| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 13 | | adverbTagCount | 1 | | adverbTags | | 0 | "He spoke quietly [quietly]" |
| | dialogueSentences | 37 | | tagDensity | 0.351 | | leniency | 0.703 | | rawRatio | 0.077 | | effectiveRatio | 0.054 | |
| 92.48% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1330 | | totalAiIsmAdverbs | 2 | | 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) | |
| 43.61% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1330 | | totalAiIsms | 15 | | found | | | highlights | | 0 | "echoed" | | 1 | "perfect" | | 2 | "sanctuary" | | 3 | "gleaming" | | 4 | "silence" | | 5 | "scanned" | | 6 | "unreadable" | | 7 | "chaotic" | | 8 | "flicked" | | 9 | "stomach" | | 10 | "navigating" | | 11 | "flicker" | | 12 | "comforting" | | 13 | "chill" | | 14 | "vibrated" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "hung in the air" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 92 | | matches | (empty) | |
| 96.27% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 3 | | narrationSentences | 92 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 116 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 38 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1318 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 10 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 23 | | wordCount | 1070 | | uniqueNames | 11 | | maxNameDensity | 0.65 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Rory" | | discoveredNames | | Eva | 3 | | Ptolemy | 3 | | Sumerian | 1 | | Rory | 7 | | Moreau | 1 | | French | 1 | | London | 1 | | Mayfair | 1 | | Brick | 1 | | Lane | 1 | | Lucien | 3 |
| | persons | | 0 | "Eva" | | 1 | "Ptolemy" | | 2 | "Rory" | | 3 | "Moreau" | | 4 | "Lucien" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 75 | | glossingSentenceCount | 1 | | matches | | 0 | "as if sensing the shift in the room’s atmosphere, hopped down from his perch and wound his way around Rory’s legs, a soft, comforting pressure" |
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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 | 1318 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 116 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 48 | | mean | 27.46 | | std | 21.36 | | cv | 0.778 | | sampleLengths | | 0 | 74 | | 1 | 6 | | 2 | 79 | | 3 | 66 | | 4 | 52 | | 5 | 22 | | 6 | 1 | | 7 | 33 | | 8 | 12 | | 9 | 4 | | 10 | 40 | | 11 | 52 | | 12 | 5 | | 13 | 14 | | 14 | 52 | | 15 | 61 | | 16 | 5 | | 17 | 24 | | 18 | 7 | | 19 | 62 | | 20 | 5 | | 21 | 32 | | 22 | 51 | | 23 | 7 | | 24 | 16 | | 25 | 14 | | 26 | 37 | | 27 | 31 | | 28 | 6 | | 29 | 17 | | 30 | 26 | | 31 | 17 | | 32 | 26 | | 33 | 5 | | 34 | 23 | | 35 | 25 | | 36 | 29 | | 37 | 32 | | 38 | 23 | | 39 | 12 | | 40 | 10 | | 41 | 56 | | 42 | 8 | | 43 | 5 | | 44 | 73 | | 45 | 16 | | 46 | 21 | | 47 | 24 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 92 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 158 | | matches | | |
| 68.97% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 5 | | semicolonCount | 0 | | flaggedSentences | 3 | | totalSentences | 116 | | ratio | 0.026 | | matches | | 0 | "And his eyes—one the colour of warm amber, the other a pit of absolute black—found hers." | | 1 | "She was acutely aware of her own state of dress—an old university sweatshirt, faded jeans, bare feet on the cool floorboards." | | 2 | "A flicker of something—regret, maybe, or frustration—crossed his features before his mask of cool composure settled back into place." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1081 | | adjectiveStacks | 1 | | stackExamples | | 0 | "small, crescent-shaped scar" |
