.prices
+        if prices.empty:
+            return pd.Series(dtype=float)
+
+        ordered = prices.sort_values("date").copy()
+        ordered["range_pct"] = (ordered["high"] - ordered["low"]) / ordered["close"]
+
+        def _ratio(s: pd.Series) -> float:
+            if len(s) < long_w:
+                return float("nan")
+            short_vol = s.tail(short_w).mean()
+            long_vol  = s.tail(long_w).mean()
+            if long_vol == 0 or pd.isna(long_vol):
+                return float("nan")
+            return 1 - (short_vol / long_vol)
+
+        raw = ordered.groupby("ticker", group_keys=False)["range_pct"].apply(_ratio)
+        return percentile_rank(raw).fillna(50.0)