| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 19 | | tagDensity | 0.263 | | leniency | 0.526 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.24% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1567 | | totalAiIsmAdverbs | 4 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
| | 2 | |
| | highlights | | 0 | "slightly" | | 1 | "barely above a whisper" | | 2 | "slowly" |
| |
| 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) | |
| 45.76% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1567 | | totalAiIsms | 17 | | found | | | highlights | | 0 | "glistening" | | 1 | "navigating" | | 2 | "fractured" | | 3 | "scanned" | | 4 | "flicker" | | 5 | "weight" | | 6 | "familiar" | | 7 | "pulse" | | 8 | "wavering" | | 9 | "scanning" | | 10 | "stomach" | | 11 | "silk" | | 12 | "glinting" | | 13 | "flickered" | | 14 | "whisper" |
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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 | 132 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 2 | | narrationSentences | 132 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 145 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 1 | | markdownWords | 3 | | totalWords | 1556 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 58 | | wordCount | 1419 | | uniqueNames | 12 | | maxNameDensity | 1.76 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Herrera" | | discoveredNames | | London | 1 | | Harlow | 1 | | Quinn | 25 | | Soho | 1 | | Herrera | 21 | | Raven | 1 | | Nest | 2 | | Morris | 2 | | Saint | 1 | | Christopher | 1 | | Veil | 1 | | Market | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Raven" | | 4 | "Nest" | | 5 | "Morris" | | 6 | "Saint" | | 7 | "Christopher" | | 8 | "Market" |
| | places | | | globalScore | 0.619 | | windowScore | 0.333 | |
| 73.47% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 98 | | glossingSentenceCount | 3 | | matches | | 0 | "looked like ledgers" | | 1 | "looked like teeth across the floor" | | 2 | "shadows that seemed to press in closer" |
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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 | 1556 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 145 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 33.83 | | std | 24.58 | | cv | 0.727 | | sampleLengths | | 0 | 82 | | 1 | 17 | | 2 | 59 | | 3 | 73 | | 4 | 8 | | 5 | 80 | | 6 | 60 | | 7 | 69 | | 8 | 8 | | 9 | 56 | | 10 | 32 | | 11 | 14 | | 12 | 60 | | 13 | 59 | | 14 | 8 | | 15 | 73 | | 16 | 6 | | 17 | 51 | | 18 | 63 | | 19 | 21 | | 20 | 3 | | 21 | 45 | | 22 | 8 | | 23 | 33 | | 24 | 65 | | 25 | 52 | | 26 | 30 | | 27 | 2 | | 28 | 73 | | 29 | 48 | | 30 | 10 | | 31 | 9 | | 32 | 15 | | 33 | 13 | | 34 | 41 | | 35 | 10 | | 36 | 34 | | 37 | 24 | | 38 | 17 | | 39 | 32 | | 40 | 23 | | 41 | 7 | | 42 | 12 | | 43 | 17 | | 44 | 27 | | 45 | 7 |
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| 91.97% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 132 | | matches | | 0 | "was connected" | | 1 | "were lined" | | 2 | "been lost" | | 3 | "were lined" | | 4 | "been worn" |
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| 93.76% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 251 | | matches | | 0 | "was running" | | 1 | "wasn’t losing" | | 2 | "wasn’t leaving" | | 3 | "was buying" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 13 | | semicolonCount | 0 | | flaggedSentences | 11 | | totalSentences | 145 | | ratio | 0.076 | | matches | | 0 | "There—just a flicker of movement." | | 1 | "Tomás Herrera—if the tip she’d gotten was right—wasn’t just some two-bit dealer." | | 2 | "There—a slight give beneath her touch." | | 3 | "A low murmur of voices filled the air, the words indistinct but the tone unmistakable—this was a market." | | 4 | "She’d seen things in her time on the force—things that defied explanation—but this was different." | | 5 | "Quinn’s breath caught as the man produced a small, curved bone—pale and smooth, like something that had been worn down by time." | | 6 | "She’d heard whispers of it—rumors of a black market that dealt in things beyond the law." | | 7 | "The market erupted into chaos—shouts, the clatter of overturned stalls, the hiss of something unseen slithering into the shadows." | | 8 | "She closed the distance, her fingers brushing the back of his jacket—" | | 9 | "If he got through that—" | | 10 | "Herrera’s eyes flickered with something—recognition?" