| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 20 | | adverbTagCount | 2 | | adverbTags | | 0 | "he said fiercely [fiercely]" | | 1 | "she said softly [softly]" |
| | dialogueSentences | 45 | | tagDensity | 0.444 | | leniency | 0.889 | | rawRatio | 0.1 | | effectiveRatio | 0.089 | |
| 79.98% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1998 | | totalAiIsmAdverbs | 8 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | adverb | "reluctantly" | | count | 1 |
| | 6 | |
| | highlights | | 0 | "loosely" | | 1 | "softly" | | 2 | "perfectly" | | 3 | "completely" | | 4 | "really" | | 5 | "reluctantly" | | 6 | "suddenly" |
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| 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) | |
| 69.97% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1998 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "echoed" | | 1 | "flicked" | | 2 | "flickered" | | 3 | "eyebrow" | | 4 | "pulse" | | 5 | "fractured" | | 6 | "perfect" | | 7 | "silence" | | 8 | "chaotic" | | 9 | "sanctuary" | | 10 | "absolutely" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 124 | | matches | | |
| 96.77% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 124 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 149 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 53 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1982 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 22 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 34 | | wordCount | 1484 | | uniqueNames | 9 | | maxNameDensity | 0.81 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 12 | | Moreau | 2 | | Marseilles | 1 | | Lucien | 10 | | Eva | 3 | | Closer | 1 | | God | 1 | | Carter | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Aurora" | | 1 | "Moreau" | | 2 | "Lucien" | | 3 | "Eva" | | 4 | "God" | | 5 | "Carter" | | 6 | "Ptolemy" |
| | places | (empty) | | globalScore | 1 | | windowScore | 1 | |
| 71.88% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 96 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like a sculpture placed in the wro" | | 1 | "as though fighting the urge to reach for her" | | 2 | "tasted like coffee and smoke and the part" |
| |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1982 | | matches | (empty) | |
| 99.55% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 3 | | totalSentences | 149 | | matches | | 0 | "chose that moment" | | 1 | "say that much" | | 2 | "admit that the" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 57 | | mean | 34.77 | | std | 20.04 | | cv | 0.576 | | sampleLengths | | 0 | 61 | | 1 | 86 | | 2 | 7 | | 3 | 7 | | 4 | 18 | | 5 | 21 | | 6 | 65 | | 7 | 27 | | 8 | 29 | | 9 | 36 | | 10 | 15 | | 11 | 46 | | 12 | 78 | | 13 | 44 | | 14 | 37 | | 15 | 20 | | 16 | 15 | | 17 | 30 | | 18 | 61 | | 19 | 56 | | 20 | 57 | | 21 | 45 | | 22 | 24 | | 23 | 32 | | 24 | 39 | | 25 | 37 | | 26 | 31 | | 27 | 90 | | 28 | 42 | | 29 | 42 | | 30 | 41 | | 31 | 12 | | 32 | 31 | | 33 | 78 | | 34 | 8 | | 35 | 23 | | 36 | 32 | | 37 | 39 | | 38 | 8 | | 39 | 26 | | 40 | 50 | | 41 | 42 | | 42 | 25 | | 43 | 15 | | 44 | 20 | | 45 | 36 | | 46 | 23 | | 47 | 38 | | 48 | 37 | | 49 | 44 |
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| 96.77% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 124 | | matches | | 0 | "was slicked" | | 1 | "been sewn" | | 2 | "was buried" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 255 | | matches | | 0 | "was watching" | | 1 | "was running" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 17 | | semicolonCount | 2 | | flaggedSentences | 13 | | totalSentences | 149 | | ratio | 0.087 | | matches | | 0 | "Lucien Moreau looked exactly as she remembered him—impossibly composed, dangerously beautiful." | | 1 | "Those eyes—one amber as molten gold, the other black as pitch—fixed on her with the same unnerving focus that had once made her feel seen in ways no one else ever had." | | 2 | "The sound of it—of her nickname in his mouth—hit her like a bruise pressed too hard." | | 3 | "The flat smelled of old paper, turmeric, and the faint metallic tang that always clung to Lucien’s skin—like ozone after lightning." | | 4 | "His expression didn’t change, but something flickered behind his eyes—the black one, always harder to read." | | 5 | "He had moved without her hearing him—a half-demon talent she both hated and, God help her, missed." | | 6 | "The amber eye darkened; the black one seemed to drink in the lamplight." | | 7 | "The cane clattered against the leg of the couch as he let it fall, both hands coming up to frame her face—careful, reverent, as though she might vanish if he gripped too hard." | | 8 | "Her back met the wall of books; a few volumes tumbled to the floor with soft thuds." | | 9 | "She pulled back enough to study him—really study him." | | 10 | "She slipped from his arms—reluctantly—and went to the intercom, buzzing the delivery up." | | 11 | "Aurora rolled her eyes and started for the door, but Lucien caught her wrist—the one with the scar—and brought it to his lips." | | 12 | "She looked at him standing in the middle of her best friend’s ridiculous, book-strewn flat—half-demon, information broker, beautiful disaster—and felt the last of her resistance crumble like ash." |
