| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | | dialogueSentences | 170 | | tagDensity | 0.112 | | leniency | 0.224 | | rawRatio | 0.053 | | effectiveRatio | 0.012 | |
| 85.58% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2080 | | totalAiIsmAdverbs | 6 | | found | | | highlights | | 0 | "carefully" | | 1 | "gently" | | 2 | "suddenly" | | 3 | "very" | | 4 | "slowly" |
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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) | |
| 78.37% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2080 | | totalAiIsms | 9 | | found | | | highlights | | 0 | "flicker" | | 1 | "traced" | | 2 | "tenderness" | | 3 | "pulse" | | 4 | "familiar" | | 5 | "silence" | | 6 | "stark" | | 7 | "warmth" | | 8 | "echoed" |
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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 | 138 | | matches | (empty) | |
| 91.10% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 2 | | hedgeCount | 3 | | narrationSentences | 138 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 289 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 48 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 2075 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 50 | | unquotedAttributions | 0 | | matches | (empty) | |
| 79.11% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 44 | | wordCount | 1199 | | uniqueNames | 7 | | maxNameDensity | 1.42 | | worstName | "Lucien" | | maxWindowNameDensity | 2 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 17 | | Moreau | 1 | | Rory | 17 | | Ptolemy | 6 | | Eva | 1 | | London | 1 | | Malphora | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Rory" | | 3 | "Ptolemy" | | 4 | "Eva" | | 5 | "Malphora" |
| | places | | | globalScore | 0.791 | | windowScore | 1 | |
| 93.18% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 88 | | glossingSentenceCount | 2 | | matches | | 0 | "not quite" | | 1 | "looked like he’d been delivered from a di" |
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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 | 2075 | | matches | (empty) | |
| 97.46% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 6 | | totalSentences | 289 | | matches | | 0 | "hated that she" | | 1 | "say that she trust, that the" | | 2 | "hated that the" | | 3 | "Hated that she" | | 4 | "letting that ease" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 202 | | mean | 10.27 | | std | 12.14 | | cv | 1.182 | | sampleLengths | | 0 | 6 | | 1 | 57 | | 2 | 19 | | 3 | 3 | | 4 | 13 | | 5 | 6 | | 6 | 9 | | 7 | 6 | | 8 | 20 | | 9 | 11 | | 10 | 8 | | 11 | 27 | | 12 | 39 | | 13 | 4 | | 14 | 1 | | 15 | 3 | | 16 | 1 | | 17 | 7 | | 18 | 5 | | 19 | 17 | | 20 | 13 | | 21 | 24 | | 22 | 29 | | 23 | 4 | | 24 | 2 | | 25 | 5 | | 26 | 4 | | 27 | 3 | | 28 | 2 | | 29 | 55 | | 30 | 5 | | 31 | 5 | | 32 | 4 | | 33 | 5 | | 34 | 7 | | 35 | 47 | | 36 | 4 | | 37 | 5 | | 38 | 1 | | 39 | 3 | | 40 | 6 | | 41 | 1 | | 42 | 14 | | 43 | 9 | | 44 | 1 | | 45 | 1 | | 46 | 4 | | 47 | 8 | | 48 | 8 | | 49 | 11 |
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| 97.64% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 3 | | totalSentences | 138 | | matches | | 0 | "been delivered" | | 1 | "been printed" | | 2 | "been settled" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 239 | | matches | (empty) | |
| 93.43% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 2 | | flaggedSentences | 5 | | totalSentences | 289 | | ratio | 0.017 | | matches | | 0 | "Lucien set his ivory-handled cane against the jamb—not pushing, not quite." | | 1 | "Not much—a crack, no wider than a hairline—but enough to show the strain beneath it." | | 2 | "It was such a familiar gesture that Rory felt something shift inside her—an old, tender hinge giving way." | | 3 | "The moment was brief, but it held all the things they’d failed to say: the apology she had never asked for, the one he’d never offered; the attraction that had outlasted the hurt; the terrible ease of being near him and the price of letting that ease matter." | | 4 | "For the first time in months, she and Lucien were under the same roof—and neither of them could pretend it meant nothing." |
