| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 14 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 33 | | tagDensity | 0.424 | | leniency | 0.848 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 88.37% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1719 | | totalAiIsmAdverbs | 4 | | found | | 0 | | adverb | "deliberately" | | count | 1 |
| | 1 | | | 2 | | | 3 | |
| | highlights | | 0 | "deliberately" | | 1 | "carefully" | | 2 | "quickly" | | 3 | "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) | |
| 62.19% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1719 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "measured" | | 1 | "footsteps" | | 2 | "warmth" | | 3 | "flickered" | | 4 | "familiar" | | 5 | "unreadable" | | 6 | "weight" | | 7 | "scanning" | | 8 | "methodical" | | 9 | "tension" | | 10 | "standard" | | 11 | "stomach" |
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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 | 0 | | narrationSentences | 110 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 3 | | hedgeCount | 0 | | narrationSentences | 110 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 129 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 68 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1707 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 16 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1372 | | uniqueNames | 19 | | maxNameDensity | 0.58 | | worstName | "Eva" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Eva" | | discoveredNames | | Eva | 8 | | God | 1 | | Silas | 2 | | Rory | 8 | | Lucien | 7 | | Oxfords | 1 | | Whitechapel | 1 | | Marseille | 2 | | London | 1 | | Moreau | 2 | | Brick | 1 | | Lane | 1 | | Golden | 1 | | Empress | 1 | | Thames | 1 | | Sunday | 1 | | November | 1 | | Digestives | 1 | | Ptolemy | 4 |
| | persons | | 0 | "Eva" | | 1 | "Silas" | | 2 | "Rory" | | 3 | "Lucien" | | 4 | "Moreau" | | 5 | "Ptolemy" |
| | places | | 0 | "Whitechapel" | | 1 | "Marseille" | | 2 | "London" | | 3 | "Brick" | | 4 | "Lane" | | 5 | "Golden" | | 6 | "Thames" | | 7 | "November" |
| | globalScore | 1 | | windowScore | 1 | |
| 41.30% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 69 | | glossingSentenceCount | 3 | | matches | | 0 | "sounded like a proposition" | | 1 | "smelled like sandalwood and smoke" | | 2 | "looked like a conspiracy theorist’s fever" |
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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 | 1707 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 1 | | totalSentences | 129 | | matches | | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 50 | | mean | 34.14 | | std | 26.57 | | cv | 0.778 | | sampleLengths | | 0 | 65 | | 1 | 56 | | 2 | 4 | | 3 | 1 | | 4 | 13 | | 5 | 50 | | 6 | 9 | | 7 | 56 | | 8 | 54 | | 9 | 14 | | 10 | 4 | | 11 | 4 | | 12 | 44 | | 13 | 50 | | 14 | 19 | | 15 | 5 | | 16 | 36 | | 17 | 69 | | 18 | 52 | | 19 | 3 | | 20 | 58 | | 21 | 54 | | 22 | 38 | | 23 | 5 | | 24 | 47 | | 25 | 66 | | 26 | 8 | | 27 | 2 | | 28 | 19 | | 29 | 76 | | 30 | 6 | | 31 | 4 | | 32 | 42 | | 33 | 49 | | 34 | 55 | | 35 | 19 | | 36 | 36 | | 37 | 103 | | 38 | 6 | | 39 | 9 | | 40 | 56 | | 41 | 65 | | 42 | 7 | | 43 | 95 | | 44 | 17 | | 45 | 31 | | 46 | 4 | | 47 | 63 | | 48 | 26 | | 49 | 33 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 110 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 227 | | matches | | 0 | "were running" | | 1 | "was crossing" | | 2 | "was going" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 9 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 129 | | ratio | 0.054 | | matches | | 0 | "The silver-headed cane rested against his gloved hand, and his eyes—God, those mismatched eyes—found hers like a blade finding its sheath." | | 1 | "The phone calls she’d ignored, the texts she’d deleted without reading, the messages he’d sent through people who didn’t know they were running his errands—all of it had been practice for this moment." | | 2 | "She’d let her guard down for half a second—that’s all it took with him." | | 3 | "Something flickered in his amber eye—quick as a shutter closing—and then his face smoothed into that familiar, unreadable neutrality she had spent months trying to decode and another six months trying to forget." | | 4 | "She was still in her delivery clothes—the black joggers and hoodie she wore for the evening shift at the Golden Empress, the fabric smelling faintly of sesame oil and soy sauce." | | 5 | "The knuckles of his right hand, visible above the glove, were bruised—fresh ones, purple and black, the kind that came from throwing a punch and hitting bone." | | 6 | "She pulled two mugs from the shelf—her own, a chipped ceramic thing with a faded daisy on the side, and Eva’s spare, which had a crack in the handle she’d been meaning to mention for three months." