| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 3 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 5 | | tagDensity | 0.6 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1198 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "cautiously" | | 1 | "slowly" | | 2 | "really" |
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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) | |
| 70.78% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1198 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "mechanical" | | 1 | "echoing" | | 2 | "scanning" | | 3 | "framework" | | 4 | "raced" | | 5 | "footsteps" | | 6 | "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 | 1 | | narrationSentences | 88 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 88 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 90 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 32 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1190 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 3 | | unquotedAttributions | 0 | | matches | (empty) | |
| 89.34% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 46 | | wordCount | 1154 | | uniqueNames | 21 | | maxNameDensity | 1.21 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 14 | | Greek | 1 | | Street | 2 | | Tomás | 1 | | Herrera | 10 | | Tuesday | 1 | | Friday | 1 | | Clerkenwell | 1 | | Old | 1 | | Compton | 1 | | Metropolitan | 1 | | Police | 1 | | Turkish | 1 | | Camden | 2 | | London | 1 | | Saint | 1 | | Christopher | 1 | | Morris | 2 | | Tube | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Tomás" | | 3 | "Herrera" | | 4 | "Saint" | | 5 | "Christopher" | | 6 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "Clerkenwell" | | 4 | "Old" | | 5 | "Compton" | | 6 | "Camden" | | 7 | "London" |
| | globalScore | 0.893 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a dead end—a service entrance" |
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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 | 1190 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 90 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 36.06 | | std | 20.11 | | cv | 0.558 | | sampleLengths | | 0 | 54 | | 1 | 51 | | 2 | 6 | | 3 | 63 | | 4 | 67 | | 5 | 9 | | 6 | 65 | | 7 | 42 | | 8 | 57 | | 9 | 3 | | 10 | 3 | | 11 | 45 | | 12 | 56 | | 13 | 24 | | 14 | 38 | | 15 | 42 | | 16 | 51 | | 17 | 38 | | 18 | 9 | | 19 | 42 | | 20 | 5 | | 21 | 69 | | 22 | 46 | | 23 | 35 | | 24 | 11 | | 25 | 46 | | 26 | 42 | | 27 | 53 | | 28 | 34 | | 29 | 27 | | 30 | 29 | | 31 | 17 | | 32 | 11 |
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| 85.33% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 88 | | matches | | 0 | "been moved" | | 1 | "been taught" | | 2 | "was involved" | | 3 | "was connected" | | 4 | "been covered" | | 5 | "been transformed" | | 6 | "was swallowed" |
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| 94.18% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 189 | | matches | | 0 | "was running" | | 1 | "was pursuing" | | 2 | "were seeking" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 90 | | ratio | 0.078 | | matches | | 0 | "The former paramedic had a pattern—Tuesday and Friday nights, he slipped away from his flat in Clerkenwell and made his way to various locations across the city." | | 1 | "Herrera ducked into what looked like a dead end—a service entrance behind a row of shops, blocked by rusted gates and warning signs." | | 2 | "Then she saw it—a gap in the brick wall, barely visible behind an overflowing skip." | | 3 | "The smell that wafted up was strange—incense mixed with something metallic and earthy, like pennies and freshly turned soil." | | 4 | "Her partner's face flashed through her mind—that last night, the confusion in his eyes when he'd seen something that shouldn't exist, couldn't exist according to everything they'd been taught." | | 5 | "The scar along Herrera's left forearm—she'd noticed it during surveillance." | | 6 | "People—if they were all people—moved between them, conducting business in low voices." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1169 | | adjectiveStacks | 1 | | stackExamples | | 0 | "same bone-deep certainty" |
