| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 1 | | adverbTags | | 0 | "Aurora said coolly [coolly]" |
| | dialogueSentences | 22 | | tagDensity | 0.136 | | leniency | 0.273 | | rawRatio | 0.333 | | effectiveRatio | 0.091 | |
| 93.54% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 774 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 48.32% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 774 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "stomach" | | 1 | "familiar" | | 2 | "trembled" | | 3 | "loomed" | | 4 | "firmly" | | 5 | "charm" | | 6 | "unspoken" | | 7 | "eyebrow" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 59 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 59 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 78 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 777 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 18.22% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 645 | | uniqueNames | 6 | | maxNameDensity | 2.64 | | worstName | "Aurora" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 8 | | Aurora | 17 | | Perry | 1 | | Brick | 1 | | Lane | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Lucien" | | 1 | "Aurora" | | 2 | "Perry" | | 3 | "Ptolemy" |
| | places | | | globalScore | 0.182 | | windowScore | 0.5 | |
| 45.83% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite meeting as she flung the heavy oak panel wide" | | 1 | "as though committing them to memory" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 777 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 78 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 44 | | mean | 17.66 | | std | 14.04 | | cv | 0.795 | | sampleLengths | | 0 | 3 | | 1 | 23 | | 2 | 28 | | 3 | 4 | | 4 | 19 | | 5 | 5 | | 6 | 17 | | 7 | 9 | | 8 | 16 | | 9 | 46 | | 10 | 1 | | 11 | 17 | | 12 | 8 | | 13 | 46 | | 14 | 8 | | 15 | 63 | | 16 | 6 | | 17 | 34 | | 18 | 8 | | 19 | 19 | | 20 | 11 | | 21 | 21 | | 22 | 19 | | 23 | 35 | | 24 | 32 | | 25 | 3 | | 26 | 25 | | 27 | 7 | | 28 | 15 | | 29 | 5 | | 30 | 6 | | 31 | 10 | | 32 | 33 | | 33 | 6 | | 34 | 10 | | 35 | 5 | | 36 | 36 | | 37 | 20 | | 38 | 4 | | 39 | 14 | | 40 | 37 | | 41 | 5 | | 42 | 31 | | 43 | 7 |
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| 99.32% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 59 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 105 | | matches | | |
| 32.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 78 | | ratio | 0.038 | | matches | | 0 | "The voice belonged to Lucien, her estranged ex-lover -- and the most dangerous man she knew." | | 1 | "A low, dark chuckle came from Lucien, and Aurora could imagine the slow lift of his lips -- lips that could charm jewels from the 뇌 or crush all that got in his way." | | 2 | "The words, the accent, the raw lust in his gaze -- it set off reflected fires." |
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| 95.72% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 646 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.04489164086687306 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.01393188854489164 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 78 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 78 | | mean | 9.96 | | std | 6.2 | | cv | 0.623 | | sampleLengths | | 0 | 3 | | 1 | 9 | | 2 | 14 | | 3 | 6 | | 4 | 8 | | 5 | 14 | | 6 | 4 | | 7 | 6 | | 8 | 13 | | 9 | 5 | | 10 | 12 | | 11 | 5 | | 12 | 9 | | 13 | 16 | | 14 | 21 | | 15 | 15 | | 16 | 10 | | 17 | 1 | | 18 | 5 | | 19 | 12 | | 20 | 8 | | 21 | 15 | | 22 | 13 | | 23 | 26 | | 24 | 8 | | 25 | 31 | | 26 | 24 | | 27 | 6 | | 28 | 34 | | 29 | 8 | | 30 | 8 | | 31 | 5 | | 32 | 6 | | 33 | 11 | | 34 | 6 | | 35 | 7 | | 36 | 8 | | 37 | 19 | | 38 | 12 | | 39 | 12 | | 40 | 11 | | 41 | 13 | | 42 | 5 | | 43 | 14 | | 44 | 3 | | 45 | 7 | | 46 | 18 | | 47 | 7 | | 48 | 5 | | 49 | 10 |
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| 64.10% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 5 | | diversityRatio | 0.4230769230769231 | | totalSentences | 78 | | uniqueOpeners | 33 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 57 | | matches | | 0 | "Of course, he'd use his" | | 1 | "Instead of answering, Lucien began" |
| | ratio | 0.035 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 57 | | matches | | 0 | "Her heart dropped to the" | | 1 | "Her fingers trembled, unwilling to" | | 2 | "She had burrowed into her" | | 3 | "She had almost convinced herself" | | 4 | "She was the picture of" | | 5 | "He was right, of course." | | 6 | "He never did ask for" | | 7 | "She reached for the door" | | 8 | "His eyes were fixed on" | | 9 | "His gaze raked over her" | | 10 | "He drank her in, taking" | | 11 | "He reached out, fingers brushing" | | 12 | "His touch lingered longer than" | | 13 | "He lifted an arm, and" | | 14 | "He had simply stepped out" | | 15 | "He unbuttoned his tailored charcoal" | | 16 | "He had always had a" |
| | ratio | 0.298 | |
| 47.72% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 47 | | totalSentences | 57 | | matches | | 0 | "Aurora's voice rapped out from" | | 1 | "Ptolemy, the settling cat, mewed" | | 2 | "The reply came muffled and" | | 3 | "Aurora strained to make out" | | 4 | "Her heart dropped to the" | | 5 | "Aurora's hand hovered over the" | | 6 | "Her fingers trembled, unwilling to" | | 7 | "A shadow loomed on the" | | 8 | "The voice belonged to Lucien," | | 9 | "She had burrowed into her" | | 10 | "She had almost convinced herself" | | 11 | "Ptolemy wound between her calves." | | 12 | "The first one disengaged with" | | 13 | "The door swung inward a" | | 14 | "Aurora turned, keeping the door" | | 15 | "She was the picture of" | | 16 | "A low, dark chuckle came" | | 17 | "Aurora's back teeth sank into" | | 18 | "He was right, of course." | | 19 | "He never did ask for" |
| | ratio | 0.825 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 57 | | matches | (empty) | | ratio | 0 | |
| 93.60% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 29 | | technicalSentenceCount | 2 | | matches | | 0 | "She was the picture of causality, from the heavy black leather boots to the crushed mourning purple of her sweater to the gold tackle box that put the torque in…" | | 1 | "But beneath the outward calm, ice had settled in her sternum, a lump of panic that had her struggling to take slow, deep breaths." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.091 | | leniency | 0.182 | | rawRatio | 0 | | effectiveRatio | 0 | |