| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 10 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 93.44% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1524 | | totalAiIsmAdverbs | 2 | | 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) | |
| 73.75% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1524 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "rhythmic" | | 1 | "glint" | | 2 | "weight" | | 3 | "determined" | | 4 | "wavering" | | 5 | "silk" | | 6 | "silence" | | 7 | "flicker" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 99.75% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 3 | | narrationSentences | 99 | | matches | | 0 | "k with panic" | | 1 | "was desperate" | | 2 | "looked terrified" |
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| 41.85% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 7 | | narrationSentences | 99 | | filterMatches | (empty) | | hedgeMatches | | 0 | "happened to" | | 1 | "began to" | | 2 | "seemed to" |
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| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 109 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 1 | | totalWords | 1512 | | ratio | 0.001 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 11 | | unquotedAttributions | 0 | | matches | (empty) | |
| 59.57% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 71 | | wordCount | 1327 | | uniqueNames | 22 | | maxNameDensity | 1.81 | | worstName | "Quinn" | | maxWindowNameDensity | 3 | | worstWindowName | "Quinn" | | discoveredNames | | Raven | 1 | | Nest | 2 | | Soho | 2 | | Harlow | 1 | | Quinn | 24 | | Tomás | 12 | | Herrera | 7 | | Clique | 1 | | Saint | 2 | | Christopher | 2 | | Morris | 3 | | Camden | 1 | | Victorian | 1 | | Tube | 1 | | Metropolitan | 1 | | Police | 1 | | London | 1 | | Underground | 1 | | Veil | 2 | | Market | 2 | | Spanish | 1 | | Enforcer | 2 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Harlow" | | 3 | "Quinn" | | 4 | "Tomás" | | 5 | "Herrera" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Morris" | | 9 | "Enforcer" |
| | places | | 0 | "Soho" | | 1 | "Victorian" | | 2 | "Metropolitan" | | 3 | "London" | | 4 | "Market" |
| | globalScore | 0.596 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 83 | | glossingSentenceCount | 1 | | matches | | 0 | "shadows that seemed to move independently of their owners" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.661 | | wordCount | 1512 | | matches | | 0 | "not to attack Quinn, but to grab her arm" |
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| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 109 | | matches | | |
| 83.64% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 36 | | mean | 42 | | std | 18.6 | | cv | 0.443 | | sampleLengths | | 0 | 58 | | 1 | 63 | | 2 | 69 | | 3 | 9 | | 4 | 102 | | 5 | 57 | | 6 | 57 | | 7 | 54 | | 8 | 24 | | 9 | 51 | | 10 | 46 | | 11 | 35 | | 12 | 58 | | 13 | 34 | | 14 | 40 | | 15 | 34 | | 16 | 18 | | 17 | 49 | | 18 | 58 | | 19 | 37 | | 20 | 48 | | 21 | 39 | | 22 | 14 | | 23 | 30 | | 24 | 73 | | 25 | 38 | | 26 | 36 | | 27 | 32 | | 28 | 19 | | 29 | 40 | | 30 | 39 | | 31 | 43 | | 32 | 18 | | 33 | 38 | | 34 | 37 | | 35 | 15 |
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| 73.37% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 9 | | totalSentences | 99 | | matches | | 0 | "being seen" | | 1 | "were gone" | | 2 | "was replaced" | | 3 | "was determined" | | 4 | "been transformed" | | 5 | "was filled" | | 6 | "was plastered" | | 7 | "was outmatched" | | 8 | "were gone" |
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| 26.09% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 230 | | matches | | 0 | "was already beginning" | | 1 | "was heading" | | 2 | "was weighing" | | 3 | "was threatening" | | 4 | "was hammering" | | 5 | "wasn't going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 12 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 109 | | ratio | 0.083 | | matches | | 0 | "He looked left, then right—a jerky, paranoid motion—before setting off toward the north." | | 1 | "Her joints ached—a dull thrum in her knees that reminded her she was forty-one, not thirty—but she didn't slow." | | 2 | "The signs were gone, the gates chained shut—or they should have been." | | 3 | "A dim, flickering light emanated from further down the escalator shaft—a pulsing violet hue that made the hair on Quinn’s neck stand up." | | 4 | "It was a tactical error—the instinct of a street cop in a place that didn't respect the law—but she needed him to stop before he vanished into the throng." | | 5 | "They were less than twenty yards away now, and she could see what lay beneath the hoods—nothing but swirling grey mist and two pinpricks of icy light." | | 6 | "He looked terrified, but beneath the fear, Quinn saw a flicker of that same paramedic instinct—the urge to save a life, even one that was threatening him." | | 7 | "One of them raised a hand—a pale, translucent thing with too many joints." | | 8 | "He reached into his pocket and produced a second bone token—this one charred and blackened." