| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 17 | | adverbTagCount | 1 | | adverbTags | | 0 | "Her voice cracked slightly [slightly]" |
| | dialogueSentences | 35 | | tagDensity | 0.486 | | leniency | 0.971 | | rawRatio | 0.059 | | effectiveRatio | 0.057 | |
| 83.84% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 928 | | totalAiIsmAdverbs | 3 | | 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) | |
| 56.90% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 928 | | totalAiIsms | 8 | | found | | | highlights | | 0 | "thundered" | | 1 | "weight" | | 2 | "gleaming" | | 3 | "reminder" | | 4 | "dancing" | | 5 | "intensity" | | 6 | "otherworldly" | | 7 | "traced" |
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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 | 47 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 47 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 65 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 47 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 938 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 12 | | unquotedAttributions | 0 | | matches | (empty) | |
| 87.40% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 639 | | uniqueNames | 9 | | maxNameDensity | 1.25 | | worstName | "Aurora" | | maxWindowNameDensity | 2 | | worstWindowName | "Aurora" | | discoveredNames | | Lucien | 4 | | Moreau | 1 | | Eva | 3 | | London | 1 | | Marseille | 1 | | Aurora | 8 | | French | 1 | | Rory | 2 | | Ptolemy | 2 |
| | persons | | 0 | "Lucien" | | 1 | "Moreau" | | 2 | "Eva" | | 3 | "Aurora" | | 4 | "Rory" | | 5 | "Ptolemy" |
| | places | | 0 | "London" | | 1 | "Marseille" | | 2 | "French" |
| | globalScore | 0.874 | | windowScore | 1 | |
| 89.02% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 41 | | glossingSentenceCount | 1 | | matches | | 0 | "felt like coming home to a place she'd" |
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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 | 938 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 65 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 33 | | mean | 28.42 | | std | 15.36 | | cv | 0.54 | | sampleLengths | | 0 | 51 | | 1 | 27 | | 2 | 40 | | 3 | 20 | | 4 | 27 | | 5 | 9 | | 6 | 24 | | 7 | 29 | | 8 | 38 | | 9 | 19 | | 10 | 52 | | 11 | 27 | | 12 | 35 | | 13 | 3 | | 14 | 25 | | 15 | 48 | | 16 | 10 | | 17 | 24 | | 18 | 37 | | 19 | 31 | | 20 | 4 | | 21 | 38 | | 22 | 29 | | 23 | 58 | | 24 | 13 | | 25 | 39 | | 26 | 15 | | 27 | 26 | | 28 | 58 | | 29 | 4 | | 30 | 11 | | 31 | 49 | | 32 | 18 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 47 | | matches | (empty) | |
| 87.01% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 118 | | matches | | 0 | "wasn't looking" | | 1 | "was savoring" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 8 | | semicolonCount | 0 | | flaggedSentences | 5 | | totalSentences | 65 | | ratio | 0.077 | | matches | | 0 | "\"Bonsoir, ma chérie.\" His voice was exactly as she remembered – smooth as aged whiskey with that hint of Marseille still clinging to his consonants." | | 1 | "His mismatched eyes – one amber, one black – crinkled slightly at the corners." | | 2 | "Letting him in was dangerous – not because she feared him, but because she feared herself." | | 3 | "\"The cat remembers me, I see.\" Lucien's lips quirked as he moved past her, his cologne – sandalwood and something darker, more exotic – briefly overwhelming the curry smell." | | 4 | "The way he said her name – not Rory, never Rory, always the full syllables like he was savoring them – made her shiver." |
