| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 44 | | adverbTagCount | 1 | | adverbTags | | 0 | "The smile slid back [back]" |
| | dialogueSentences | 96 | | tagDensity | 0.458 | | leniency | 0.917 | | rawRatio | 0.023 | | effectiveRatio | 0.021 | |
| 100.00% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 2338 | | totalAiIsmAdverbs | 0 | | found | (empty) | | highlights | (empty) | |
| 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) | |
| 50.81% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 2338 | | totalAiIsms | 23 | | found | | 0 | | | 1 | | | 2 | | | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | | | 13 | | | 14 | | | 15 | | | 16 | | | 17 | | | 18 | | | 19 | |
| | highlights | | 0 | "mechanical" | | 1 | "stark" | | 2 | "unsettled" | | 3 | "trembled" | | 4 | "vibrated" | | 5 | "silence" | | 6 | "flicked" | | 7 | "traced" | | 8 | "charged" | | 9 | "weight" | | 10 | "velvet" | | 11 | "echoed" | | 12 | "whisper" | | 13 | "pulse" | | 14 | "stomach" | | 15 | "calculating" | | 16 | "pulsed" | | 17 | "footsteps" | | 18 | "silk" | | 19 | "flickered" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 1 | | narrationSentences | 222 | | matches | | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 1 | | narrationSentences | 222 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 271 | | gibberishSentences | 1 | | adjustedGibberishSentences | 1 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0.004 | | matches | | 0 | "\"Better.\" He removed his coat,袖口 frayed where the demon mark had burned through." |
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| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 14 | | markdownWords | 17 | | totalWords | 2333 | | ratio | 0.007 | | matches | | 0 | "Used" | | 1 | "ma lionne." | | 2 | "heterochromia" | | 3 | "ma lionne" | | 4 | "Goetia" | | 5 | "ally" | | 6 | "human" | | 7 | "what" | | 8 | "Cardiff" | | 9 | "meant" | | 10 | "you’re" | | 11 | "non" | | 12 | "ma lionne." | | 13 | "I’ll" |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 38 | | unquotedAttributions | 1 | | matches | | 0 | "Used to, she corrected." |
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| 50.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 92 | | wordCount | 1626 | | uniqueNames | 30 | | maxNameDensity | 1.66 | | worstName | "Luc" | | maxWindowNameDensity | 3.5 | | worstWindowName | "Luc" | | discoveredNames | | Eva | 4 | | Lucien | 2 | | Moreau | 2 | | East | 1 | | London | 1 | | Silas | 7 | | Pakistani | 1 | | Luc | 27 | | Avaros | 2 | | Enochian | 1 | | Cardiff | 2 | | Gone | 1 | | Rory | 15 | | Avoided | 1 | | Brendan | 1 | | Carter | 1 | | Ptolemy | 7 | | French | 1 | | Cuban | 1 | | Rothgar | 2 | | Irish | 1 | | Bitter | 1 | | Evan | 2 | | Six | 2 | | Notre | 1 | | Dame | 1 | | Brick | 1 | | Lane | 1 | | Paris | 1 | | Lucy | 1 |
| | persons | | 0 | "Eva" | | 1 | "Lucien" | | 2 | "Moreau" | | 3 | "Silas" | | 4 | "Luc" | | 5 | "Rory" | | 6 | "Brendan" | | 7 | "Carter" | | 8 | "Ptolemy" | | 9 | "French" | | 10 | "Irish" | | 11 | "Evan" | | 12 | "Lucy" |
| | places | | 0 | "East" | | 1 | "London" | | 2 | "Avaros" | | 3 | "Cardiff" | | 4 | "Notre" | | 5 | "Brick" | | 6 | "Lane" | | 7 | "Paris" |
| | globalScore | 0.67 | | windowScore | 0.5 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 139 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 2333 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 271 | | matches | | 0 | "killed that voicemail" | | 1 | "used that trick" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 81 | | mean | 28.8 | | std | 15.3 | | cv | 0.531 | | sampleLengths | | 0 | 58 | | 1 | 64 | | 2 | 11 | | 3 | 50 | | 4 | 39 | | 5 | 36 | | 6 | 3 | | 7 | 51 | | 8 | 39 | | 9 | 11 | | 10 | 37 | | 11 | 61 | | 12 | 42 | | 13 | 23 | | 14 | 12 | | 15 | 41 | | 16 | 23 | | 17 | 44 | | 18 | 49 | | 19 | 17 | | 20 | 40 | | 21 | 39 | | 22 | 58 | | 23 | 32 | | 24 | 23 | | 25 | 24 | | 26 | 12 | | 27 | 23 | | 28 | 19 | | 29 | 16 | | 30 | 23 | | 31 | 51 | | 32 | 28 | | 33 | 25 | | 34 | 34 | | 35 | 44 | | 36 | 1 | | 37 | 30 | | 38 | 17 | | 39 | 21 | | 40 | 51 | | 41 | 3 | | 42 | 31 | | 43 | 14 | | 44 | 13 | | 45 | 30 | | 46 | 31 | | 47 | 59 | | 48 | 46 | | 49 | 27 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 222 | | matches | | 0 | "were dusted" | | 1 | "been postmarked" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 289 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 3 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 271 | | ratio | 0.011 | | matches | | 0 | "The scent that clung to him after they’d—" | | 1 | "He gestured at the cluttered shelves—Eva’s obsession with Enochian, her half-translated grimoires." | | 2 | "Eva had warned her about Luc—how his demon blood made him taste pain like a flavor she’d studied in truffle constellations." |
