| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 1 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 95.57% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1129 | | totalAiIsmAdverbs | 1 | | 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) | |
| 20.28% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1129 | | totalAiIsms | 18 | | found | | | highlights | | 0 | "fractured" | | 1 | "scanned" | | 2 | "footsteps" | | 3 | "wavering" | | 4 | "unraveling" | | 5 | "pulse" | | 6 | "glinting" | | 7 | "echoing" | | 8 | "flickered" | | 9 | "silence" | | 10 | "oppressive" | | 11 | "rhythmic" | | 12 | "stomach" | | 13 | "flicked" | | 14 | "echoed" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "air was thick with" | | count | 1 |
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| | highlights | | 0 | "The air was thick with" |
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| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 87 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 1 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 99 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 34 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 2 | | markdownWords | 2 | | totalWords | 1118 | | ratio | 0.002 | | matches | | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 2 | | unquotedAttributions | 0 | | matches | (empty) | |
| 33.33% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1018 | | uniqueNames | 14 | | maxNameDensity | 1.47 | | worstName | "Quinn" | | maxWindowNameDensity | 4 | | worstWindowName | "Herrera" | | discoveredNames | | Soho | 1 | | Harlow | 1 | | Quinn | 15 | | Greek | 1 | | Street | 1 | | Herrera | 14 | | London | 1 | | Raven | 1 | | Nest | 1 | | Saint | 2 | | Christopher | 2 | | Tube | 1 | | Camden | 2 | | Morris | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Saint" | | 4 | "Christopher" | | 5 | "Camden" | | 6 | "Morris" |
| | places | | 0 | "Soho" | | 1 | "Greek" | | 2 | "Street" | | 3 | "London" | | 4 | "Raven" |
| | globalScore | 0.763 | | windowScore | 0.333 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like floating embers" |
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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 | 1118 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 99 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 34 | | mean | 32.88 | | std | 27.64 | | cv | 0.841 | | sampleLengths | | 0 | 88 | | 1 | 43 | | 2 | 75 | | 3 | 1 | | 4 | 84 | | 5 | 35 | | 6 | 52 | | 7 | 64 | | 8 | 64 | | 9 | 43 | | 10 | 12 | | 11 | 77 | | 12 | 5 | | 13 | 47 | | 14 | 11 | | 15 | 98 | | 16 | 37 | | 17 | 6 | | 18 | 50 | | 19 | 7 | | 20 | 8 | | 21 | 20 | | 22 | 22 | | 23 | 9 | | 24 | 21 | | 25 | 21 | | 26 | 4 | | 27 | 35 | | 28 | 6 | | 29 | 17 | | 30 | 25 | | 31 | 18 | | 32 | 6 | | 33 | 7 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 87 | | matches | | |
| 45.86% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 4 | | totalVerbs | 173 | | matches | | 0 | "wasn’t losing" | | 1 | "was heading" | | 2 | "was running" | | 3 | "was breathing" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 99 | | ratio | 0.091 | | matches | | 0 | "Eighteen years on the force had taught her the rhythm of a chase—the way a fleeing man’s shoulders tensed before a turn, the way his footsteps hesitated when he thought he’d lost you." | | 1 | "Tomás Herrera—former paramedic, off-the-books medic to London’s underbelly, and, if her instincts were right, the key to unraveling the clique’s operations." | | 2 | "She knew the stories—urban explorers who’d gone missing, kids who’d broken in for dares and come out changed." | | 3 | "But backup wouldn’t get here in time, and Herrera would be gone—vanished into whatever lay beneath Camden’s streets." | | 4 | "Then, a sound—low, rhythmic, like the murmur of a crowd." | | 5 | "People moved between the stalls—no, not people." | | 6 | "She’d seen things in the past three years that defied explanation—things that had gotten Morris killed." | | 7 | "Quinn turned in time to see a group of figures—tall, gaunt, their limbs too long—pushing through the crowd toward them." | | 8 | "But she knew fear when she saw it—and Herrera was terrified." