| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 2 | | adverbTags | | 0 | "She spun around [around]" | | 1 | "His grip tightened just [just]" |
| | dialogueSentences | 51 | | tagDensity | 0.255 | | leniency | 0.51 | | rawRatio | 0.154 | | effectiveRatio | 0.078 | |
| 77.50% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1111 | | totalAiIsmAdverbs | 5 | | found | | | highlights | | 0 | "tightly" | | 1 | "lightly" | | 2 | "carefully" | | 3 | "slightly" | | 4 | "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) | |
| 50.50% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1111 | | totalAiIsms | 11 | | found | | | highlights | | 0 | "pulsed" | | 1 | "lilt" | | 2 | "silence" | | 3 | "flicked" | | 4 | "charged" | | 5 | "whisper" | | 6 | "pulse" | | 7 | "trembled" | | 8 | "unreadable" | | 9 | "shattered" |
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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 | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 80 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 114 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 33 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 3 | | markdownWords | 6 | | totalWords | 1100 | | ratio | 0.005 | | matches | | 0 | "I can’t do this" | | 1 | "that’s" | | 2 | "hers" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 769 | | uniqueNames | 7 | | maxNameDensity | 0.91 | | worstName | "Aurora" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Moreau | 1 | | French | 1 | | Eva | 1 | | Lucien | 6 | | Marseille | 1 | | Soho | 1 | | Aurora | 7 |
| | persons | | 0 | "Moreau" | | 1 | "Eva" | | 2 | "Lucien" | | 3 | "Aurora" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 36.36% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 44 | | glossingSentenceCount | 2 | | matches | | 0 | "as if remembering the last time she’d seen him" | | 1 | "looked like it had been cut from the nigh" |
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| 18.18% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 2 | | per1kWords | 1.818 | | wordCount | 1100 | | matches | | 0 | "Not the cramped space above Silas’ bar, not Eva’s cluttered one-bedroom, but something new" | | 1 | "not Eva’s cluttered one-bedroom, but something new" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 114 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 54 | | mean | 20.37 | | std | 20.02 | | cv | 0.983 | | sampleLengths | | 0 | 12 | | 1 | 73 | | 2 | 98 | | 3 | 28 | | 4 | 7 | | 5 | 23 | | 6 | 1 | | 7 | 7 | | 8 | 3 | | 9 | 7 | | 10 | 26 | | 11 | 4 | | 12 | 58 | | 13 | 33 | | 14 | 20 | | 15 | 1 | | 16 | 5 | | 17 | 3 | | 18 | 3 | | 19 | 25 | | 20 | 40 | | 21 | 6 | | 22 | 1 | | 23 | 5 | | 24 | 32 | | 25 | 34 | | 26 | 2 | | 27 | 1 | | 28 | 1 | | 29 | 42 | | 30 | 12 | | 31 | 4 | | 32 | 54 | | 33 | 8 | | 34 | 21 | | 35 | 31 | | 36 | 18 | | 37 | 44 | | 38 | 7 | | 39 | 19 | | 40 | 31 | | 41 | 43 | | 42 | 8 | | 43 | 24 | | 44 | 20 | | 45 | 25 | | 46 | 5 | | 47 | 10 | | 48 | 15 | | 49 | 13 |
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| 96.49% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 80 | | matches | | 0 | "being drawn" | | 1 | "was curled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 138 | | matches | | |
| 42.61% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 4 | | totalSentences | 114 | | ratio | 0.035 | | matches | | 0 | "“Rory,” he said, and his voice was the same—smooth, low, with that faint French lilt that had always made her name sound like a promise." | | 1 | "The flat was exactly as he remembered it—cramped, cluttered, every surface buried under books and scrolls and half-empty mugs of tea gone cold." | | 2 | "The scent of him—bergamot and something darker, something that made her think of midnight in Marseille—wrapped around her." | | 3 | "She could go back to her life—the deliveries, the late nights, the careful, controlled existence where no one could hurt her because she never let them close enough to try." |
