| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 16 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 44 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.063 | | effectiveRatio | 0.045 | |
| 96.03% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1258 | | 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) | |
| 52.31% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1258 | | totalAiIsms | 12 | | found | | | highlights | | 0 | "flicked" | | 1 | "measured" | | 2 | "tracing" | | 3 | "familiar" | | 4 | "flickered" | | 5 | "could feel" | | 6 | "weight" | | 7 | "stomach" | | 8 | "silence" | | 9 | "perfect" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "let out a breath" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 109 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 0 | | narrationSentences | 109 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 135 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1252 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 21 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 24 | | wordCount | 930 | | uniqueNames | 15 | | maxNameDensity | 0.54 | | worstName | "Lucien" | | maxWindowNameDensity | 1 | | worstWindowName | "Lucien" | | discoveredNames | | Eva | 2 | | British | 1 | | Library | 1 | | Silas | 1 | | Didn | 1 | | Moreau | 2 | | Lucien | 5 | | Oxfords | 1 | | Brighton | 1 | | Pier | 1 | | Evan | 1 | | London | 1 | | Wapping | 1 | | Right | 1 | | Ptolemy | 4 |
| | persons | | 0 | "Eva" | | 1 | "Silas" | | 2 | "Moreau" | | 3 | "Lucien" | | 4 | "Evan" | | 5 | "Ptolemy" |
| | places | | 0 | "British" | | 1 | "Library" | | 2 | "Brighton" | | 3 | "London" | | 4 | "Wapping" |
| | globalScore | 1 | | windowScore | 1 | |
| 0.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 57 | | glossingSentenceCount | 4 | | matches | | 0 | "felt like a hand tracing a familiar map" | | 1 | "quite cover" | | 2 | "tasted like six months of stored-up anger" | | 3 | "smelled like roasted garlic and rosemary" |
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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 | 1252 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 135 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 63 | | mean | 19.87 | | std | 17.86 | | cv | 0.899 | | sampleLengths | | 0 | 18 | | 1 | 59 | | 2 | 31 | | 3 | 13 | | 4 | 6 | | 5 | 19 | | 6 | 20 | | 7 | 17 | | 8 | 19 | | 9 | 22 | | 10 | 8 | | 11 | 69 | | 12 | 21 | | 13 | 4 | | 14 | 6 | | 15 | 13 | | 16 | 20 | | 17 | 99 | | 18 | 25 | | 19 | 11 | | 20 | 29 | | 21 | 1 | | 22 | 5 | | 23 | 9 | | 24 | 56 | | 25 | 6 | | 26 | 11 | | 27 | 13 | | 28 | 30 | | 29 | 2 | | 30 | 20 | | 31 | 11 | | 32 | 3 | | 33 | 27 | | 34 | 6 | | 35 | 24 | | 36 | 7 | | 37 | 30 | | 38 | 13 | | 39 | 43 | | 40 | 9 | | 41 | 23 | | 42 | 13 | | 43 | 57 | | 44 | 3 | | 45 | 9 | | 46 | 30 | | 47 | 9 | | 48 | 5 | | 49 | 23 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 109 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 163 | | matches | | 0 | "wasn’t expecting" | | 1 | "was leaking" |
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| 37.04% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 6 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 135 | | ratio | 0.037 | | matches | | 0 | "His eyes—one amber, one black—moved across her face in a slow sweep that felt like a hand tracing a familiar map." | | 1 | "His gaze landed on the corkboard above her desk—pinned with string maps, newspaper clippings, a photo of her and Eva at Brighton Pier." | | 2 | "She’d watched him do it a dozen times during the weeks they’d worked together—before she’d understood what it cost him to get involved." | | 3 | "She looked at him—at the careful way he stood, shoulders squared, the cane held at rest but ready to draw the blade hidden inside." | | 4 | "He let out a sound—half laugh, half exhale of relief." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 941 | | adjectiveStacks | 1 | | stackExamples | | 0 | "single, perfect white bloom." |
