diff --git a/app.py b/app.py
index d61614e..d7dd6a6 100644
--- a/app.py
+++ b/app.py
@@ -164,14 +164,28 @@ def _json_response(body: bytes, etag: str | None = None) -> Response:
 # /cell bundle, and the offline migrate script. HTTP semantics (audit runs, cache
 # lookups, etags) stay in the endpoints; `run` is the audit run or None.
 
-def _build_grade(cell, target, days, history, recent, cache_meta, place, run=None) -> dict:
-    """/grade payload: the last `days` observed days graded against their own
-    ±7-day windows, plus the target day's climatology summary."""
+def _build_grade(cell, target, days, history, recent, cache_meta, place, run=None, after=14) -> dict:
+    """/grade payload: a window of days centered on the target — `days` of history
+    before it, the target itself, then up to `after` days after it — plus the
+    target day's climatology summary. Days after the target are observed when they
+    are already in the past and forecast when they run into the future, so the
+    weekly view can frame two weeks of history around the orange target marker and
+    trail off into up to 14 days of observations / forecast after it. The forecast
+    only reaches ~7 days out, so a recent target naturally yields some observed days
+    plus 1-7 forecast days, while an older target fills the whole 14 with real obs."""
     run = run or _NullRun()
     with run.phase("grading"):
-        # Only grade observed days up to and including the target date (last `days`).
-        recent = recent[recent["date"] <= target].sort_values("date").tail(days)
-        graded = _grade_rows(history, recent)
+        lo = target - pd.Timedelta(days=days)
+        hi = target + pd.Timedelta(days=after)
+        # Build the window from both sources. The recent+forecast bundle covers the
+        # last few weeks plus the forward forecast (the only source for future days);
+        # the archive reaches decades back for targets older than that bundle. Prefer
+        # the bundle row for any given date, filling the rest from the archive.
+        rwin = recent[(recent["date"] >= lo) & (recent["date"] <= hi)]
+        hwin = history[(history["date"] >= lo) & (history["date"] <= hi)]
+        hwin = hwin[~hwin["date"].isin(set(rwin["date"]))]
+        window = pd.concat([rwin, hwin]).sort_values("date")
+        graded = _grade_rows(history, window)
         _attach_dry_streaks(graded, history, recent)
         graded.reverse()  # newest first for display
         climo = grading.climatology(history, int(target.dayofyear))
@@ -331,7 +345,10 @@ def api_grade(
     lat: float = Query(..., ge=-90, le=90),
     lon: float = Query(..., ge=-180, le=180),
     date: str | None = Query(None, description="target date YYYY-MM-DD (default today)"),
-    days: int = Query(14, ge=1, le=60, description="how many recent days to grade"),
+    days: int = Query(14, ge=1, le=60, description="days of history to grade before the target"),
+    after: int = Query(14, ge=0, le=14,
+                       description="days to grade after the target (observed, or forecast when future; "
+                                   "the forecast reaches ~7 days out so future days cap there)"),
 ):
     if not grid.in_north_america(lat, lon):
         raise HTTPException(
@@ -365,7 +382,7 @@ def api_grade(
         if history.empty:
             raise HTTPException(status_code=404, detail="No historical data for this cell.")
 
-        key = f"{target.date().isoformat()}:{days}"
+        key = f"{target.date().isoformat()}:{days}:{after}"
         token = f"{PAYLOAD_VER}:{_hist_end(history)}:{climate.recent_stamp(cell['id'])}"
         etag = _etag_for("grade", cell["id"], key, token)
         if _not_modified(request, etag):
@@ -378,7 +395,7 @@ def api_grade(
 
         with run.phase("reverse_geocode"):
             place = climate.reverse_geocode(cell["center_lat"], cell["center_lon"])
-        payload = _build_grade(cell, target, days, history, recent, cache_meta, place, run)
+        payload = _build_grade(cell, target, days, history, recent, cache_meta, place, run, after=after)
         return _json_response(store.put_payload("grade", cell["id"], key, token, payload), etag)
 
 
@@ -647,8 +664,8 @@ def api_cell(
         else:
             rf_token = f"{PAYLOAD_VER}:{hist_end}:{climate.recent_stamp(cid)}"
             slices["grade"] = slice_for(
-                "grade", f"{today.date().isoformat()}:14", rf_token,
-                lambda: _build_grade(cell, today, 14, history, recent, cache_meta, place, run))
+                "grade", f"{today.date().isoformat()}:14:14", rf_token,
+                lambda: _build_grade(cell, today, 14, history, recent, cache_meta, place, run, after=14))
             slices["forecast"] = slice_for(
                 "forecast", f"{today.date().isoformat()}:7", rf_token,
                 lambda: _build_forecast(cell, 7, history, recent, today, place, run))