diff --git a/docs/MATCHING_COOKBOOK.md b/docs/MATCHING_COOKBOOK.md
index 6427151..d64960f 100644
--- a/docs/MATCHING_COOKBOOK.md
+++ b/docs/MATCHING_COOKBOOK.md
@@ -2744,3 +2744,26 @@ two `move`s (one in the 2nd call's delay slot, one in the 3rd's) then `addu s0,s
 
 Same family as findings 156 and 157: **a chained accumulation is not the same source as three named
 results summed.**
+
+### 169. Worker A's family calibration CONFIRMED AT SCALE — 0.96–0.99 is idiom noise (coordinator)
+
+Worker A calibrated `sf3_family` by checking two 0.97-scoring entries and finding neither shared its
+sibling's body. **I have now confirmed that on eight candidates by raw-word diff**, which is the
+decisive test:
+
+| candidate | sibling | words | **differing words** |
+|---|---|---|---|
+| `0x8006EBA0` | `0x80028CE0` | 61 | **60** |
+| `0x800FFFEC` | `0x8007E8B8` | 19 | **18** |
+| `0x8005E17C` | `0x800FB54C` | 26 | **25** |
+
+**A high cosine with a size ratio of 1.00 is not evidence of a shared body** — at 0.96–0.99 the
+histogram is matching common **idioms**, exactly as worker A said. Contrast the genuine siblings:
+`0x800F3DC0` vs `0x800F3E18` differs in **1 of 22 words** (finding 166).
+
+> **The useful band is ratio 1.000 AND a near-zero raw-word diff.** Check the words, not the score —
+> it is one cheap computation and it is the difference between a copy-and-rename and a full
+> derivation.
+
+**Tool bug fixed:** `sf3_family` did not exclude already-claimed rows, so its top hit was a row
+matching **itself**. The registry is now the authority and claimed rows are skipped.
diff --git a/tools/sf3_family b/tools/sf3_family
index 683b47e..d1c0846 100755
--- a/tools/sf3_family
+++ b/tools/sf3_family
@@ -119,8 +119,15 @@ def main(argv: list[str]) -> int:
 
     payload = EXE.read_bytes()
 
+    claimed = read_regions(REGIONS)
+    claimed_ranges = [(s, e) for s, e, _ in claimed]
+    claimed_starts = {s for s, _, _ in claimed}
+
+    def is_claimed(addr: int) -> bool:
+        return addr in claimed_starts or any(s < addr < e for s, e in claimed_ranges)
+
     matched = []
-    for start, end, source in read_regions(REGIONS):
+    for start, end, source in claimed:
         words = body_words(payload, start, end)
         matched.append((start, end, source, histogram(words), end - start))
 
@@ -129,6 +136,8 @@ def main(argv: list[str]) -> int:
         size = end - start
         if size < min_size or size > max_size:
             continue
+        if is_claimed(start):
+            continue  # already merged -- reporting it is noise (it matched itself)
         mine = histogram(body_words(payload, start, end))
         best = None
         for m_start, m_end, m_source, m_hist, m_size in matched: