| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 5 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 12 | | tagDensity | 0.417 | | leniency | 0.833 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 97.28% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1840 | | 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) | |
| 64.67% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1840 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "pulse" | | 1 | "flickered" | | 2 | "lurch" | | 3 | "glistening" | | 4 | "flicked" | | 5 | "porcelain" | | 6 | "pulsed" | | 7 | "velvet" | | 8 | "shattered" | | 9 | "echoing" |
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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 | 0 | | narrationSentences | 219 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 1 | | narrationSentences | 219 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 226 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 23 | | markdownWords | 61 | | totalWords | 1812 | | ratio | 0.034 | | matches | | 0 | "The Raven, The Raven" | | 1 | "Herrera" | | 2 | "Tommy" | | 3 | "Tommy" | | 4 | "Berwick Street Market closed at midnight, no one should be there" | | 5 | "No Access" | | 6 | "something" | | 7 | "Veil Market." | | 8 | "something going wrong" | | 9 | "clang." | | 10 | "alive." | | 11 | "visible." | | 12 | "Bone token." | | 13 | "skinwalkers, maybe" | | 14 | "stared." | | 15 | "Bleak House" | | 16 | "The Turn of the Screw." | | 17 | "What the hell are you?" | | 18 | "not smoke." | | 19 | "waiting." | | 20 | "answered" | | 21 | "DI Carter. No voice, no explanation. Just the location ping." | | 22 | "hers." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 5 | | unquotedAttributions | 0 | | matches | (empty) | |
| 81.90% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 76 | | wordCount | 1762 | | uniqueNames | 21 | | maxNameDensity | 1.36 | | worstName | "Quinn" | | maxWindowNameDensity | 2.5 | | worstWindowName | "Herrera" | | discoveredNames | | Raven | 3 | | Nest | 1 | | Harlow | 1 | | Quinn | 24 | | Thai | 1 | | Herrera | 21 | | Special | 1 | | Branch | 1 | | Wardour | 1 | | Street | 2 | | Chinatown | 1 | | Market | 6 | | London | 1 | | Veil | 5 | | Maglite | 1 | | Victorian | 1 | | Tube | 1 | | Turn | 1 | | Gas | 1 | | Carter | 1 | | Soho | 1 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Herrera" | | 3 | "Market" | | 4 | "Gas" | | 5 | "Carter" |
| | places | | 0 | "Raven" | | 1 | "Special" | | 2 | "Wardour" | | 3 | "Street" | | 4 | "London" | | 5 | "Veil" | | 6 | "Soho" |
| | globalScore | 0.819 | | windowScore | 0.833 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 110 | | glossingSentenceCount | 1 | | matches | | 0 | "something like static, as if sound traveled" |
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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 | 1812 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 226 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 86 | | mean | 21.07 | | std | 18.83 | | cv | 0.894 | | sampleLengths | | 0 | 70 | | 1 | 49 | | 2 | 43 | | 3 | 3 | | 4 | 67 | | 5 | 29 | | 6 | 4 | | 7 | 55 | | 8 | 49 | | 9 | 26 | | 10 | 34 | | 11 | 3 | | 12 | 5 | | 13 | 54 | | 14 | 5 | | 15 | 31 | | 16 | 43 | | 17 | 3 | | 18 | 73 | | 19 | 51 | | 20 | 6 | | 21 | 61 | | 22 | 25 | | 23 | 43 | | 24 | 16 | | 25 | 30 | | 26 | 2 | | 27 | 2 | | 28 | 46 | | 29 | 44 | | 30 | 9 | | 31 | 26 | | 32 | 54 | | 33 | 10 | | 34 | 15 | | 35 | 3 | | 36 | 20 | | 37 | 9 | | 38 | 6 | | 39 | 21 | | 40 | 4 | | 41 | 24 | | 42 | 2 | | 43 | 5 | | 44 | 2 | | 45 | 39 | | 46 | 16 | | 47 | 3 | | 48 | 27 | | 49 | 21 |
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| 97.25% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 5 | | totalSentences | 219 | | matches | | 0 | "was slicked" | | 1 | "was gone" | | 2 | "were muffled" | | 3 | "were obscured" | | 4 | "been seen" |