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| 89.38% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 633 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 33 | | adverbRatio | 0.052132701421800945 | | lyAdverbCount | 11 | | lyAdverbRatio | 0.017377567140600316 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 65 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 65 | | mean | 14.43 | | std | 8.73 | | cv | 0.605 | | sampleLengths | | 0 | 7 | | 1 | 19 | | 2 | 8 | | 3 | 17 | | 4 | 13 | | 5 | 14 | | 6 | 25 | | 7 | 15 | | 8 | 20 | | 9 | 14 | | 10 | 13 | | 11 | 4 | | 12 | 5 | | 13 | 13 | | 14 | 11 | | 15 | 17 | | 16 | 12 | | 17 | 2 | | 18 | 16 | | 19 | 7 | | 20 | 13 | | 21 | 19 | | 22 | 29 | | 23 | 18 | | 24 | 5 | | 25 | 15 | | 26 | 12 | | 27 | 15 | | 28 | 20 | | 29 | 3 | | 30 | 15 | | 31 | 10 | | 32 | 15 | | 33 | 24 | | 34 | 9 | | 35 | 3 | | 36 | 7 | | 37 | 12 | | 38 | 12 | | 39 | 6 | | 40 | 31 | | 41 | 11 | | 42 | 20 | | 43 | 4 | | 44 | 29 | | 45 | 9 | | 46 | 24 | | 47 | 5 | | 48 | 12 | | 49 | 46 |
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| 77.44% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 3 | | diversityRatio | 0.49230769230769234 | | totalSentences | 65 | | uniqueOpeners | 32 | |
| 75.76% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 1 | | totalSentences | 44 | | matches | | 0 | "Of course he'd track her" |
| | ratio | 0.023 | |
| 10.91% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 23 | | totalSentences | 44 | | matches | | 0 | "She should have known better" | | 1 | "Her heart thundered against her" | | 2 | "His voice was exactly as" | | 3 | "He leaned casually on his" | | 4 | "His mismatched eyes – one" | | 5 | "She did know better." | | 6 | "His gaze hadn't left her" | | 7 | "He shifted his weight, the" | | 8 | "She pushed the memory aside" | | 9 | "He surveyed the cramped space," | | 10 | "He turned to face her," | | 11 | "he repeated, testing the word" | | 12 | "He took a step closer," | | 13 | "Her voice cracked slightly" | | 14 | "He stopped, frustration flickering across" | | 15 | "He closed the distance between" | | 16 | "She pressed her palms against" | | 17 | "His free hand came up" | | 18 | "His breath ghosted across her" | | 19 | "She opened her eyes to" |
| | ratio | 0.523 | |
| 28.18% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 38 | | totalSentences | 44 | | matches | | 0 | "Aurora's fingers froze on the" | | 1 | "She should have known better" | | 2 | "Her heart thundered against her" | | 3 | "The door creaked open, releasing" | | 4 | "His voice was exactly as" | | 5 | "He leaned casually on his" | | 6 | "Aurora managed to keep her" | | 7 | "His mismatched eyes – one" | | 8 | "She did know better." | | 9 | "That was half the problem." | | 10 | "Aurora said, even though he" | | 11 | "His gaze hadn't left her" | | 12 | "He shifted his weight, the" | | 13 | "The last time they'd been" | | 14 | "She pushed the memory aside" | | 15 | "Ptolemy, Eva's tabby, took one" | | 16 | "Lucien's lips quirked as he" | | 17 | "He surveyed the cramped space," | | 18 | "Aurora closed the door but" | | 19 | "The flat suddenly felt too" |
| | ratio | 0.864 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 44 | | matches | (empty) | | ratio | 0 | |
| 49.69% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 23 | | technicalSentenceCount | 3 | | matches | | 0 | "He turned to face her, his expression softening into something that made her chest ache." | | 1 | "She opened her eyes to find him watching her with an intensity that made her breath catch." | | 2 | "His mismatched gaze held centuries of power, of otherworldly knowledge, and yet all she saw was the man who'd spent three weeks trying to find her favorite coff…" |
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| 36.76% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 17 | | uselessAdditionCount | 3 | | matches | | 0 | "Aurora managed, though her fingers curled tighter around the doorframe" | | 1 | "He stopped, frustration flickering across his usually controlled features" | | 2 | "free hand came up, thumb brushing her cheekbone" |
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| 35.71% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 5 | | fancyCount | 4 | | fancyTags | | 0 | "he repeated (repeat)" | | 1 | "she admitted (admit)" | | 2 | "She pressed (press)" | | 3 | "she whispered (whisper)" |
| | dialogueSentences | 35 | | tagDensity | 0.143 | | leniency | 0.286 | | rawRatio | 0.8 | | effectiveRatio | 0.229 | |