fix(trust): treat feedback_ratio=0.0 as missing data for buyer-only/returning sellers (#52)

eBay omits the 12-month positive percentage for returning sellers and
buyer-only accounts with no recent sales. Previously ratio=0.0 with
count>0 triggered established_bad_actor; now it returns None from the
scorer (score_is_partial=True) and emits a soft no_recent_seller_data
flag instead. ratio=0.0 with count=0 is still treated as no-history.

app/trust/aggregator.py

@@ -126,7 +126,12 @@ class Aggregator:
         # Hard filters
         if seller and seller.account_age_days is not None and seller.account_age_days < HARD_FILTER_AGE_DAYS:
             red_flags.append("new_account")
-        if seller and seller.feedback_ratio < HARD_FILTER_BAD_RATIO_THRESHOLD:
+        if seller and seller.feedback_ratio == 0.0 and seller.feedback_count > 0:
+            # 12-month ratio missing from page — returning seller or buyer-only account.
+            # Score will be partial (metadata._feedback_ratio returns None).  Soft flag
+            # only: do NOT fire established_bad_actor on what is likely missing data.
+            red_flags.append("no_recent_seller_data")
+        elif seller and seller.feedback_ratio < HARD_FILTER_BAD_RATIO_THRESHOLD:
             if HARD_FILTER_BAD_RATIO_MIN_COUNT < seller.feedback_count <= HARD_FILTER_BAD_RATIO_MAX_COUNT:
                 # Moderate-volume account with consistently bad ratio → hard flag.
                 red_flags.append("established_bad_actor")

app/trust/metadata.py

@@ -44,7 +44,13 @@ class MetadataScorer:
         if count < 200: return 15
         return 20
 
-    def _feedback_ratio(self, ratio: float, count: int) -> int:
+    def _feedback_ratio(self, ratio: float, count: int) -> Optional[int]:
+        # ratio=0.0 with count>0 means the 12-month percentage wasn't on the page —
+        # eBay omits the ratio for returning/buyer-only sellers with no recent sales.
+        # Treat as missing rather than "literally 0% positive" (which eBay doesn't allow
+        # on active accounts — those get suspended long before reaching 0%).
+        if ratio == 0.0 and count > 0:
+            return None
         if ratio < 0.80 and count > 20: return 0
         if ratio < 0.90: return 5
         if ratio < 0.95: return 10

tests/trust/test_aggregator.py

@@ -296,3 +296,37 @@ def test_non_retailer_does_not_suppress_duplicate_photo():
     )
     result = agg.aggregate(_ALL_20.copy(), photo_hash_duplicate=True, seller=seller)
     assert "duplicate_photo" in result.red_flags_json
+
+
+# ── #52: buyer-only / returning seller (ratio=0.0, count>0) ──────────────────
+
+def test_zero_ratio_with_count_gives_no_recent_seller_data_flag():
+    """Seller with 117 lifetime feedbacks (buyer-only) has ratio=0.0 parsed from page.
+    Must get no_recent_seller_data soft flag, NOT established_bad_actor."""
+    agg = Aggregator()
+    scores = {k: 10 for k in ["account_age", "feedback_count",
+                               "feedback_ratio", "price_vs_market", "category_history"]}
+    buyer_only = Seller(
+        platform="ebay", platform_seller_id="u", username="jjcpryz",
+        account_age_days=1200, feedback_count=117, feedback_ratio=0.0,
+        category_history_json="{}",
+    )
+    result = agg.aggregate(scores, photo_hash_duplicate=False, seller=buyer_only)
+    assert "no_recent_seller_data" in result.red_flags_json
+    assert "established_bad_actor" not in result.red_flags_json
+
+
+
+def test_established_bad_actor_still_fires_for_genuinely_bad_ratio():
+    """ratio=0.75 (not zero) with moderate count → established_bad_actor still fires."""
+    agg = Aggregator()
+    scores = {k: 10 for k in ["account_age", "feedback_count",
+                               "feedback_ratio", "price_vs_market", "category_history"]}
+    bad = Seller(
+        platform="ebay", platform_seller_id="u", username="u",
+        account_age_days=500, feedback_count=100, feedback_ratio=0.75,
+        category_history_json="{}",
+    )
+    result = agg.aggregate(scores, photo_hash_duplicate=False, seller=bad)
+    assert "established_bad_actor" in result.red_flags_json
+    assert "no_recent_seller_data" not in result.red_flags_json

tests/trust/test_metadata.py

@@ -43,3 +43,26 @@ def test_no_market_data_returns_none():
     scores = scorer.score(_seller(), market_median=None, listing_price=950.0)
     # None signals "data unavailable" — aggregator will set score_is_partial=True
     assert scores["price_vs_market"] is None
+
+
+def test_zero_ratio_with_nonzero_count_returns_none():
+    """ratio=0.0 with count>0 means eBay didn't show a 12-month percentage.
+    Must return None (missing data) not 0 (catastrophically bad)."""
+    scorer = MetadataScorer()
+    scores = scorer.score(
+        _seller(feedback_ratio=0.0, feedback_count=117),
+        market_median=None, listing_price=500.0,
+    )
+    assert scores["feedback_ratio"] is None
+
+
+def test_zero_ratio_with_zero_count_scores_low():
+    """feedback_ratio=0.0 with count=0 is a real 'no data at all' case, not missing."""
+    scorer = MetadataScorer()
+    scores = scorer.score(
+        _seller(feedback_ratio=0.0, feedback_count=0),
+        market_median=None, listing_price=500.0,
+    )
+    # count=0 means zero_feedback; ratio=0 with count=0 is the standard no-history path
+    # (not the "missing 12-month window" path)
+    assert scores["feedback_ratio"] == 5  # ratio < 0.90 → 5