| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 8 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 22 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 87.76% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1225 | | totalAiIsmAdverbs | 3 | | found | | | highlights | | 0 | "tightly" | | 1 | "truly" | | 2 | "really" |
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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) | |
| 71.43% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1225 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "familiar" | | 1 | "flickered" | | 2 | "fleeting" | | 3 | "wavered" | | 4 | "echoing" | | 5 | "raced" |
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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 | 80 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 2 | | narrationSentences | 80 | | filterMatches | (empty) | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 93 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 41 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 1224 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 9 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 991 | | uniqueNames | 9 | | maxNameDensity | 0.81 | | worstName | "Rory" | | maxWindowNameDensity | 1.5 | | worstWindowName | "Lucien" | | discoveredNames | | Lucien | 4 | | Pussy | 3 | | Rory | 8 | | London | 1 | | Evelyn | 1 | | Regent | 1 | | Park | 1 | | Luc | 1 | | Lilies | 1 |
| | persons | | 0 | "Lucien" | | 1 | "Rory" | | 2 | "Evelyn" | | 3 | "Luc" | | 4 | "Lilies" |
| | places | | | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 62 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 1 | | per1kWords | 0.817 | | wordCount | 1224 | | matches | | 0 | "not for any unbeatable purpose but because they completed each other, because not could almost" |
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| 94.98% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 2 | | totalSentences | 93 | | matches | | 0 | "knew that she" | | 1 | "into that sea" |
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| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 43 | | mean | 28.47 | | std | 18.7 | | cv | 0.657 | | sampleLengths | | 0 | 42 | | 1 | 43 | | 2 | 8 | | 3 | 53 | | 4 | 54 | | 5 | 54 | | 6 | 56 | | 7 | 21 | | 8 | 51 | | 9 | 54 | | 10 | 16 | | 11 | 34 | | 12 | 4 | | 13 | 21 | | 14 | 6 | | 15 | 25 | | 16 | 14 | | 17 | 3 | | 18 | 28 | | 19 | 2 | | 20 | 4 | | 21 | 18 | | 22 | 46 | | 23 | 46 | | 24 | 10 | | 25 | 33 | | 26 | 9 | | 27 | 33 | | 28 | 19 | | 29 | 24 | | 30 | 34 | | 31 | 47 | | 32 | 78 | | 33 | 16 | | 34 | 39 | | 35 | 10 | | 36 | 4 | | 37 | 31 | | 38 | 43 | | 39 | 12 | | 40 | 6 | | 41 | 43 | | 42 | 30 |
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| 100.00% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 0 | | totalSentences | 80 | | matches | (empty) | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 172 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 1 | | semicolonCount | 0 | | flaggedSentences | 1 | | totalSentences | 93 | | ratio | 0.011 | | matches | | 0 | "\"What we had—\" he began, lower back against the bookcase cluttered with scrolls \"—had nothing to do with the benefactor. Something we both could never compel. I don't care about your power. Or the beneficiary. I want to know you.\"" |
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| 96.38% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 861 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 38 | | adverbRatio | 0.04413472706155633 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.006968641114982578 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 93 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 93 | | mean | 13.16 | | std | 8.89 | | cv | 0.676 | | sampleLengths | | 0 | 11 | | 1 | 31 | | 2 | 17 | | 3 | 17 | | 4 | 9 | | 5 | 8 | | 6 | 13 | | 7 | 24 | | 8 | 16 | | 9 | 12 | | 10 | 18 | | 11 | 24 | | 12 | 17 | | 13 | 37 | | 14 | 14 | | 15 | 10 | | 16 | 32 | | 17 | 21 | | 18 | 11 | | 19 | 40 | | 20 | 22 | | 21 | 20 | | 22 | 12 | | 23 | 12 | | 24 | 4 | | 25 | 15 | | 26 | 9 | | 27 | 10 | | 28 | 4 | | 29 | 7 | | 30 | 9 | | 31 | 5 | | 32 | 6 | | 33 | 7 | | 34 | 14 | | 35 | 4 | | 36 | 7 | | 37 | 7 | | 38 | 3 | | 39 | 3 | | 40 | 15 | | 41 | 10 | | 42 | 2 | | 43 | 4 | | 44 | 18 | | 45 | 10 | | 46 | 36 | | 47 | 12 | | 48 | 34 | | 49 | 10 |
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| 69.53% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 7 | | diversityRatio | 0.46236559139784944 | | totalSentences | 93 | | uniqueOpeners | 43 | |
| 100.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 4 | | totalSentences | 76 | | matches | | 0 | "Then she exhaled, or cursed," | | 1 | "Instead, he nodded, pocketed off" | | 2 | "Maybe he would never have" | | 3 | "Then in one swift movement," |
| | ratio | 0.053 | |
| 35.79% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 35 | | totalSentences | 76 | | matches | | 0 | "He kept his own tone" | | 1 | "He wouldn't give her reason" | | 2 | "She returned to her pile" | | 3 | "He followed the curve of" | | 4 | "he said, settling himself against" | | 5 | "She spoke to him like" | | 6 | "he began, lower back against" | | 7 | "She glanced up then, a" | | 8 | "he answered, his amber and" | | 9 | "She froze, and that one" | | 10 | "His gaze never wavered from" | | 11 | "He knew exactly what she" | | 12 | "He couldn't tell her." | | 13 | "He had forgotten." | | 14 | "He wanted to scream." | | 15 | "He wanted to take Rory" | | 16 | "He wanted her back in" | | 17 | "He wanted to go back" | | 18 | "His voice broke on her" | | 19 | "He looked into that sea" |
| | ratio | 0.461 | |
| 85.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 57 | | totalSentences | 76 | | matches | | 0 | "The door creaked open a" | | 1 | "Lucien found himself in the" | | 2 | "He kept his own tone" | | 3 | "He wouldn't give her reason" | | 4 | "The chain rattled as Rory" | | 5 | "She returned to her pile" | | 6 | "Lucien stepped inside, closing the" | | 7 | "He followed the curve of" | | 8 | "he said, settling himself against" | | 9 | "Rory flipped a page, her" | | 10 | "Something flickered across her face," | | 11 | "She spoke to him like" | | 12 | "Lucien closed the distance between" | | 13 | "he began, lower back against" | | 14 | "This close, he caught the" | | 15 | "She glanced up then, a" | | 16 | "he answered, his amber and" | | 17 | "She froze, and that one" | | 18 | "Rory closed the book in" | | 19 | "His gaze never wavered from" |
| | ratio | 0.75 | |
| 65.79% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 1 | | totalSentences | 76 | | matches | | | ratio | 0.013 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 2 | | matches | | 0 | "Lucien found himself in the familiar old scene: standing before her door, searching for the right words." | | 1 | "Rory took a deep, steadying breath, squared her shoulders, and let the Lilies, the memories, and the promises drift away like the petals that separated from the…" |
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| 62.50% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 8 | | uselessAdditionCount | 1 | | matches | | 0 | "She returned, not looking at him as he entered" |
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| 59.09% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "blue eye peered (peer)" | | 1 | "She returned (return)" |
| | dialogueSentences | 22 | | tagDensity | 0.182 | | leniency | 0.364 | | rawRatio | 0.5 | | effectiveRatio | 0.182 | |