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| 73.42% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 6 | | totalVerbs | 316 | | matches | | 0 | "was vanishing" | | 1 | "wasn’t running" | | 2 | "was *waiting" | | 3 | "was thinning" | | 4 | "was tilting" | | 5 | "was spreading" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 40 | | semicolonCount | 0 | | flaggedSentences | 33 | | totalSentences | 226 | | ratio | 0.146 | | matches | | 0 | "The rain came down like judgment—cold, relentless, turning every neon pulse from The Raven’s Nest into a shivering smear on wet pavement." | | 1 | "The green neon sign flickered—*The Raven, The Raven*—as if calling her out by name." | | 2 | "Tomas Herrera—*Herrera*, not *Tommy*, never *Tommy*—had been inside for eleven." | | 3 | "Rain was just weather—she’d survived worse." | | 4 | "Even from twenty paces, she saw the way his eyes flicked left then right—like a man checking for tails." | | 5 | "He walked fast—purposeful strides down Wardour Street, dodging puddles, weaving through late-night crowds of drunks and tourists in branded club wear." | | 6 | "When he turned abruptly into an alley near Chinatown—*Berwick Street Market closed at midnight, no one should be there*—Quinn increased her pace." | | 7 | "Herrera was already at the far end, pressing something into a keypad beside a rusted service door marked *No Access*—but the way his fingers moved, quick and practiced, spoke of familiarity." | | 8 | "Quinn had read the case files—the black-market bazaar beneath London, moving like a parasite, living in the lungs of the city." | | 9 | "And in the Veil Market, *something going wrong* wasn’t a possibility—it was an inevitability." | | 10 | "The door swung shut behind her with a hollow *clang.* The air turned thick—dank, metallic, the kind of damp that clung to lungs and left a film on the back of your throat." | | 11 | "The beam cut through the murk, revealing worn stone steps carved generations ago—maybe Victorian, maybe older." | | 12 | "Herrera was across the market, weaving between a group of pale figures in long coats—*skinwalkers, maybe*—and a stall hawking \"genuine cursed dolls.\" He glanced back once, eyes locking onto hers." | | 13 | "The canvas tore away from a cage of rattling things—young faces, no older than ten, their eyes black and vacant." | | 14 | "The corridor dead-ended in a brick wall—except it wasn’t a wall." | | 15 | "No, not just a bookshelf—a false front." | | 16 | "Beyond was another room—small, lit by a single blue bulb." | | 17 | "Herrera stood at the far end, a knife in his hand—long, curved, something you’d use in an abattoir." | | 18 | "The room felt wrong—walls breathing, the blue bulb flickering like a dying insect." | | 19 | "She dodged, but not fast enough—his blade raked her thigh through her coat." | | 20 | "A wave of blue smoke erupted—*not smoke.* Gas." | | 21 | "Herrera was moving again—toward a shadowed corner where a second door stood half-open, leading into darkness." | | 22 | "Quinn feinted right, then drove forward low—shoulder into his gut." | | 23 | "She blocked with her forearm—bone on bone, pain like lightning—but got his wrist pinned." | | 24 | "Youth, adrenaline, maybe something else—something not human." | | 25 | "Their faces—if they were faces—were obscured by shifting shadows." | | 26 | "His voice was different now—softer." | | 27 | "The fire alarm in the Veil Market had begun—a high, wailing siren, alien and dissonant, cutting through the smoke and stench." | | 28 | "The first stall in the main chamber had gone up—flames licking across a table of enchanted jewelry." | | 29 | "She turned and ran—not after Herrera, not into the shadowed corridor—but back through the bookshelf, back into the artery of the Veil Market, where the fire was spreading like a living thing, where panicked bodies shoved past her, where a goblin child with too many teeth screamed in a language Quinn refused to hear." | | 30 | "But in the distance, something *answered*—a low, guttural growl rising from the sewers, or maybe it was in the wind." | | 31 | "Worse—she’d been seen." | | 32 | "But for tonight—it was *hers.