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| 82.95% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 622 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 37 | | adverbRatio | 0.0594855305466238 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.017684887459807074 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 149 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 149 | | mean | 13.3 | | std | 9.01 | | cv | 0.677 | | sampleLengths | | 0 | 24 | | 1 | 17 | | 2 | 20 | | 3 | 11 | | 4 | 19 | | 5 | 24 | | 6 | 32 | | 7 | 7 | | 8 | 7 | | 9 | 11 | | 10 | 2 | | 11 | 5 | | 12 | 20 | | 13 | 1 | | 14 | 16 | | 15 | 7 | | 16 | 42 | | 17 | 19 | | 18 | 8 | | 19 | 22 | | 20 | 5 | | 21 | 2 | | 22 | 17 | | 23 | 15 | | 24 | 4 | | 25 | 7 | | 26 | 8 | | 27 | 7 | | 28 | 27 | | 29 | 12 | | 30 | 21 | | 31 | 40 | | 32 | 17 | | 33 | 10 | | 34 | 11 | | 35 | 13 | | 36 | 10 | | 37 | 12 | | 38 | 14 | | 39 | 11 | | 40 | 15 | | 41 | 5 | | 42 | 5 | | 43 | 10 | | 44 | 16 | | 45 | 14 | | 46 | 12 | | 47 | 9 | | 48 | 5 | | 49 | 10 |
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| 45.19% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 11 | | diversityRatio | 0.31543624161073824 | | totalSentences | 149 | | uniqueOpeners | 47 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 112 | | matches | | 0 | "Instead, the man standing on" | | 1 | "Then Aurora tried to slam" | | 2 | "Just enough to stop her." | | 3 | "Instead she stepped back, letting" | | 4 | "Everywhere she moved, he was" | | 5 | "Then she made a small," |
| | ratio | 0.054 | |
| 48.57% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 48 | | totalSentences | 112 | | matches | | 0 | "She had only meant to" | | 1 | "His charcoal suit hugged his" | | 2 | "he said, voice low and" | | 3 | "She hadn’t heard it in" | | 4 | "She glared up at him," | | 5 | "His mismatched gaze flicked down" | | 6 | "His jaw tightened almost imperceptibly." | | 7 | "She should have told him" | | 8 | "He was too tall for" | | 9 | "He looked like a sculpture" | | 10 | "Her heart still beat too" | | 11 | "He rested both hands on" | | 12 | "She laughed, sharp and humorless." | | 13 | "His expression didn’t change, but" | | 14 | "She busied herself gathering an" | | 15 | "she said without looking at" | | 16 | "Her voice faltered" | | 17 | "His voice was quieter now" | | 18 | "He had moved without her" | | 19 | "She whipped around." |
| | ratio | 0.429 | |
| 35.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 112 | | matches | | 0 | "The three deadbolts gave way" | | 1 | "She had only meant to" | | 2 | "Lucien Moreau looked exactly as" | | 3 | "The platinum blond of his" | | 4 | "His charcoal suit hugged his" | | 5 | "Those eyes—one amber as molten" | | 6 | "The cane flashed out, catching" | | 7 | "he said, voice low and" | | 8 | "The sound of it—of her" | | 9 | "She hadn’t heard it in" | | 10 | "She glared up at him," | | 11 | "His mismatched gaze flicked down" | | 12 | "His jaw tightened almost imperceptibly." | | 13 | "Ptolemy chose that moment to" | | 14 | "The tabby’s back arched, orange" | | 15 | "Aurora understood the feeling." | | 16 | "Lucien’s mouth curved in a" | | 17 | "She should have told him" | | 18 | "The flat smelled of old" | | 19 | "Every surface of Eva’s one-bedroom" |
| | ratio | 0.848 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 112 | | matches | (empty) | | ratio | 0 | |
| 88.74% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 66 | | technicalSentenceCount | 5 | | matches | | 0 | "The three deadbolts gave way one after another, heavy metallic clunks that echoed in the narrow hallway like punctuation marks to Aurora’s growing irritation." | | 1 | "Those eyes—one amber as molten gold, the other black as pitch—fixed on her with the same unnerving focus that had once made her feel seen in ways no one else ev…" | | 2 | "He stood less than three feet away, close enough that she could see the faint scar through his left eyebrow, close enough to smell the faint notes of vetiver an…" | | 3 | "The cane clattered against the leg of the couch as he let it fall, both hands coming up to frame her face—careful, reverent, as though she might vanish if he gr…" | | 4 | "The faint lines of exhaustion at the corners of his eyes that hadn’t been there seven months ago." |
| |
| 50.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 20 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, the confession dragged from somewhere deep" | | 1 | "he murmured, lips brushing her temple" | | 2 | "he repeated, voice rough with promise" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 16 | | fancyCount | 7 | | fancyTags | | 0 | "Her voice faltered (falter)" | | 1 | "she whispered (whisper)" | | 2 | "he breathed (breathe)" | | 3 | "she admitted (admit)" | | 4 | "he murmured (murmur)" | | 5 | "she warned (warn)" | | 6 | "he repeated (repeat)" |
| | dialogueSentences | 45 | | tagDensity | 0.356 | | leniency | 0.711 | | rawRatio | 0.438 | | effectiveRatio | 0.311 | |