| | adverbCount | 29 | | adverbRatio | 0.030818278427205102 | | lyAdverbCount | 2 | | lyAdverbRatio | 0.0021253985122210413 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 135 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 135 | | mean | 9.27 | | std | 7.37 | | cv | 0.795 | | sampleLengths | | 0 | 18 | | 1 | 16 | | 2 | 11 | | 3 | 4 | | 4 | 12 | | 5 | 16 | | 6 | 20 | | 7 | 8 | | 8 | 3 | | 9 | 13 | | 10 | 6 | | 11 | 15 | | 12 | 4 | | 13 | 10 | | 14 | 4 | | 15 | 6 | | 16 | 10 | | 17 | 7 | | 18 | 9 | | 19 | 10 | | 20 | 4 | | 21 | 5 | | 22 | 3 | | 23 | 10 | | 24 | 4 | | 25 | 4 | | 26 | 34 | | 27 | 11 | | 28 | 14 | | 29 | 10 | | 30 | 21 | | 31 | 4 | | 32 | 6 | | 33 | 5 | | 34 | 4 | | 35 | 4 | | 36 | 3 | | 37 | 13 | | 38 | 4 | | 39 | 4 | | 40 | 13 | | 41 | 12 | | 42 | 23 | | 43 | 6 | | 44 | 2 | | 45 | 5 | | 46 | 34 | | 47 | 7 | | 48 | 8 | | 49 | 10 |
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| 47.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.34074074074074073 | | totalSentences | 135 | | uniqueOpeners | 46 | |
| 36.63% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 91 | | matches | | | ratio | 0.011 | |
| 26.59% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 44 | | totalSentences | 91 | | matches | | 0 | "She wasn’t expecting anyone." | | 1 | "She set down the menu" | | 2 | "Her hand stopped on the" | | 3 | "His voice carried the same" | | 4 | "She pressed her forehead against" | | 5 | "She didn’t open it wider" | | 6 | "He did calculations." | | 7 | "She unhooked the chain." | | 8 | "He stood in the dim" | | 9 | "His blond hair was still" | | 10 | "His eyes—one amber, one black—moved" | | 11 | "She stepped aside." | | 12 | "He didn’t look down." | | 13 | "He set the paper bag" | | 14 | "His gaze landed on the" | | 15 | "She hadn’t seen him since" | | 16 | "She’d left a thank-you note" | | 17 | "He’d sent back a single" | | 18 | "She closed the door, but" | | 19 | "She crossed her arms." |
| | ratio | 0.484 | |
| 58.90% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 73 | | totalSentences | 91 | | matches | | 0 | "The knock came at half" | | 1 | "Rory looked up from the" | | 2 | "Ptolemy, sprawled across her open" | | 3 | "She wasn’t expecting anyone." | | 4 | "She set down the menu" | | 5 | "The deadbolt scraped as she" | | 6 | "The chain rattled." | | 7 | "Her hand stopped on the" | | 8 | "His voice carried the same" | | 9 | "She pressed her forehead against" | | 10 | "The wood was cool." | | 11 | "The chain bit into her" | | 12 | "She didn’t open it wider" | | 13 | "Lucien Moreau didn’t do coincidence." | | 14 | "He did calculations." | | 15 | "Every footstep measured, every question" | | 16 | "She unhooked the chain." | | 17 | "He stood in the dim" | | 18 | "His blond hair was still" | | 19 | "The suit was charcoal, not" |
| | ratio | 0.802 | |
| 100.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 3 | | totalSentences | 91 | | matches | | 0 | "Before she’d fled to London." | | 1 | "Before Lucien had pulled her" | | 2 | "Before he’d told her that" |
| | ratio | 0.033 | |
| 84.94% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 37 | | technicalSentenceCount | 3 | | matches | | 0 | "He stood in the dim bulb light of the hallway, one hand resting on the ivory head of his cane, the other holding a paper bag that smelled of good bread and some…" | | 1 | "His eyes—one amber, one black—moved across her face in a slow sweep that felt like a hand tracing a familiar map." | | 2 | "And now he was in her kitchen, smelling of rain and sandalwood, telling her that someone had assembled a dossier on her life." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 16 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 10 | | fancyCount | 0 | | fancyTags | (empty) | | dialogueSentences | 44 | | tagDensity | 0.227 | | leniency | 0.455 | | rawRatio | 0 | | effectiveRatio | 0 | |