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1388 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 43 | | adverbRatio | 0.030979827089337175 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.00792507204610951 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 129 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 129 | | mean | 13.23 | | std | 11.98 | | cv | 0.905 | | sampleLengths | | 0 | 11 | | 1 | 18 | | 2 | 36 | | 3 | 4 | | 4 | 6 | | 5 | 25 | | 6 | 21 | | 7 | 2 | | 8 | 2 | | 9 | 1 | | 10 | 10 | | 11 | 3 | | 12 | 6 | | 13 | 26 | | 14 | 7 | | 15 | 11 | | 16 | 9 | | 17 | 10 | | 18 | 3 | | 19 | 33 | | 20 | 10 | | 21 | 8 | | 22 | 19 | | 23 | 9 | | 24 | 9 | | 25 | 9 | | 26 | 4 | | 27 | 10 | | 28 | 4 | | 29 | 4 | | 30 | 3 | | 31 | 14 | | 32 | 12 | | 33 | 13 | | 34 | 2 | | 35 | 11 | | 36 | 22 | | 37 | 17 | | 38 | 6 | | 39 | 8 | | 40 | 5 | | 41 | 5 | | 42 | 3 | | 43 | 33 | | 44 | 22 | | 45 | 2 | | 46 | 36 | | 47 | 9 | | 48 | 5 | | 49 | 23 |
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| 50.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 16 | | diversityRatio | 0.3798449612403101 | | totalSentences | 129 | | uniqueOpeners | 49 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 88 | | matches | | 0 | "Of course he looked the" | | 1 | "Instead, she let her hand" |
| | ratio | 0.023 | |
| 60.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 88 | | matches | | 0 | "He looked the same." | | 1 | "Her name in his mouth" | | 2 | "It always had." | | 3 | "She should have closed the" | | 4 | "She should have turned the" | | 5 | "Her voice came out flat," | | 6 | "She’d practiced that." | | 7 | "She’d let her guard down" | | 8 | "He didn’t push, didn’t pressure," | | 9 | "He just asked, with that" | | 10 | "He shifted his weight onto" | | 11 | "She could hear it in" | | 12 | "He traded for them." | | 13 | "He owed favors and collected" | | 14 | "She stepped back." | | 15 | "He crossed the threshold like" | | 16 | "She closed the door and" | | 17 | "She was still in her" | | 18 | "She’d been planning to shower" | | 19 | "His fingers tightened on the" |
| | ratio | 0.398 | |
| 62.27% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 70 | | totalSentences | 88 | | matches | | 0 | "The brass of the third" | | 1 | "Rory stood frozen in the" | | 2 | "He looked the same." | | 3 | "The silver-headed cane rested against" | | 4 | "Her name in his mouth" | | 5 | "It always had." | | 6 | "She should have closed the" | | 7 | "She should have turned the" | | 8 | "That’s what a smart person" | | 9 | "That’s what a person who" | | 10 | "Her voice came out flat," | | 11 | "She’d practiced that." | | 12 | "The phone calls she’d ignored," | | 13 | "Lucien’s head tilted a fraction" | | 14 | "The movement was elegant and" | | 15 | "Rory’s jaw tightened." | | 16 | "She’d let her guard down" | | 17 | "He didn’t push, didn’t pressure," | | 18 | "He just asked, with that" | | 19 | "Ptolemy appeared from behind the" |
| | ratio | 0.795 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 88 | | matches | (empty) | | ratio | 0 | |
| 23.81% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 48 | | technicalSentenceCount | 8 | | matches | | 0 | "Same tailored charcoal suit, same platinum hair swept back from a widow’s peak that caught the dim light from the bulb above Eva’s number 42." | | 1 | "The phone calls she’d ignored, the texts she’d deleted without reading, the messages he’d sent through people who didn’t know they were running his errands—all …" | | 2 | "He crossed the threshold like he was crossing a border into hostile territory, his eyes scanning the cluttered space with the quick, methodical sweep of a man w…" | | 3 | "Research notes pinned to the wall above Eva’s desk, red string connecting names and dates and locations that looked like a conspiracy theorist’s fever dream." | | 4 | "She closed the door and turned the deadbolts one by one, the metal thunking into place with a finality that felt theatrical." | | 5 | "She’d been planning to shower and fall into bed, not stand in her best friend’s living room with the half-demon who’d broken her heart in three separate languag…" | | 6 | "Black leather, stitched with a dark thread that caught the light like the scales of something that lived deep in the Thames." | | 7 | "The knuckles of his right hand, visible above the glove, were bruised—fresh ones, purple and black, the kind that came from throwing a punch and hitting bone." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 14 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 89.39% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 9 | | fancyCount | 2 | | fancyTags | | 0 | "he continued (continue)" | | 1 | "he agreed (agree)" |
| | dialogueSentences | 33 | | tagDensity | 0.273 | | leniency | 0.545 | | rawRatio | 0.222 | | effectiveRatio | 0.121 | |