| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 11 | | adverbTagCount | 1 | | adverbTags | | 0 | "she asked quietly [quietly]" |
| | dialogueSentences | 54 | | tagDensity | 0.204 | | leniency | 0.407 | | rawRatio | 0.091 | | effectiveRatio | 0.037 | |
| 79.69% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1477 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "really" | | 1 | "slightly" | | 2 | "perfectly" | | 3 | "carefully" | | 4 | "suddenly" |
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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) | |
| 55.99% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1477 | | totalAiIsms | 13 | | found | | | highlights | | 0 | "silence" | | 1 | "intensity" | | 2 | "pulse" | | 3 | "flicked" | | 4 | "charm" | | 5 | "stomach" | | 6 | "roaring" | | 7 | "charged" | | 8 | "rhythmic" | | 9 | "tension" | | 10 | "raced" | | 11 | "eyebrow" |
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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 | 114 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 114 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 156 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 6 | | markdownWords | 17 | | totalWords | 1467 | | ratio | 0.012 | | matches | | 0 | "alive" | | 1 | "The Malphora bloodline holds the key. Find her before they do." | | 2 | "Malphora." | | 3 | "are" | | 4 | "Too late." | | 5 | "me" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 66.67% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 45 | | wordCount | 1078 | | uniqueNames | 12 | | maxNameDensity | 1.48 | | worstName | "Rory" | | maxWindowNameDensity | 3 | | worstWindowName | "Rory" | | discoveredNames | | Rory | 16 | | Eva | 1 | | Silas | 1 | | Moreau | 1 | | Black | 1 | | Dog | 1 | | Malphora | 3 | | London | 1 | | Lucien | 15 | | Aurora | 1 | | Carter | 1 | | Ptolemy | 3 |
| | persons | | 0 | "Rory" | | 1 | "Eva" | | 2 | "Silas" | | 3 | "Moreau" | | 4 | "Lucien" | | 5 | "Aurora" | | 6 | "Carter" | | 7 | "Ptolemy" |
| | places | | | globalScore | 0.758 | | windowScore | 0.667 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 78 | | glossingSentenceCount | 1 | | matches | | 0 | "something like gunpowder and old books—filli" |
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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 | 1467 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 156 | | matches | | 0 | "chose that moment" | | 1 | "chose that moment" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 61 | | mean | 24.05 | | std | 14.74 | | cv | 0.613 | | sampleLengths | | 0 | 63 | | 1 | 16 | | 2 | 54 | | 3 | 20 | | 4 | 46 | | 5 | 45 | | 6 | 23 | | 7 | 44 | | 8 | 5 | | 9 | 11 | | 10 | 35 | | 11 | 13 | | 12 | 29 | | 13 | 41 | | 14 | 9 | | 15 | 13 | | 16 | 19 | | 17 | 13 | | 18 | 23 | | 19 | 13 | | 20 | 9 | | 21 | 53 | | 22 | 5 | | 23 | 16 | | 24 | 28 | | 25 | 34 | | 26 | 35 | | 27 | 11 | | 28 | 33 | | 29 | 16 | | 30 | 8 | | 31 | 29 | | 32 | 41 | | 33 | 58 | | 34 | 15 | | 35 | 13 | | 36 | 16 | | 37 | 19 | | 38 | 19 | | 39 | 17 | | 40 | 11 | | 41 | 11 | | 42 | 8 | | 43 | 18 | | 44 | 36 | | 45 | 6 | | 46 | 29 | | 47 | 19 | | 48 | 29 | | 49 | 41 |
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| 99.11% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 114 | | matches | | 0 | "were fixed" | | 1 | "was charged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 3 | | totalVerbs | 210 | | matches | | 0 | "was wiping" | | 1 | "was looking" | | 2 | "was catching" |
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| 14.65% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 11 | | semicolonCount | 0 | | flaggedSentences | 7 | | totalSentences | 156 | | ratio | 0.045 | | matches | | 0 | "The flat was a mess—takeout containers littered the coffee table, a half-empty bottle of wine sat open on the kitchen counter, and her notes on the latest supernatural anomaly were spread across the floor like confetti." | | 1 | "His heterochromatic eyes—one amber, one black—were fixed on the door with unsettling intensity." | | 2 | "But the way he was looking at her—like she was a puzzle he’d been trying to solve for years—rooted her in place." | | 3 | "Lucien stepped over the threshold, the scent of bergamot and something darker—something like gunpowder and old books—filling the space between them." | | 4 | "There was something in his gaze—something raw, something he usually kept locked away—that made her stomach twist." | | 5 | "The alias, the mirror, the deaths—it all felt too deliberate, too personal." | | 6 | "He was a man who controlled everything—his business, his emotions, his world." |