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1350 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 29 | | adverbRatio | 0.02148148148148148 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.005925925925925926 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 109 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 109 | | mean | 13.87 | | std | 7.21 | | cv | 0.52 | | sampleLengths | | 0 | 20 | | 1 | 23 | | 2 | 13 | | 3 | 2 | | 4 | 37 | | 5 | 7 | | 6 | 16 | | 7 | 3 | | 8 | 22 | | 9 | 12 | | 10 | 22 | | 11 | 13 | | 12 | 9 | | 13 | 21 | | 14 | 17 | | 15 | 19 | | 16 | 2 | | 17 | 6 | | 18 | 25 | | 19 | 12 | | 20 | 13 | | 21 | 26 | | 22 | 18 | | 23 | 24 | | 24 | 12 | | 25 | 21 | | 26 | 12 | | 27 | 14 | | 28 | 6 | | 29 | 12 | | 30 | 10 | | 31 | 3 | | 32 | 13 | | 33 | 8 | | 34 | 4 | | 35 | 20 | | 36 | 4 | | 37 | 23 | | 38 | 11 | | 39 | 4 | | 40 | 8 | | 41 | 23 | | 42 | 13 | | 43 | 17 | | 44 | 5 | | 45 | 11 | | 46 | 11 | | 47 | 17 | | 48 | 19 | | 49 | 9 |
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| 54.13% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 6 | | diversityRatio | 0.3577981651376147 | | totalSentences | 109 | | uniqueOpeners | 39 | |
| 35.09% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 95 | | matches | | 0 | "Instead of commuters, the space" |
| | ratio | 0.011 | |
| 43.16% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 95 | | matches | | 0 | "She checked the worn leather" | | 1 | "She had been following Tomás" | | 2 | "She watched the door of" | | 3 | "It creaked open, spilling amber" | | 4 | "He was younger than her" | | 5 | "His dark, curly hair was" | | 6 | "He pulled his collar up," | | 7 | "He looked left, then right—a" | | 8 | "Her eighteen years on the" | | 9 | "She kept her distance, using" | | 10 | "Her joints ached—a dull thrum" | | 11 | "He turned into a narrow" | | 12 | "She rounded the corner just" | | 13 | "He reached into his pocket" | | 14 | "He held it up to" | | 15 | "She threw her weight against" | | 16 | "It yielded with a groan" | | 17 | "She drew her service weapon," | | 18 | "Her sharp jaw tightened." | | 19 | "She descended the dead escalator," |
| | ratio | 0.442 | |
| 17.89% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 84 | | totalSentences | 95 | | matches | | 0 | "The green neon sign of" | | 1 | "Detective Harlow Quinn stood in" | | 2 | "She checked the worn leather" | | 3 | "She had been following Tomás" | | 4 | "She watched the door of" | | 5 | "It creaked open, spilling amber" | | 6 | "Herrera stepped out." | | 7 | "He was younger than her" | | 8 | "His dark, curly hair was" | | 9 | "He pulled his collar up," | | 10 | "He looked left, then right—a" | | 11 | "Quinn waited five seconds, then" | | 12 | "Her eighteen years on the" | | 13 | "She kept her distance, using" | | 14 | "Her joints ached—a dull thrum" | | 15 | "Every time she closed her" | | 16 | "Herrera was the closest she’d" | | 17 | "The chase led them out" | | 18 | "Herrera was fast, his boots" | | 19 | "He turned into a narrow" |
| | ratio | 0.884 | |
| 52.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 95 | | matches | | 0 | "Before Tomás could respond, a" |
| | ratio | 0.011 | |
| 52.15% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 63 | | technicalSentenceCount | 8 | | matches | | 0 | "He was younger than her by a decade, twenty-nine with the kind of restless energy that made him hard to pin down." | | 1 | "Her joints ached—a dull thrum in her knees that reminded her she was forty-one, not thirty—but she didn't slow." | | 2 | "Herrera was fast, his boots splashing through puddles, his gait showing the practiced navigation of someone who knew these streets as a map of escape routes." | | 3 | "As Quinn reached the top of the stairs, she saw Herrera stop at a side door that had been pry-barred open." | | 4 | "A dim, flickering light emanated from further down the escalator shaft—a pulsing violet hue that made the hair on Quinn’s neck stand up." | | 5 | "This was the territory that had swallowed DS Morris whole, a world of shadows she didn't yet understand but was determined to break." | | 6 | "Blue-flame lanterns hung from the vaulted ceiling, casting long, wavering shadows that seemed to move independently of their owners." | | 7 | "But something deeper, the primal part of her that remembered the look on Morris’s face, screamed that she was outmatched." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 10 | | uselessAdditionCount | 4 | | matches | | 0 | "he gasped, his Spanish accent thick with panic" | | 1 | "she said, her voice a cold rasp" | | 2 | "Tomás whispered, not looking back" | | 3 | "she said, her voice regaining its iron" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 6 | | fancyTags | | 0 | "he gasped (gasp)" | | 1 | "Tomás whispered (whisper)" | | 2 | "Quinn snapped (snap)" | | 3 | "Tomás hissed (hiss)" | | 4 | "she growled (growl)" | | 5 | "Tomás whispered (whisper)" |
| | dialogueSentences | 22 | | tagDensity | 0.455 | | leniency | 0.909 | | rawRatio | 0.6 | | effectiveRatio | 0.545 | |