lint: wrap long lines (E501), fix F841/F821/E731 — make check fully green

All 32 findings resolved: regex literals kept single-line with noqa
(pattern IS the reviewed artifact), HTML rows string-concatenated for
line length, walrus tuple in BIP-340 verify split into named generator,
unused pytest import dropped. No behavior changes; 44/44 tests pass.
Full-gate discipline restored: ruff exit 0.

cayceops/components/maild/classify.py

@@ -15,9 +15,22 @@ from cayceops.models import MailClassification
 
 _RULES: list[tuple[MailClassification, re.Pattern[str], float]] = [
     # (class, pattern, confidence when matched)
-    (MailClassification.REJECTION, re.compile(r"\b(declin|reject|not able to|unable to|unfortunately|we regret|won.t be able)\w*", re.I), 0.9),
-    (MailClassification.APPROVAL, re.compile(r"\b(approv|accept|welcome to the|you.re (in|approved)|live|activated|glad to)\w*", re.I), 0.85),
-    (MailClassification.QUESTION, re.compile(r"\b(could you|can you|please (provide|clarify|confirm)|what (is|are)|how (do|does|can)|need more (info|details))\b", re.I), 0.7),
+    (
+        MailClassification.REJECTION,
+        # noqa: E501 (kept on one line: the pattern IS the reviewed artifact)
+        re.compile(r"\b(declin|reject|not able to|unable to|unfortunately|we regret|won.t be able)\w*", re.I),  # noqa: E501
+        0.9,
+    ),
+    (
+        MailClassification.APPROVAL,
+        re.compile(r"\b(approv|accept|welcome to the|you.re (in|approved)|live|activated|glad to)\w*", re.I),  # noqa: E501
+        0.85,
+    ),
+    (
+        MailClassification.QUESTION,
+        re.compile(r"\b(could you|can you|please (provide|clarify|confirm)|what (is|are)|how (do|does|can)|need more (info|details))\b", re.I),  # noqa: E501
+        0.7,
+    ),
 ]
 
 _LLM_PROMPT = """Classify this merchant email into exactly one of:
@@ -41,7 +54,10 @@ def _llm_classify(text: str, cfg: Config) -> tuple[MailClassification, float] |
 
     try:
         provider = get_provider(cfg)
-        raw = provider.complete(_LLM_PROMPT.format(body=text[:4000]), system="You classify merchant emails. Reply with JSON only.")
+        raw = provider.complete(
+            _LLM_PROMPT.format(body=text[:4000]),
+            system="You classify merchant emails. Reply with JSON only.",
+        )
         data = json.loads(re.search(r"\{.*\}", raw, re.S).group(0))
         kind = MailClassification(data["classification"].lower())
         confidence = float(data["confidence"])