fix: address CodeRabbit review comments

src/core/services/tokenizer.test.ts

@@ -3086,6 +3086,27 @@ test('tokenizeSubtitle uses Yomitan word classes to classify standalone particle
   assert.equal(result.tokens?.[0]?.jlptLevel, undefined);
 });
 
+test('tokenizeSubtitle uses Yomitan word classes to classify auxiliary subclasses', async () => {
+  const result = await tokenizeSubtitle(
+    'です',
+    makeDepsFromYomitanTokens(
+      [{ surface: 'です', reading: 'です', headword: 'です', wordClasses: ['aux-v'] }],
+      {
+        getFrequencyDictionaryEnabled: () => true,
+        getFrequencyRank: () => 10,
+        getJlptLevel: () => 'N5',
+        tokenizeWithMecab: async () => null,
+      },
+    ),
+  );
+
+  assert.equal(result.tokens?.length, 1);
+  assert.equal(result.tokens?.[0]?.partOfSpeech, PartOfSpeech.bound_auxiliary);
+  assert.equal(result.tokens?.[0]?.pos1, '助動詞');
+  assert.equal(result.tokens?.[0]?.frequencyRank, undefined);
+  assert.equal(result.tokens?.[0]?.jlptLevel, undefined);
+});
+
 test('tokenizeSubtitle fills detailed MeCab POS when Yomitan word class supplies coarse POS', async () => {
   const result = await tokenizeSubtitle(
     'は',

src/core/services/tokenizer.ts

@@ -359,7 +359,7 @@ function resolvePartOfSpeechFromYomitanWordClasses(wordClasses: string[]): {
   if (wordClasses.includes('prt')) {
     return { partOfSpeech: PartOfSpeech.particle, pos1: '助詞' };
   }
-  if (wordClasses.includes('aux')) {
+  if (wordClasses.some((wordClass) => wordClass === 'aux' || wordClass.startsWith('aux-'))) {
     return { partOfSpeech: PartOfSpeech.bound_auxiliary, pos1: '助動詞' };
   }
   if (wordClasses.some((wordClass) => wordClass.startsWith('v'))) {

src/core/services/tokenizer/annotation-stage.test.ts

@@ -713,6 +713,57 @@ test('annotateTokens N+1 sentence word count respects source punctuation gaps om
   assert.equal(result[3]?.isNPlusOneTarget, false);
 });
 
+test('annotateTokens N+1 sentence word count normalizes line breaks before gap detection', () => {
+  const tokens = [
+    makeToken({
+      surface: '私',
+      headword: '私',
+      pos1: '名詞',
+      startPos: 0,
+      endPos: 1,
+    }),
+    makeToken({
+      surface: '猫',
+      headword: '猫',
+      pos1: '名詞',
+      startPos: 2,
+      endPos: 3,
+    }),
+    makeToken({
+      surface: '犬',
+      headword: '犬',
+      pos1: '名詞',
+      startPos: 3,
+      endPos: 4,
+    }),
+    makeToken({
+      surface: 'ふざけん',
+      headword: 'ふざける',
+      partOfSpeech: PartOfSpeech.verb,
+      pos1: '動詞',
+      pos2: '自立',
+      startPos: 5,
+      endPos: 9,
+    }),
+  ];
+
+  const result = annotateTokens(
+    tokens,
+    makeDeps({
+      isKnownWord: (text) => text === '私' || text === '猫' || text === '犬',
+    }),
+    {
+      minSentenceWordsForNPlusOne: 3,
+      sourceText: '私\r\n猫犬！ふざけんなよ！',
+    },
+  );
+
+  assert.equal(result[0]?.isNPlusOneTarget, false);
+  assert.equal(result[1]?.isNPlusOneTarget, false);
+  assert.equal(result[2]?.isNPlusOneTarget, false);
+  assert.equal(result[3]?.isNPlusOneTarget, false);
+});
+
 test('annotateTokens applies configured pos1 exclusions to both frequency and N+1', () => {
   const tokens = [
     makeToken({