| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 144 | | tagDensity | 0.118 | | leniency | 0.236 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.14% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2185 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "really" | | 1 | "very" | | 2 | "slowly" |
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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) | |
| 79.41% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2185 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "silence" | | 1 | "footsteps" | | 2 | "flicked" | | 3 | "flicker" | | 4 | "comfortable" | | 5 | "tenderness" | | 6 | "desire" | | 7 | "familiar" | | 8 | "warmth" |
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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 | 152 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 152 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 279 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 54 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2182 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 41 | | unquotedAttributions | 1 | | matches | | 0 | "From behind the book tower, Ptolemy hissed." |
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| 83.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 47 | | wordCount | 1423 | | uniqueNames | 13 | | maxNameDensity | 1.26 | | worstName | "Lucien" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | Ptolemy | 4 | | Lucien | 18 | | Brick | 1 | | Lane | 1 | | Frenchman | 1 | | Cardiff | 1 | | Evan | 1 | | Avaros | 1 | | London | 2 | | Don | 1 | | French | 1 | | Aurora | 14 |
| | persons | | 0 | "Moreau" | | 1 | "Ptolemy" | | 2 | "Lucien" | | 3 | "Frenchman" | | 4 | "Evan" | | 5 | "Aurora" |
| | places | | 0 | "Brick" | | 1 | "Lane" | | 2 | "Cardiff" | | 3 | "London" |
| | globalScore | 0.868 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 91 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like a hand rather than a knife" |
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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 | 2182 | | matches | (empty) | |
| 94.98% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 6 | | totalSentences | 279 | | matches | | 0 | "hated that part" | | 1 | "learned that the" | | 2 | "hated that she" | | 3 | "Hated that she" | | 4 | "remembered that night" | | 5 | "enough that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 196 | | mean | 11.13 | | std | 13.21 | | cv | 1.186 | | sampleLengths | | 0 | 10 | | 1 | 44 | | 2 | 5 | | 3 | 3 | | 4 | 4 | | 5 | 13 | | 6 | 11 | | 7 | 20 | | 8 | 9 | | 9 | 1 | | 10 | 3 | | 11 | 1 | | 12 | 11 | | 13 | 3 | | 14 | 6 | | 15 | 2 | | 16 | 27 | | 17 | 16 | | 18 | 9 | | 19 | 2 | | 20 | 6 | | 21 | 1 | | 22 | 35 | | 23 | 9 | | 24 | 3 | | 25 | 3 | | 26 | 10 | | 27 | 8 | | 28 | 10 | | 29 | 50 | | 30 | 11 | | 31 | 7 | | 32 | 4 | | 33 | 1 | | 34 | 5 | | 35 | 5 | | 36 | 10 | | 37 | 6 | | 38 | 64 | | 39 | 9 | | 40 | 4 | | 41 | 2 | | 42 | 33 | | 43 | 5 | | 44 | 4 | | 45 | 6 | | 46 | 7 | | 47 | 47 | | 48 | 11 | | 49 | 4 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 152 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 261 | | matches | | 0 | "was admitting" | | 1 | "was holding" |
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| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 1 | | flaggedSentences | 4 | | totalSentences | 279 | | ratio | 0.014 | | matches | | 0 | "He smelled faintly of rain, cedar, and something warmer beneath it—spice, perhaps, or the ghost of smoke." | | 1 | "There it was—the hurt beneath the polish, buried so deep it had grown sharp edges." | | 2 | "Lucien had always moved like that—quietly, until he was near enough to alter the air." | | 3 | "His amber eye burned; the black one gave nothing away." |
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| 89.20% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1429 | | adjectiveStacks | 1 | | stackExamples | | 0 | "tiny rain-darkened strand" |