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1031 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.023278370514064017 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.005819592628516004 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 99 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 99 | | mean | 11.29 | | std | 7.53 | | cv | 0.667 | | sampleLengths | | 0 | 25 | | 1 | 24 | | 2 | 19 | | 3 | 20 | | 4 | 33 | | 5 | 7 | | 6 | 3 | | 7 | 27 | | 8 | 9 | | 9 | 16 | | 10 | 15 | | 11 | 8 | | 12 | 1 | | 13 | 16 | | 14 | 21 | | 15 | 17 | | 16 | 30 | | 17 | 18 | | 18 | 11 | | 19 | 4 | | 20 | 2 | | 21 | 18 | | 22 | 22 | | 23 | 5 | | 24 | 7 | | 25 | 1 | | 26 | 11 | | 27 | 18 | | 28 | 4 | | 29 | 22 | | 30 | 5 | | 31 | 3 | | 32 | 17 | | 33 | 15 | | 34 | 20 | | 35 | 12 | | 36 | 5 | | 37 | 3 | | 38 | 18 | | 39 | 14 | | 40 | 3 | | 41 | 9 | | 42 | 3 | | 43 | 18 | | 44 | 16 | | 45 | 15 | | 46 | 28 | | 47 | 5 | | 48 | 9 | | 49 | 21 |
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| 53.54% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.3333333333333333 | | totalSentences | 99 | | uniqueOpeners | 33 | |
| 81.30% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 82 | | matches | | 0 | "Then she followed." | | 1 | "Then, a sound—low, rhythmic, like" |
| | ratio | 0.024 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 17 | | totalSentences | 82 | | matches | | 0 | "Her breath came in controlled" | | 1 | "She’d heard that hesitation three" | | 2 | "He was tiring." | | 3 | "She rounded the corner, her" | | 4 | "He’d been at the Raven’s" | | 5 | "She’d followed his trail through" | | 6 | "She wasn’t losing him." | | 7 | "He was heading for the" | | 8 | "She knew the stories—urban explorers" | | 9 | "They were hungry." | | 10 | "She could call it in." | | 11 | "Her boots splashed through shallow" | | 12 | "She followed it, her steps" | | 13 | "She’d seen things in the" | | 14 | "His eyes were wide, his" | | 15 | "She had no idea what" | | 16 | "She turned and ran." |
| | ratio | 0.207 | |
| 27.07% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 71 | | totalSentences | 82 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn moved like" | | 2 | "Her breath came in controlled" | | 3 | "The suspect had vanished around" | | 4 | "She’d heard that hesitation three" | | 5 | "He was tiring." | | 6 | "Quinn adjusted the worn leather" | | 7 | "The cold metal bit into" | | 8 | "She rounded the corner, her" | | 9 | "The alley was narrow, lined" | | 10 | "A single flickering bulb cast" | | 11 | "A figure darted across the" | | 12 | "Tomás Herrera—former paramedic, off-the-books medic" | | 13 | "He’d been at the Raven’s" | | 14 | "She’d followed his trail through" | | 15 | "Herrera ducked into a side" | | 16 | "Quinn broke into a sprint," | | 17 | "She wasn’t losing him." | | 18 | "The side street opened into" | | 19 | "Herrera glanced over his shoulder," |
| | ratio | 0.866 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 82 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 46 | | technicalSentenceCount | 10 | | matches | | 0 | "The rain came down in sheets, turning the pavement into a slick mirror that fractured the neon glow of Soho into a thousand trembling reflections." | | 1 | "Detective Harlow Quinn moved like a shadow cut loose from the storm, her boots splashing through puddles that swallowed the sound of her steps." | | 2 | "Abandoned, half-collapsed, a graveyard for trains that hadn’t run in decades." | | 3 | "Herrera disappeared down the stairs leading to the station’s entrance, his footsteps echoing back up to her." | | 4 | "Quinn hesitated at the top, her fingers tightening around the cold metal of the railing." | | 5 | "Her boots splashed through shallow pools of water that reflected the dim light like black glass." | | 6 | "The air was thick with the scent of spices and something sharper, something that made her nose burn." | | 7 | "Others moved with a fluid grace that made her stomach clench." | | 8 | "A woman with eyes like polished obsidian turned to watch her pass, her lips curling into a smile that showed too many teeth." | | 9 | "The grip loosened, and she spun, her fist connecting with a jaw that felt too solid, too *wrong*." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 1 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 78.57% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 1 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 14 | | tagDensity | 0.071 | | leniency | 0.143 | | rawRatio | 1 | | effectiveRatio | 0.143 | |