diff --git a/custom-skills/35-seo-signal-validation/code/CLAUDE.md b/custom-skills/35-seo-signal-validation/code/CLAUDE.md
index 4501a1b..da26660 100644
--- a/custom-skills/35-seo-signal-validation/code/CLAUDE.md
+++ b/custom-skills/35-seo-signal-validation/code/CLAUDE.md
@@ -12,6 +12,8 @@ python3 scripts/gsc_signal_delta.py \
 Returns day-normalized site totals, top gainers/decliners, and a `verdict_hint`
 (heuristic only — the final verdict is the skill's job, after L2/L3).
 
+**Surge-tuning note**: `verdict_hint` and `in_top_movers` are calibrated for upward "surge" claims (movers ranked by click gain). For a claimed *drop*, inspect `top_decliners` directly rather than relying on the hint.
+
 ## Getting the exports
 `mcp__dda__gsc_fetch_performance` (property pinned per workspace, e.g. JHR
 `sc-domain:josunhotel.com`) → save the query-dimension rows to a file → run the
diff --git a/custom-skills/35-seo-signal-validation/code/scripts/gsc_signal_delta.py b/custom-skills/35-seo-signal-validation/code/scripts/gsc_signal_delta.py
index 79c718e..fc34263 100644
--- a/custom-skills/35-seo-signal-validation/code/scripts/gsc_signal_delta.py
+++ b/custom-skills/35-seo-signal-validation/code/scripts/gsc_signal_delta.py
@@ -106,9 +106,10 @@ def compute_delta(recent, prior, recent_days, prior_days,
         gainer_terms = {g["query"] for g in gainers}
         rc, pc = r_by.get(claim_term, {}), p_by.get(claim_term, {})
         in_movers = claim_term in gainer_terms
+        found = bool(rc or pc)
         share = (rc.get("clicks", 0.0) / rt["clicks"] * 100) if rt["clicks"] else 0.0
         out["claim_term"] = {
-            "term": claim_term, "found": bool(rc or pc),
+            "term": claim_term, "found": found,
             "recent": {"clicks": rc.get("clicks", 0.0),
                        "impressions": rc.get("impressions", 0.0),
                        "position": rc.get("position")},
@@ -118,7 +119,12 @@ def compute_delta(recent, prior, recent_days, prior_days,
             "in_top_movers": in_movers,
             "click_share_pct": round(share, 2),
         }
-        if not in_movers and share < 1.0:
+        if not found:
+            out["verdict_hint"] = (
+                f"'{claim_term}' is absent from both GSC windows (no impressions / "
+                f"likely anonymized) -> INCONCLUSIVE, not refuted; confirm via live "
+                f"SERP + entity layer.")
+        elif not in_movers and share < 1.0:
             out["verdict_hint"] = (
                 f"'{claim_term}' contributes {share:.2f}% of recent clicks and is "
                 f"absent from top movers -> claimed impact likely ARTIFACT; real "
diff --git a/custom-skills/35-seo-signal-validation/code/scripts/test_gsc_signal_delta.py b/custom-skills/35-seo-signal-validation/code/scripts/test_gsc_signal_delta.py
index 79d6c9a..57a3f6a 100644
--- a/custom-skills/35-seo-signal-validation/code/scripts/test_gsc_signal_delta.py
+++ b/custom-skills/35-seo-signal-validation/code/scripts/test_gsc_signal_delta.py
@@ -40,6 +40,12 @@ def test_day_normalization():
     assert out["site_totals"]["prior"]["clicks_per_day"] == 6.93     # 208/30
 
 
+def test_absent_claim_term_inconclusive():
+    out = compute_delta(RECENT, PRIOR, 28, 30, claim_term="존재하지않는검색어")
+    assert out["claim_term"]["found"] is False
+    assert "INCONCLUSIVE" in out["verdict_hint"]
+
+
 def test_positive_days_required():
     try:
         compute_delta(RECENT, PRIOR, 0, 30)