| | adverbCount | 36 | | adverbRatio | 0.030795551753635585 | | lyAdverbCount | 16 | | lyAdverbRatio | 0.013686911890504704 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 90 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 90 | | mean | 13.22 | | std | 6.79 | | cv | 0.514 | | sampleLengths | | 0 | 16 | | 1 | 21 | | 2 | 17 | | 3 | 8 | | 4 | 27 | | 5 | 6 | | 6 | 10 | | 7 | 6 | | 8 | 14 | | 9 | 20 | | 10 | 12 | | 11 | 17 | | 12 | 24 | | 13 | 10 | | 14 | 18 | | 15 | 15 | | 16 | 9 | | 17 | 19 | | 18 | 10 | | 19 | 4 | | 20 | 15 | | 21 | 17 | | 22 | 6 | | 23 | 5 | | 24 | 16 | | 25 | 15 | | 26 | 13 | | 27 | 20 | | 28 | 24 | | 29 | 3 | | 30 | 3 | | 31 | 16 | | 32 | 15 | | 33 | 14 | | 34 | 23 | | 35 | 10 | | 36 | 11 | | 37 | 12 | | 38 | 13 | | 39 | 11 | | 40 | 2 | | 41 | 6 | | 42 | 17 | | 43 | 4 | | 44 | 9 | | 45 | 15 | | 46 | 15 | | 47 | 12 | | 48 | 7 | | 49 | 11 |
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| 64.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.43333333333333335 | | totalSentences | 90 | | uniqueOpeners | 39 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 85 | | matches | | 0 | "Always carrying that weathered medical" | | 1 | "Always meeting people who looked" | | 2 | "Then she saw it—a gap" | | 3 | "Only Quinn had seen the" |
| | ratio | 0.047 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 20 | | totalSentences | 85 | | matches | | 0 | "She'd been watching him for" | | 1 | "Her voice cut through the" | | 2 | "He vaulted over a newspaper" | | 3 | "He took another turn, this" | | 4 | "Her military bearing kept her" | | 5 | "They crossed over into Camden" | | 6 | "He ran harder." | | 7 | "She'd pay for this tomorrow," | | 8 | "she called out, her voice" | | 9 | "She moved forward, scanning the" | | 10 | "She craned her neck, searching" | | 11 | "She pulled out her torch" | | 12 | "She should call for backup." | | 13 | "She should mark the location" | | 14 | "She should follow procedure, the" | | 15 | "Her partner's face flashed through" | | 16 | "She knew it the way" | | 17 | "She saw Herrera's medical bag" | | 18 | "She wore layers of scarves" | | 19 | "Her smile showed too many" |
| | ratio | 0.235 | |
| 65.88% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 67 | | totalSentences | 85 | | matches | | 0 | "The rain hammered down in" | | 1 | "Detective Harlow Quinn's boots splashed" | | 2 | "She'd been watching him for" | | 3 | "The former paramedic had a" | | 4 | "Tonight she'd finally decided to" | | 5 | "Her voice cut through the" | | 6 | "He vaulted over a newspaper" | | 7 | "Quinn swore and followed, her" | | 8 | "Herrera cut left down Old" | | 9 | "Quinn stayed on him, her" | | 10 | "The worn leather watch on" | | 11 | "Whatever this man was running" | | 12 | "That fact alone told her" | | 13 | "He took another turn, this" | | 14 | "Quinn's hand went instinctively to" | | 15 | "That she was pursuing a" | | 16 | "That she'd been conducting unauthorized" | | 17 | "The alley ended at a" | | 18 | "Herrera went right, toward Camden." | | 19 | "Quinn followed, the rain soaking" |
| | ratio | 0.788 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 85 | | matches | (empty) | | ratio | 0 | |
| 73.73% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 62 | | technicalSentenceCount | 6 | | matches | | 0 | "Herrera cut left down Old Compton Street, weaving between couples huddled under shared umbrellas and groups of tourists who shouted as he pushed past." | | 1 | "The smell that wafted up was strange—incense mixed with something metallic and earthy, like pennies and freshly turned soil." | | 2 | "She should follow procedure, the same procedure that had kept her alive and advancing through the ranks for nearly two decades." | | 3 | "Her partner's face flashed through her mind—that last night, the confusion in his eyes when he'd seen something that shouldn't exist, couldn't exist according t…" | | 4 | "She knew it the way she knew her own name, the same bone-deep certainty that had made her a good detective even when it made her a difficult one." | | 5 | "Each step took her deeper into darkness, deeper into something that existed beneath the city's official surface." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 3 | | uselessAdditionCount | 2 | | matches | | 0 | "she called out, her voice echoing off brick walls" | | 1 | "the woman asked, her accent impossible to place" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | 0 | "she called out (call out)" |
| | dialogueSentences | 5 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.5 | | effectiveRatio | 0.4 | |