*" |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1800 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 66 | | adverbRatio | 0.03666666666666667 | | lyAdverbCount | 9 | | lyAdverbRatio | 0.005 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 226 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 226 | | mean | 8.02 | | std | 7.02 | | cv | 0.876 | | sampleLengths | | 0 | 22 | | 1 | 23 | | 2 | 14 | | 3 | 7 | | 4 | 2 | | 5 | 2 | | 6 | 15 | | 7 | 4 | | 8 | 10 | | 9 | 9 | | 10 | 6 | | 11 | 1 | | 12 | 4 | | 13 | 20 | | 14 | 2 | | 15 | 4 | | 16 | 11 | | 17 | 6 | | 18 | 3 | | 19 | 16 | | 20 | 9 | | 21 | 8 | | 22 | 15 | | 23 | 19 | | 24 | 11 | | 25 | 8 | | 26 | 4 | | 27 | 6 | | 28 | 4 | | 29 | 21 | | 30 | 12 | | 31 | 22 | | 32 | 9 | | 33 | 6 | | 34 | 3 | | 35 | 31 | | 36 | 14 | | 37 | 9 | | 38 | 3 | | 39 | 15 | | 40 | 4 | | 41 | 7 | | 42 | 6 | | 43 | 1 | | 44 | 1 | | 45 | 3 | | 46 | 3 | | 47 | 2 | | 48 | 21 | | 49 | 20 |
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| 41.15% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 22 | | diversityRatio | 0.3053097345132743 | | totalSentences | 226 | | uniqueOpeners | 69 | |
| 93.11% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 179 | | matches | | 0 | "Then he came." | | 1 | "Then the lamp cracked." | | 2 | "Then past her, to the" | | 3 | "Just the location ping.*" | | 4 | "Then she slipped into the" |
| | ratio | 0.028 | |
| 99.33% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 54 | | totalSentences | 179 | | matches | | 0 | "She didn’t move under its" | | 1 | "Her leather watch glinted when" | | 2 | "She adjusted the collar of" | | 3 | "His curly dark hair was" | | 4 | "She didn’t want to spook" | | 5 | "He walked fast—purposeful strides down" | | 6 | "She stayed two lengths behind," | | 7 | "She ignored it." | | 8 | "He was gone." | | 9 | "She was three strides from" | | 10 | "He pressed *something* against the" | | 11 | "Her breath caught." | | 12 | "She hesitated on the threshold." | | 13 | "She stepped inside." | | 14 | "They were *alive.* She saw" | | 15 | "She took a breath and" | | 16 | "Her shoes made almost no" | | 17 | "She was too warm." | | 18 | "She hadn’t planned on coming" | | 19 | "They didn’t scream." |
| | ratio | 0.302 | |
| 74.53% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 138 | | totalSentences | 179 | | matches | | 0 | "The rain came down like" | | 1 | "Detective Harlow Quinn kept her" | | 2 | "The green neon sign flickered—*The" | | 3 | "She didn’t move under its" | | 4 | "Her leather watch glinted when" | | 5 | "Tomas Herrera—*Herrera*, not *Tommy*, never" | | 6 | "The kind of timing that" | | 7 | "Favor for a clique." | | 8 | "She adjusted the collar of" | | 9 | "Rain didn’t scare her." | | 10 | "Rain was just weather—she’d survived" | | 11 | "Herrera pushed through the door" | | 12 | "This was a man late" | | 13 | "His curly dark hair was" | | 14 | "Quinn stepped from the awning" | | 15 | "She didn’t want to spook" | | 16 | "He walked fast—purposeful strides down" | | 17 | "She stayed two lengths behind," | | 18 | "The alley smelled of fried" | | 19 | "A rat skittered past her" |
| | ratio | 0.771 | |
| 27.93% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 179 | | matches | | 0 | "Even from twenty paces, she" |
| | ratio | 0.006 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 65 | | technicalSentenceCount | 2 | | matches | | 0 | "The voices from below were muffled, layered with something like static, as if sound traveled differently here." | | 1 | "She sprinted, her watch thudding against her wrist, rainwater still dripping from her sleeves." |
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| 25.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 5 | | uselessAdditionCount | 1 | | matches | | |
| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "Quinn barked (bark)" | | 1 | "she growled (growl)" |
| | dialogueSentences | 12 | | tagDensity | 0.333 | | leniency | 0.667 | | rawRatio | 0.5 | | effectiveRatio | 0.333 | |