| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 1 | | adverbTags | | 0 | "His fingers flexed around [around]" |
| | dialogueSentences | 65 | | tagDensity | 0.215 | | leniency | 0.431 | | rawRatio | 0.071 | | effectiveRatio | 0.031 | |
| 87.55% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1606 | | totalAiIsmAdverbs | 4 | | found | | | highlights | | 0 | "carefully" | | 1 | "suddenly" | | 2 | "slightly" |
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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) | |
| 28.39% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1606 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | word | "down her spine" | | count | 1 |
| | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | |
| | highlights | | 0 | "silence" | | 1 | "familiar" | | 2 | "pulse" | | 3 | "gleaming" | | 4 | "flickered" | | 5 | "down her spine" | | 6 | "stomach" | | 7 | "velvet" | | 8 | "eyebrow" | | 9 | "charged" | | 10 | "trembled" | | 11 | "searing" | | 12 | "implication" | | 13 | "dance" | | 14 | "shattered" | | 15 | "unreadable" | | 16 | "weight" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "stomach dropped/sank" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 129 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 129 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 176 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 44 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 11 | | markdownWords | 14 | | totalWords | 1589 | | ratio | 0.009 | | matches | | 0 | "Her" | | 1 | "pissed off" | | 2 | "Damn it." | | 3 | "always" | | 4 | "Danger" | | 5 | "chérie" | | 6 | "gift" | | 7 | "protect" | | 8 | "he" | | 9 | "Get out." | | 10 | "will" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 15 | | unquotedAttributions | 1 | | matches | | 0 | "But her traitorous hands fisted in his lapels, pulling him closer, and when his teeth nipped her lower lip, she gasped a…" |
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| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 29 | | wordCount | 1247 | | uniqueNames | 13 | | maxNameDensity | 0.72 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 9 | | Moreau | 2 | | Eva | 3 | | Brighton | 1 | | Ptolemy | 2 | | Golden | 1 | | Empress | 1 | | Yu-Fei | 1 | | Marseille | 1 | | Close | 1 | | Malphor | 2 | | Evan | 1 | | Aurora | 4 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Ptolemy" | | 4 | "Yu-Fei" | | 5 | "Evan" | | 6 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 80 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1589 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 176 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 78 | | mean | 20.37 | | std | 16.27 | | cv | 0.799 | | sampleLengths | | 0 | 10 | | 1 | 44 | | 2 | 8 | | 3 | 58 | | 4 | 26 | | 5 | 25 | | 6 | 23 | | 7 | 14 | | 8 | 39 | | 9 | 39 | | 10 | 38 | | 11 | 3 | | 12 | 21 | | 13 | 7 | | 14 | 24 | | 15 | 20 | | 16 | 22 | | 17 | 11 | | 18 | 16 | | 19 | 9 | | 20 | 13 | | 21 | 21 | | 22 | 2 | | 23 | 22 | | 24 | 63 | | 25 | 5 | | 26 | 17 | | 27 | 4 | | 28 | 18 | | 29 | 11 | | 30 | 16 | | 31 | 18 | | 32 | 52 | | 33 | 4 | | 34 | 25 | | 35 | 6 | | 36 | 31 | | 37 | 23 | | 38 | 9 | | 39 | 31 | | 40 | 24 | | 41 | 45 | | 42 | 9 | | 43 | 9 | | 44 | 61 | | 45 | 4 | | 46 | 12 | | 47 | 12 | | 48 | 9 | | 49 | 28 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 129 | | matches | | |
| 30.51% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 236 | | matches | | 0 | "was reining" | | 1 | "was warning" | | 2 | "wasn’t going" | | 3 | "was trying" | | 4 | "was memorising" | | 5 | "were coming" |
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| 29.22% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 176 | | ratio | 0.04 | | matches | | 0 | "The door swung inward before she could second-guess herself, revealing Lucien Moreau in all his infuriating glory—charcoal suit immaculate, platinum hair slicked back like he’d just stepped out of a board meeting instead of whatever shadowy underworld dealings he’d been tangled in." | | 1 | "He chose his battles carefully—always had—and this wasn’t one of them." | | 2 | "The cane—ivory handle gleaming—tapped once against the hardwood." | | 3 | "The symbols burned into the surface were familiar—too familiar." | | 4 | "“They know you’re looking.” His fingers brushed her wrist—accidental or deliberate, she couldn’t tell." | | 5 | "The scar on her wrist—twin to the one on her soul—ached in memory." | | 6 | "The thing that had driven Evan to—" |