| | adverbCount | 65 | | adverbRatio | 0.04548635409377187 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.006298110566829951 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 279 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 279 | | mean | 7.82 | | std | 7.15 | | cv | 0.914 | | sampleLengths | | 0 | 10 | | 1 | 22 | | 2 | 8 | | 3 | 14 | | 4 | 5 | | 5 | 3 | | 6 | 4 | | 7 | 13 | | 8 | 3 | | 9 | 8 | | 10 | 7 | | 11 | 13 | | 12 | 8 | | 13 | 1 | | 14 | 1 | | 15 | 3 | | 16 | 1 | | 17 | 11 | | 18 | 3 | | 19 | 6 | | 20 | 2 | | 21 | 5 | | 22 | 10 | | 23 | 2 | | 24 | 2 | | 25 | 8 | | 26 | 16 | | 27 | 6 | | 28 | 3 | | 29 | 2 | | 30 | 6 | | 31 | 1 | | 32 | 12 | | 33 | 6 | | 34 | 17 | | 35 | 5 | | 36 | 4 | | 37 | 3 | | 38 | 3 | | 39 | 10 | | 40 | 8 | | 41 | 10 | | 42 | 10 | | 43 | 16 | | 44 | 24 | | 45 | 11 | | 46 | 7 | | 47 | 4 | | 48 | 1 | | 49 | 5 |
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| 44.27% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.24014336917562723 | | totalSentences | 279 | | uniqueOpeners | 67 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 9 | | totalSentences | 133 | | matches | | 0 | "Then one amber eye caught" | | 1 | "Just her name written in" | | 2 | "Bright blue eyes, she knew." | | 3 | "Then she had hated him" | | 4 | "Just don’t go tonight." | | 5 | "Then he had left." | | 6 | "Instead, she let him take" | | 7 | "Instead, she stepped closer and" | | 8 | "Then Lucien made a broken" |
| | ratio | 0.068 | |
| 51.58% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 56 | | totalSentences | 133 | | matches | | 0 | "She stared at him." | | 1 | "Her gaze dropped despite herself." | | 2 | "She had seen it three" | | 3 | "He never rushed to fill" | | 4 | "He let it sit there," | | 5 | "She hated that part of" | | 6 | "She hated more that he" | | 7 | "Her fingers slipped the chain" | | 8 | "He smelled faintly of rain," | | 9 | "He wore a tailored charcoal" | | 10 | "His gaze flicked to her" | | 11 | "She had seen his attention" | | 12 | "She folded her arms." | | 13 | "He had built a career" | | 14 | "His black eye held hers." | | 15 | "She laughed once, without humor." | | 16 | "She had never seen Avaros." | | 17 | "She had seen what touched" | | 18 | "She had learned that the" | | 19 | "It existed beneath London’s ordinary" |
| | ratio | 0.421 | |
| 50.23% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 109 | | totalSentences | 133 | | matches | | 0 | "The door opened three inches" | | 1 | "Aurora saw the platinum hair" | | 2 | "The other, black as spilled" | | 3 | "Lucien Moreau inclined his head." | | 4 | "She stared at him." | | 5 | "Lucien’s mouth tilted." | | 6 | "Aurora’s hand tightened around the" | | 7 | "The little crescent scar on" | | 8 | "Her gaze dropped despite herself." | | 9 | "A thin black envelope lay" | | 10 | "She had seen it three" | | 11 | "The answer landed with the" | | 12 | "He never rushed to fill" | | 13 | "He let it sit there," | | 14 | "Aurora kept the chain fastened." | | 15 | "The building carried every sound:" | | 16 | "Aurora imagined Lucien’s voice traveling" | | 17 | "She hated that part of" | | 18 | "She hated more that he" | | 19 | "The words were quiet." |
| | ratio | 0.82 | |
| 37.59% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 133 | | matches | | | ratio | 0.008 | |
| 64.94% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 55 | | technicalSentenceCount | 6 | | matches | | 0 | "He wore a tailored charcoal suit that looked untouched by the damp night, his ivory-handled cane tucked beneath one arm." | | 1 | "Ptolemy watched from the arm of the sofa, his striped tail lashing as if Lucien’s arrival had personally insulted the cat’s bloodline." | | 2 | "She had seen what touched it: impossible shadows, creatures that wore human shapes badly, Lucien’s blood on a white shirt and the terrible calm with which he ha…" | | 3 | "His thumb brushed the inside of her wrist, beside the crescent scar, and every memory she had locked away came awake at once: his mouth against her throat, his …" | | 4 | "For all his control, he was holding her hand as though it might disappear." | | 5 | "He kissed her as though he had been waiting in some locked room inside himself, and she hated him for making her want to open the door." |
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| 95.59% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 1 | | matches | | 0 | "he said, his breath warm against her mouth," |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 14 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 144 | | tagDensity | 0.097 | | leniency | 0.194 | | rawRatio | 0.143 | | effectiveRatio | 0.028 | |