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| 97.24% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1205 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 52 | | adverbRatio | 0.043153526970954356 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.009128630705394191 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 289 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 289 | | mean | 7.18 | | std | 6.04 | | cv | 0.841 | | sampleLengths | | 0 | 6 | | 1 | 20 | | 2 | 33 | | 3 | 2 | | 4 | 2 | | 5 | 19 | | 6 | 3 | | 7 | 6 | | 8 | 7 | | 9 | 6 | | 10 | 9 | | 11 | 6 | | 12 | 11 | | 13 | 9 | | 14 | 3 | | 15 | 8 | | 16 | 8 | | 17 | 5 | | 18 | 7 | | 19 | 15 | | 20 | 8 | | 21 | 12 | | 22 | 19 | | 23 | 4 | | 24 | 1 | | 25 | 3 | | 26 | 1 | | 27 | 7 | | 28 | 5 | | 29 | 17 | | 30 | 5 | | 31 | 2 | | 32 | 6 | | 33 | 14 | | 34 | 10 | | 35 | 5 | | 36 | 11 | | 37 | 5 | | 38 | 8 | | 39 | 4 | | 40 | 2 | | 41 | 5 | | 42 | 4 | | 43 | 3 | | 44 | 2 | | 45 | 10 | | 46 | 8 | | 47 | 25 | | 48 | 12 | | 49 | 5 |
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| 45.85% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 12 | | diversityRatio | 0.2664359861591695 | | totalSentences | 289 | | uniqueOpeners | 77 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 5 | | totalSentences | 114 | | matches | | 0 | "Then Ptolemy pushed between her" | | 1 | "Instead she looked past him" | | 2 | "Once, he’d traced the curve" | | 3 | "Instead, he reached into his" | | 4 | "Just a question about the" |
| | ratio | 0.044 | |
| 62.11% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 45 | | totalSentences | 114 | | matches | | 0 | "She saw only his face:" | | 1 | "His gaze lifted to hers." | | 2 | "It vanished before she could" | | 3 | "She unhooked the chain and" | | 4 | "He moved carefully, favoring one" | | 5 | "She hated that she noticed." | | 6 | "She hated more that he" | | 7 | "She closed the door and" | | 8 | "He looked like he’d been" | | 9 | "He reached into his coat." | | 10 | "His hand stopped." | | 11 | "His eyes sharpened at the" | | 12 | "He lowered his hand." | | 13 | "She stared at him." | | 14 | "She glanced to the door," | | 15 | "They looked suddenly small and" | | 16 | "His jaw flexed." | | 17 | "She’d asked what he meant." | | 18 | "He’d answered with a warning" | | 19 | "She let out a short" |
| | ratio | 0.395 | |
| 43.33% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 95 | | totalSentences | 114 | | matches | | 0 | "The door opened on Lucien" | | 1 | "She saw only his face:" | | 2 | "Lucien glanced down at the" | | 3 | "Rory began to close the" | | 4 | "Lucien set his ivory-handled cane" | | 5 | "The door stopped with a" | | 6 | "His gaze lifted to hers." | | 7 | "Whatever answer he’d prepared, he" | | 8 | "The cane remained between door" | | 9 | "Rory could have slammed the" | | 10 | "A flicker crossed his face." | | 11 | "It vanished before she could" | | 12 | "She unhooked the chain and" | | 13 | "Lucien stepped over the threshold." | | 14 | "He moved carefully, favoring one" | | 15 | "She hated that she noticed." | | 16 | "She hated more that he" | | 17 | "She closed the door and" | | 18 | "The little ritual steadied her:" | | 19 | "He looked like he’d been" |
| | ratio | 0.833 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 114 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 42 | | technicalSentenceCount | 2 | | matches | | 0 | "Behind her, Lucien stood amid Eva’s impossible clutter, surrounded by stacked books and scrolls, loose research notes, mugs that had lost the argument with grav…" | | 1 | "The moment was brief, but it held all the things they’d failed to say: the apology she had never asked for, the one he’d never offered; the attraction that had …" |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 19 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 15 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 170 | | tagDensity | 0.088 | | leniency | 0.176 | | rawRatio | 0.067 | | effectiveRatio | 0.012 | |