| | adverbCount | 28 | | adverbRatio | 0.025901942645698426 | | lyAdverbCount | 8 | | lyAdverbRatio | 0.0074005550416281225 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 116 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 116 | | mean | 11.36 | | std | 7.63 | | cv | 0.671 | | sampleLengths | | 0 | 16 | | 1 | 26 | | 2 | 10 | | 3 | 22 | | 4 | 2 | | 5 | 2 | | 6 | 1 | | 7 | 1 | | 8 | 12 | | 9 | 14 | | 10 | 11 | | 11 | 14 | | 12 | 7 | | 13 | 8 | | 14 | 13 | | 15 | 7 | | 16 | 12 | | 17 | 12 | | 18 | 19 | | 19 | 16 | | 20 | 14 | | 21 | 38 | | 22 | 9 | | 23 | 13 | | 24 | 1 | | 25 | 8 | | 26 | 15 | | 27 | 10 | | 28 | 7 | | 29 | 5 | | 30 | 4 | | 31 | 3 | | 32 | 12 | | 33 | 25 | | 34 | 4 | | 35 | 15 | | 36 | 4 | | 37 | 15 | | 38 | 14 | | 39 | 5 | | 40 | 10 | | 41 | 4 | | 42 | 4 | | 43 | 10 | | 44 | 15 | | 45 | 13 | | 46 | 10 | | 47 | 5 | | 48 | 24 | | 49 | 12 |
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| 52.01% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 8 | | diversityRatio | 0.35344827586206895 | | totalSentences | 116 | | uniqueOpeners | 41 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 0.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 52 | | totalSentences | 87 | | matches | | 0 | "She set the toast down" | | 1 | "She drew back the first," | | 2 | "She eased the door open" | | 3 | "He filled the space, a" | | 4 | "His charcoal suit was immaculate," | | 5 | "He gave a slight, formal" | | 6 | "His gaze swept over the" | | 7 | "His voice was just as" | | 8 | "It did something unsettling to" | | 9 | "Her own voice came out" | | 10 | "She didn’t move." | | 11 | "Her fingers were white where" | | 12 | "He was the last person" | | 13 | "He waited, impossibly patient." | | 14 | "He held a cane, its" | | 15 | "He didn’t belong here." | | 16 | "He was Mayfair townhouses and" | | 17 | "She undid the chain." | | 18 | "She stepped back, pulling the" | | 19 | "He moved with a liquid" |
| | ratio | 0.598 | |
| 0.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 83 | | totalSentences | 87 | | matches | | 0 | "The knock came sharp and" | | 1 | "Rory froze, a half-eaten slice" | | 2 | "A ginger tabby, Ptolemy, lifted" | | 3 | "She set the toast down" | | 4 | "The flat was a fortress" | | 5 | "Rory’s hand moved over the" | | 6 | "She drew back the first," | | 7 | "The second slid with a" | | 8 | "The third turned with a" | | 9 | "She eased the door open" | | 10 | "Lucien Moreau stood in the" | | 11 | "He filled the space, a" | | 12 | "His charcoal suit was immaculate," | | 13 | "Platinum blond hair, slicked back" | | 14 | "A breath she hadn’t realised" | | 15 | "The world seemed to shrink" | | 16 | "He gave a slight, formal" | | 17 | "His gaze swept over the" | | 18 | "His voice was just as" | | 19 | "A low, smooth cadence with" |
| | ratio | 0.954 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 87 | | matches | (empty) | | ratio | 0 | |
| 84.55% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 49 | | technicalSentenceCount | 4 | | matches | | 0 | "Not Eva’s knock, which was more of an impatient drumming, and not the delivery driver from the takeaway downstairs, who usually just hollered up the stairwell." | | 1 | "They were two different worlds colliding in a room that smelled of dust and cardamom." | | 2 | "He walked past her, his movements economical, navigating the labyrinth of books with an ease that grated on her." | | 3 | "Ptolemy, as if sensing the shift in the room’s atmosphere, hopped down from his perch and wound his way around Rory’s legs, a soft, comforting pressure." |
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| 86.54% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 13 | | uselessAdditionCount | 1 | | matches | | 0 | "He spoke quietly, his voice a low thrum that vibrated through her" |
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| 68.92% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 3 | | fancyCount | 3 | | fancyTags | | 0 | "He stated (state)" | | 1 | "He corrected (correct)" | | 2 | "He spoke quietly (speak)" |
| | dialogueSentences | 37 | | tagDensity | 0.081 | | leniency | 0.162 | | rawRatio | 1 | | effectiveRatio | 0.162 | |