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1433 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 26 | | adverbRatio | 0.018143754361479414 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.0034891835310537334 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 145 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 145 | | mean | 10.73 | | std | 6.66 | | cv | 0.621 | | sampleLengths | | 0 | 15 | | 1 | 31 | | 2 | 17 | | 3 | 19 | | 4 | 5 | | 5 | 12 | | 6 | 16 | | 7 | 2 | | 8 | 19 | | 9 | 22 | | 10 | 20 | | 11 | 12 | | 12 | 3 | | 13 | 2 | | 14 | 36 | | 15 | 3 | | 16 | 5 | | 17 | 17 | | 18 | 15 | | 19 | 17 | | 20 | 21 | | 21 | 3 | | 22 | 7 | | 23 | 13 | | 24 | 25 | | 25 | 22 | | 26 | 16 | | 27 | 13 | | 28 | 21 | | 29 | 19 | | 30 | 3 | | 31 | 5 | | 32 | 11 | | 33 | 16 | | 34 | 11 | | 35 | 6 | | 36 | 12 | | 37 | 2 | | 38 | 3 | | 39 | 8 | | 40 | 10 | | 41 | 9 | | 42 | 8 | | 43 | 6 | | 44 | 11 | | 45 | 27 | | 46 | 10 | | 47 | 12 | | 48 | 15 | | 49 | 12 |
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| 45.17% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.2620689655172414 | | totalSentences | 145 | | uniqueOpeners | 38 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 122 | | matches | | 0 | "Once she stepped through, there" | | 1 | "Then he bolted." | | 2 | "Then Herrera’s shoulders sagged, the" | | 3 | "Then he looked back at" | | 4 | "Then, slowly, he reached into" |
| | ratio | 0.041 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 34 | | totalSentences | 122 | | matches | | 0 | "Her breath came in controlled" | | 1 | "She adjusted the worn leather" | | 2 | "He was connected." | | 3 | "She wasn’t losing another one." | | 4 | "She caught herself against the" | | 5 | "He shouldered through the entrance," | | 6 | "She wiped the rain from" | | 7 | "Her instincts prickled." | | 8 | "She moved toward it, her" | | 9 | "She ran her fingers along" | | 10 | "She stepped into the passage," | | 11 | "She kept to the edges," | | 12 | "She’d seen things in her" | | 13 | "She spotted him near a" | | 14 | "She wasn’t here to arrest" | | 15 | "She needed answers." | | 16 | "He said something to the" | | 17 | "She’d seen enough case files" | | 18 | "She’d heard whispers of it—rumors" | | 19 | "He was part of whatever" |
| | ratio | 0.279 | |
| 33.77% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 104 | | totalSentences | 122 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn moved with" | | 2 | "The air smelled of wet" | | 3 | "Her breath came in controlled" | | 4 | "There—just a flicker of movement." | | 5 | "A shadow detaching itself from" | | 6 | "Quinn’s fingers twitched toward the" | | 7 | "She adjusted the worn leather" | | 8 | "The suspect was fast, weaving" | | 9 | "Tomás Herrera—if the tip she’d" | | 10 | "He was connected." | | 11 | "Quinn’s jaw tightened." | | 12 | "She wasn’t losing another one." | | 13 | "Herrera cut left down a" | | 14 | "Quinn followed, her breath hitching" | | 15 | "She caught herself against the" | | 16 | "The alley opened into a" | | 17 | "Herrera didn’t slow." | | 18 | "He shouldered through the entrance," | | 19 | "Quinn slowed as she reached" |
| | ratio | 0.852 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 122 | | matches | | 0 | "If this was the lead" | | 1 | "If Herrera was here, if" | | 2 | "If he got through that—" |
| | ratio | 0.025 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 71 | | technicalSentenceCount | 4 | | matches | | 0 | "Detective Harlow Quinn moved with the precision of a woman who had spent half her life navigating chaos, her boots splashing through puddles that reflected the …" | | 1 | "The suspect was fast, weaving through the labyrinth of Soho’s backstreets with the ease of someone who knew them intimately." | | 2 | "The air grew cooler, damp with the scent of earth and something older, something that made the hairs on the back of her neck stand on end." | | 3 | "Quinn’s breath caught as the man produced a small, curved bone—pale and smooth, like something that had been worn down by time." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | 0 | "she demanded, her voice low and rough" |
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| 97.37% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 2 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 19 | | tagDensity | 0.105 | | leniency | 0.211 | | rawRatio | 0.5 | | effectiveRatio | 0.105 | |