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| 96.90% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1263 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 55 | | adverbRatio | 0.043547110055423596 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.007125890736342043 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 176 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 176 | | mean | 9.03 | | std | 7.41 | | cv | 0.821 | | sampleLengths | | 0 | 10 | | 1 | 25 | | 2 | 7 | | 3 | 12 | | 4 | 8 | | 5 | 42 | | 6 | 16 | | 7 | 19 | | 8 | 7 | | 9 | 3 | | 10 | 2 | | 11 | 13 | | 12 | 7 | | 13 | 7 | | 14 | 16 | | 15 | 3 | | 16 | 9 | | 17 | 2 | | 18 | 11 | | 19 | 11 | | 20 | 10 | | 21 | 7 | | 22 | 2 | | 23 | 16 | | 24 | 21 | | 25 | 28 | | 26 | 10 | | 27 | 3 | | 28 | 13 | | 29 | 8 | | 30 | 3 | | 31 | 4 | | 32 | 9 | | 33 | 8 | | 34 | 7 | | 35 | 18 | | 36 | 2 | | 37 | 4 | | 38 | 2 | | 39 | 13 | | 40 | 3 | | 41 | 1 | | 42 | 10 | | 43 | 10 | | 44 | 6 | | 45 | 3 | | 46 | 6 | | 47 | 4 | | 48 | 9 | | 49 | 18 |
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| 53.03% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3522727272727273 | | totalSentences | 176 | | uniqueOpeners | 62 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 110 | | matches | | 0 | "Just gripped the doorframe like" | | 1 | "Then Lucien exhaled, sharp and" | | 2 | "Then his lips crashed into" | | 3 | "Then his fingers brushed the" |
| | ratio | 0.036 | |
| 56.36% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 110 | | matches | | 0 | "She should’ve known better than" | | 1 | "His heterochromatic gaze locked onto" | | 2 | "His voice was smooth, rich," | | 3 | "She didn’t move." | | 4 | "Her fingers twitched." | | 5 | "He chose his battles carefully—always" | | 6 | "*Her* flat now, technically, since" | | 7 | "he observed, eyes flicking over" | | 8 | "Her molars ground." | | 9 | "He turned then, full and" | | 10 | "His expression didn’t change." | | 11 | "She barked a laugh." | | 12 | "He reached into his jacket." | | 13 | "She tensed, but all he" | | 14 | "She took it, unfolding the" | | 15 | "His jaw tightened" | | 16 | "Her stomach dropped." | | 17 | "Her breath stuttered, the parchment" | | 18 | "He stepped closer, close enough" | | 19 | "His voice dropped, low and" |
| | ratio | 0.409 | |
| 73.64% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 85 | | totalSentences | 110 | | matches | | 0 | "The third deadbolt clicked like" | | 1 | "Aurora froze, fingers still wrapped" | | 2 | "She should’ve known better than" | | 3 | "The door swung inward before" | | 4 | "His heterochromatic gaze locked onto" | | 5 | "His voice was smooth, rich," | | 6 | "She didn’t move." | | 7 | "A slow, knowing smile curled" | | 8 | "Her fingers twitched." | | 9 | "Lucien stepped forward, forcing her" | | 10 | "He chose his battles carefully—always" | | 11 | "The door clicked shut behind" | | 12 | "The flat suddenly felt half" | | 13 | "*Her* flat now, technically, since" | | 14 | "The thought was a lifeline," | | 15 | "he observed, eyes flicking over" | | 16 | "Ptolemy’s tail lashed like a" | | 17 | "Lucien ignored her, trailing a" | | 18 | "Her molars ground." | | 19 | "He turned then, full and" |
| | ratio | 0.773 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 110 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 6 | | matches | | 0 | "The same ones she’d spent the last three nights deciphering in Eva’s notes, the same ones that had turned up on the corpse in the alley behind the Golden Empres…" | | 1 | "The same ones that had made Yu-Fei’s face go sheet-white when she’d shown him the photo." | | 2 | "His cane clattered to the floor as his hands slid into her hair, angling her head just so, deepening the kiss like he was memorising the shape of her." | | 3 | "His hands slid down, gripping her hips, lifting her onto the edge of the desk." | | 4 | "His mouth trailed down her throat, teeth scraping over her pulse point, and she arched into him with a sound that was half moan, half growl." | | 5 | "His breath was ragged, his lips swollen, his eyes dark with something that looked suspiciously like regret." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "he observed (observe)" | | 1 | "he agreed (agree)" |
| | dialogueSentences | 65 | | tagDensity | 0.062 | | leniency | 0.123 | | rawRatio | 0.5 | | effectiveRatio | 0.062 | |