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| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1638 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 40 | | adverbRatio | 0.02442002442002442 | | lyAdverbCount | 10 | | lyAdverbRatio | 0.006105006105006105 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 271 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 271 | | mean | 8.61 | | std | 5.09 | | cv | 0.592 | | sampleLengths | | 0 | 7 | | 1 | 20 | | 2 | 18 | | 3 | 9 | | 4 | 4 | | 5 | 15 | | 6 | 11 | | 7 | 15 | | 8 | 11 | | 9 | 6 | | 10 | 4 | | 11 | 2 | | 12 | 11 | | 13 | 12 | | 14 | 7 | | 15 | 12 | | 16 | 6 | | 17 | 13 | | 18 | 23 | | 19 | 16 | | 20 | 6 | | 21 | 15 | | 22 | 4 | | 23 | 3 | | 24 | 8 | | 25 | 1 | | 26 | 2 | | 27 | 6 | | 28 | 8 | | 29 | 17 | | 30 | 4 | | 31 | 10 | | 32 | 2 | | 33 | 4 | | 34 | 6 | | 35 | 7 | | 36 | 3 | | 37 | 4 | | 38 | 19 | | 39 | 3 | | 40 | 8 | | 41 | 13 | | 42 | 13 | | 43 | 11 | | 44 | 10 | | 45 | 16 | | 46 | 20 | | 47 | 12 | | 48 | 3 | | 49 | 17 |
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| 55.35% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 10 | | diversityRatio | 0.35424354243542433 | | totalSentences | 271 | | uniqueOpeners | 96 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 6 | | totalSentences | 190 | | matches | | 0 | "Once, he’d shown her how" | | 1 | "Somewhere in the stairwell, a" | | 2 | "Just the syllable before *ma" | | 3 | "Then he snapped it back" | | 4 | "Somehow, the scroll on the" | | 5 | "Then the kettle whistled in" |
| | ratio | 0.032 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 55 | | totalSentences | 190 | | matches | | 0 | "She expected Eva’s frantic face" | | 1 | "He leaned against the frame," | | 2 | "His suit was too crisp" | | 3 | "His left eye glowed amber," | | 4 | "His fingers tapped the cane" | | 5 | "She knew the blade was" | | 6 | "She glanced at the stairwell," | | 7 | "Her temporary flatmate had made" | | 8 | "His smile didn’t touch his" | | 9 | "She stepped back into the" | | 10 | "He shut the door behind" | | 11 | "Her voice sounded too high," | | 12 | "He removed his coat,袖口 frayed" | | 13 | "He gestured at the cluttered" | | 14 | "She set the kettle on," | | 15 | "He flicked ash from a" | | 16 | "She choked, tea sloshing over" | | 17 | "He leaned closer, the air" | | 18 | "Her hand tightened on the" | | 19 | "She set the cup down" |
| | ratio | 0.289 | |
| 44.21% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 158 | | totalSentences | 190 | | matches | | 0 | "The deadbolts snapped back with" | | 1 | "Rory hesitated before turning the" | | 2 | "The smell of cumin and" | | 3 | "She expected Eva’s frantic face" | | 4 | "He leaned against the frame," | | 5 | "His suit was too crisp" | | 6 | "Charcoal pressed to perfection, a" | | 7 | "His left eye glowed amber," | | 8 | "The mismatch had always unsettled" | | 9 | "His fingers tapped the cane" | | 10 | "A rhythm only he could" | | 11 | "The knuckles were dusted with" | | 12 | "She knew the blade was" | | 13 | "She glanced at the stairwell," | | 14 | "Her temporary flatmate had made" | | 15 | "His smile didn’t touch his" | | 16 | "The scent of petrichor and" | | 17 | "Pakistani jasmine, she thought." | | 18 | "The scent that clung to" | | 19 | "Ptolemy’s tail lashed from the" |
| | ratio | 0.832 | |
| 52.63% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 2 | | totalSentences | 190 | | matches | | 0 | "Now the scar on her" | | 1 | "Now Rory saw it in" |
| | ratio | 0.011 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 54 | | technicalSentenceCount | 1 | | matches | | 0 | "Rory hesitated before turning the knob, her fingers brushing the scar on her wrist through the fabric of her apron." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 44 | | uselessAdditionCount | 1 | | matches | | 0 | "Luc deactivated, his blade spinning in midair to catch the silk string" |
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| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 17 | | fancyCount | 2 | | fancyTags | | 0 | "The kettle whistled (whistle)" | | 1 | "she whispered (whisper)" |
| | dialogueSentences | 96 | | tagDensity | 0.177 | | leniency | 0.354 | | rawRatio | 0.118 | | effectiveRatio | 0.042 | |