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| 90.10% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 682 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 35 | | adverbRatio | 0.051319648093841645 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.010263929618768328 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 114 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 114 | | mean | 9.65 | | std | 8.03 | | cv | 0.833 | | sampleLengths | | 0 | 12 | | 1 | 26 | | 2 | 18 | | 3 | 29 | | 4 | 14 | | 5 | 29 | | 6 | 23 | | 7 | 32 | | 8 | 25 | | 9 | 3 | | 10 | 3 | | 11 | 4 | | 12 | 19 | | 13 | 4 | | 14 | 1 | | 15 | 7 | | 16 | 3 | | 17 | 4 | | 18 | 3 | | 19 | 6 | | 20 | 8 | | 21 | 5 | | 22 | 3 | | 23 | 4 | | 24 | 4 | | 25 | 23 | | 26 | 14 | | 27 | 21 | | 28 | 8 | | 29 | 25 | | 30 | 15 | | 31 | 5 | | 32 | 1 | | 33 | 5 | | 34 | 3 | | 35 | 3 | | 36 | 8 | | 37 | 12 | | 38 | 5 | | 39 | 5 | | 40 | 19 | | 41 | 8 | | 42 | 8 | | 43 | 3 | | 44 | 3 | | 45 | 1 | | 46 | 5 | | 47 | 11 | | 48 | 21 | | 49 | 6 |
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| 43.86% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.3157894736842105 | | totalSentences | 114 | | uniqueOpeners | 36 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 74 | | matches | | 0 | "Of course he saw it." | | 1 | "Instead, he moved deeper into" | | 2 | "Instead, she said," | | 3 | "Then, slowly, he reached into" |
| | ratio | 0.054 | |
| 47.03% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 74 | | matches | | 0 | "He wore one of his" | | 1 | "he said, and his voice" | | 2 | "She didn’t answer." | | 3 | "She flinched, just slightly, but" | | 4 | "He didn’t so much as" | | 5 | "He tapped the cane against" | | 6 | "She turned away, busying herself" | | 7 | "He didn’t answer right away." | | 8 | "His cane left faint indentations" | | 9 | "He turned, his heterochromatic eyes" | | 10 | "She yanked it off the" | | 11 | "She spun around, the words" | | 12 | "He took a step closer" | | 13 | "His voice dropped, low and" | | 14 | "Her breath hitched." | | 15 | "She wanted to step back." | | 16 | "She wanted to step forward." | | 17 | "She wanted to scream." | | 18 | "His fingers brushed against her" | | 19 | "Her pulse jumped beneath his" |
| | ratio | 0.432 | |
| 14.05% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 66 | | totalSentences | 74 | | matches | | 0 | "The deadbolt scraped back with" | | 1 | "Aurora stood in the doorway," | | 2 | "The crescent-shaped scar on her" | | 3 | "The scent of curry from" | | 4 | "Lucien Moreau leaned against the" | | 5 | "The amber of his left" | | 6 | "He wore one of his" | | 7 | "A single platinum strand of" | | 8 | "he said, and his voice" | | 9 | "She didn’t answer." | | 10 | "The chain stayed latched." | | 11 | "Lucien exhaled through his nose," | | 12 | "A beat of silence." | | 13 | "The word landed like a" | | 14 | "She flinched, just slightly, but" | | 15 | "Lucien missed nothing." | | 16 | "That was the problem." | | 17 | "Aurora unlatched the chain." | | 18 | "The flat was exactly as" | | 19 | "Ptolemy, Eva’s tabby cat, was" |
| | ratio | 0.892 | |
| 67.57% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 74 | | matches | | | ratio | 0.014 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 24 | | technicalSentenceCount | 4 | | matches | | 0 | "The crescent-shaped scar on her left wrist pulsed faintly, as if remembering the last time she’d seen him." | | 1 | "The scent of curry from the restaurant below curled around her ankles, thick and cloying, but it was the man on her doorstep who made her throat go dry." | | 2 | "A single platinum strand of hair had escaped its slicked-back prison, curling against his temple in a way that made her fingers twitch with the memory of how so…" | | 3 | "The scent of him—bergamot and something darker, something that made her think of midnight in Marseille—wrapped around her." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 4 | | matches | | 0 | "he said, and his voice was the same—smooth, low, with that faint French lilt that had always made her name sound like a promise" | | 1 | "He tapped, the ivory handle catching the light" | | 2 | "He turned, his heterochromatic eyes locking onto hers" | | 3 | "She spun around, the words spilling out before she could stop them" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 2 | | fancyTags | | 0 | "she whispered (whisper)" | | 1 | "she breathed (breathe)" |
| | dialogueSentences | 51 | | tagDensity | 0.098 | | leniency | 0.196 | | rawRatio | 0.4 | | effectiveRatio | 0.078 | |