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| 93.33% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1092 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 52 | | adverbRatio | 0.047619047619047616 | | lyAdverbCount | 15 | | lyAdverbRatio | 0.013736263736263736 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 156 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 156 | | mean | 9.4 | | std | 6.5 | | cv | 0.691 | | sampleLengths | | 0 | 17 | | 1 | 11 | | 2 | 5 | | 3 | 12 | | 4 | 18 | | 5 | 2 | | 6 | 14 | | 7 | 12 | | 8 | 36 | | 9 | 6 | | 10 | 17 | | 11 | 3 | | 12 | 18 | | 13 | 15 | | 14 | 13 | | 15 | 3 | | 16 | 7 | | 17 | 30 | | 18 | 5 | | 19 | 14 | | 20 | 9 | | 21 | 3 | | 22 | 5 | | 23 | 28 | | 24 | 8 | | 25 | 4 | | 26 | 1 | | 27 | 6 | | 28 | 5 | | 29 | 8 | | 30 | 22 | | 31 | 5 | | 32 | 9 | | 33 | 4 | | 34 | 14 | | 35 | 12 | | 36 | 3 | | 37 | 21 | | 38 | 15 | | 39 | 5 | | 40 | 9 | | 41 | 3 | | 42 | 10 | | 43 | 11 | | 44 | 8 | | 45 | 9 | | 46 | 4 | | 47 | 4 | | 48 | 19 | | 49 | 13 |
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| 51.92% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 9 | | diversityRatio | 0.34615384615384615 | | totalSentences | 156 | | uniqueOpeners | 54 | |
| 92.59% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 108 | | matches | | 0 | "Too deliberate to be Eva," | | 1 | "Too patient to be Silas," | | 2 | "Instead, she grabbed her jacket" |
| | ratio | 0.028 | |
| 64.44% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 42 | | totalSentences | 108 | | matches | | 0 | "She froze, the dishcloth still" | | 1 | "She didn’t have time for" | | 2 | "She padded to the door," | | 3 | "Her breath hitched." | | 4 | "He held his ivory-handled cane" | | 5 | "His heterochromatic eyes—one amber, one" | | 6 | "She hadn’t seen him in" | | 7 | "She unlatched the first deadbolt," | | 8 | "He never did, not really." | | 9 | "he said, voice low, accented" | | 10 | "She should’ve slammed the door" | | 11 | "He tilted his head slightly," | | 12 | "She stepped back, gesturing him" | | 13 | "He took in the flat" | | 14 | "she shot back" | | 15 | "His lips quirked." | | 16 | "She barked a laugh." | | 17 | "he said, stepping closer" | | 18 | "He sighed, running a hand" | | 19 | "His voice dropped, the amber" |
| | ratio | 0.389 | |
| 61.85% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 86 | | totalSentences | 108 | | matches | | 0 | "The first knock came just" | | 1 | "She froze, the dishcloth still" | | 2 | "Ptolemy, the tabby, lifted his" | | 3 | "Rory exhaled through her nose" | | 4 | "The flat was a mess—takeout" | | 5 | "She didn’t have time for" | | 6 | "She padded to the door," | | 7 | "Her breath hitched." | | 8 | "Lucien Moreau stood in the" | | 9 | "He held his ivory-handled cane" | | 10 | "His heterochromatic eyes—one amber, one" | | 11 | "Rory’s pulse spiked." | | 12 | "She hadn’t seen him in" | | 13 | "She unlatched the first deadbolt," | | 14 | "The door swung open before" | | 15 | "Lucien didn’t smile." | | 16 | "He never did, not really." | | 17 | "he said, voice low, accented" | | 18 | "Rory crossed her arms." | | 19 | "A corner of his mouth" |
| | ratio | 0.796 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 108 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "She’d spent years running from her past, from the people who knew her as Aurora Carter, as Malphora." | | 1 | "He was a man who controlled everything—his business, his emotions, his world." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 11 | | uselessAdditionCount | 3 | | matches | | 0 | "he said, voice low, accented" | | 1 | "His voice dropped, the amber eye softening just a fraction" | | 2 | "He trailed, his amber eye flickering with something she couldn’t name" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 54 | | tagDensity | 0.093 | | leniency | 0.185 | | rawRatio | 0 | | effectiveRatio | 0 | |