| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 19 | | adverbTagCount | 1 | | adverbTags | | 0 | "Lucien said softly [softly]" |
| | dialogueSentences | 45 | | tagDensity | 0.422 | | leniency | 0.844 | | rawRatio | 0.053 | | effectiveRatio | 0.044 | |
| 81.46% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1079 | | totalAiIsmAdverbs | 4 | | 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) | |
| 81.46% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1079 | | totalAiIsms | 4 | | found | | | highlights | | 0 | "weight" | | 1 | "silence" | | 2 | "anticipation" |
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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 | 1 | | narrationSentences | 60 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 60 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 84 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 36 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1083 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 19 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 18 | | wordCount | 708 | | uniqueNames | 9 | | maxNameDensity | 0.42 | | worstName | "Aurora" | | maxWindowNameDensity | 1 | | worstWindowName | "Aurora" | | discoveredNames | | Aurora | 3 | | Eva | 3 | | Ptolemy | 2 | | Lucien | 3 | | London | 2 | | Brick | 1 | | Lane | 1 | | Quiet | 1 | | Marseille | 2 |
| | persons | | 0 | "Aurora" | | 1 | "Eva" | | 2 | "Ptolemy" | | 3 | "Lucien" |
| | places | | 0 | "London" | | 1 | "Brick" | | 2 | "Lane" | | 3 | "Marseille" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 35 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.923 | | wordCount | 1083 | | matches | | 0 | "not for her, she'd told herself a hundred times since, but for the witnesses, to sell the lie" |
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| 87.30% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 84 | | matches | | 0 | "chosen that word" | | 1 | "hated that she" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 46 | | mean | 23.54 | | std | 21.07 | | cv | 0.895 | | sampleLengths | | 0 | 36 | | 1 | 22 | | 2 | 2 | | 3 | 7 | | 4 | 56 | | 5 | 6 | | 6 | 35 | | 7 | 8 | | 8 | 35 | | 9 | 23 | | 10 | 106 | | 11 | 15 | | 12 | 7 | | 13 | 50 | | 14 | 6 | | 15 | 3 | | 16 | 19 | | 17 | 28 | | 18 | 2 | | 19 | 3 | | 20 | 12 | | 21 | 33 | | 22 | 37 | | 23 | 33 | | 24 | 52 | | 25 | 33 | | 26 | 7 | | 27 | 4 | | 28 | 58 | | 29 | 35 | | 30 | 50 | | 31 | 19 | | 32 | 13 | | 33 | 8 | | 34 | 2 | | 35 | 58 | | 36 | 6 | | 37 | 1 | | 38 | 14 | | 39 | 8 | | 40 | 24 | | 41 | 24 | | 42 | 8 | | 43 | 41 | | 44 | 29 | | 45 | 5 |
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| 99.42% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 60 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 124 | | matches | (empty) | |
| 40.82% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 84 | | ratio | 0.036 | | matches | | 0 | "That was the maddening thing about him — he simply waited, one amber eye and one black one fixed on her, until the world rearranged itself to his liking." | | 1 | "The way he'd kissed her on the gangway — not for her, she'd told herself a hundred times since, but for the witnesses, to sell the lie that they were lovers fleeing rather than thieves running." | | 2 | "He came in the way he came into everywhere — as though the room had been arranged in anticipation of him." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 705 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 24 | | adverbRatio | 0.03404255319148936 | | lyAdverbCount | 4 | | lyAdverbRatio | 0.005673758865248227 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 84 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 84 | | mean | 12.89 | | std | 10.23 | | cv | 0.793 | | sampleLengths | | 0 | 36 | | 1 | 22 | | 2 | 2 | | 3 | 7 | | 4 | 21 | | 5 | 3 | | 6 | 3 | | 7 | 29 | | 8 | 6 | | 9 | 10 | | 10 | 4 | | 11 | 21 | | 12 | 5 | | 13 | 3 | | 14 | 18 | | 15 | 17 | | 16 | 4 | | 17 | 19 | | 18 | 3 | | 19 | 6 | | 20 | 1 | | 21 | 31 | | 22 | 36 | | 23 | 29 | | 24 | 2 | | 25 | 2 | | 26 | 11 | | 27 | 7 | | 28 | 21 | | 29 | 29 | | 30 | 6 | | 31 | 3 | | 32 | 15 | | 33 | 4 | | 34 | 7 | | 35 | 21 | | 36 | 2 | | 37 | 3 | | 38 | 7 | | 39 | 5 | | 40 | 23 | | 41 | 10 | | 42 | 4 | | 43 | 25 | | 44 | 8 | | 45 | 11 | | 46 | 22 | | 47 | 28 | | 48 | 24 | | 49 | 15 |
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| 61.51% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.44047619047619047 | | totalSentences | 84 | | uniqueOpeners | 37 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 3 | | totalSentences | 49 | | matches | | 0 | "Instead she got a charcoal" | | 1 | "Then six weeks of silence" | | 2 | "Instead she stayed exactly where" |
| | ratio | 0.061 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 29 | | totalSentences | 49 | | matches | | 0 | "She moved to shut the" | | 1 | "He didn't push." | | 2 | "He never pushed." | | 3 | "She leaned harder" | | 4 | "He tilted his head" | | 5 | "Her jaw tightened." | | 6 | "He'd chosen that word on" | | 7 | "She'd believed her own version" | | 8 | "she said, and stepped back" | | 9 | "He came in the way" | | 10 | "His gaze moved across Eva's" | | 11 | "He set the cane against" | | 12 | "She folded her arms, hiding" | | 13 | "She held his stare" | | 14 | "He reached into his breast" | | 15 | "He laid it on the" | | 16 | "His accent thickened, the way" | | 17 | "She turned away, busied her" | | 18 | "she said to the window" | | 19 | "She watched her own reflection" |
| | ratio | 0.592 | |
| 11.02% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 44 | | totalSentences | 49 | | matches | | 0 | "The third deadbolt gave way" | | 1 | "She moved to shut the" | | 2 | "Lucien set the tip of" | | 3 | "He didn't push." | | 4 | "He never pushed." | | 5 | "That was the maddening thing" | | 6 | "She leaned harder" | | 7 | "The door didn't budge." | | 8 | "He tilted his head" | | 9 | "Ptolemy appeared at Aurora's ankles," | | 10 | "Her jaw tightened." | | 11 | "He'd chosen that word on" | | 12 | "The harbour at four in" | | 13 | "The way he'd kissed her" | | 14 | "She'd believed her own version" | | 15 | "she said, and stepped back" | | 16 | "He came in the way" | | 17 | "His gaze moved across Eva's" | | 18 | "He set the cane against" | | 19 | "The question landed somewhere under" |
| | ratio | 0.898 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 3 | | matches | | 0 | "Instead she got a charcoal suit and a smile that had cost her three sleepless nights the last time she'd seen it." | | 1 | "She folded her arms, hiding the small crescent scar on the left, the old childhood thing he had no business remembering." | | 2 | "He smelled of cedar and cold air and something underneath it, scorched, the thing in him that wasn't human." |
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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 | 9 | | fancyCount | 1 | | fancyTags | | | dialogueSentences | 45 | | tagDensity | 0.2 | | leniency | 0.4 | | rawRatio | 0.111 | | effectiveRatio | 0.044 | |